From 080f0f78d301c1a2e2d69a27c2492fb3e011cdab Mon Sep 17 00:00:00 2001
From: rmflight <r.flight79@gmail.com>
Date: Sat, 27 Jan 2024 10:28:55 -0500
Subject: [PATCH] fixes a missed instance of rows as samples

---
 R/kendalltau.R                            |  1 -
 README.Rmd                                |  6 +++---
 README.md                                 | 16 ++++++++--------
 docs/404.html                             |  2 +-
 docs/CODE_OF_CONDUCT.html                 |  2 +-
 docs/LICENSE-text.html                    |  2 +-
 docs/LICENSE.html                         |  2 +-
 docs/articles/ici-kendalltau.html         | 12 ++++++------
 docs/articles/index.html                  |  2 +-
 docs/authors.html                         |  6 +++---
 docs/index.html                           | 18 +++++++++---------
 docs/news/index.html                      |  2 +-
 docs/pkgdown.yml                          |  2 +-
 docs/reference/cor_matrix_2_long_df.html  |  2 +-
 docs/reference/disable_logging.html       |  2 +-
 docs/reference/enable_logging.html        |  2 +-
 docs/reference/ici_kendalltau.html        |  2 +-
 docs/reference/ici_kendalltau_ref.html    |  2 +-
 docs/reference/ici_kt.html                |  2 +-
 docs/reference/index.html                 |  2 +-
 docs/reference/kt_fast.html               |  2 +-
 docs/reference/log_memory.html            |  2 +-
 docs/reference/log_message.html           |  2 +-
 docs/reference/long_df_2_cor_matrix.html  |  2 +-
 docs/reference/pairwise_completeness.html |  2 +-
 docs/reference/show_progress.html         |  2 +-
 docs/search.json                          |  2 +-
 vignettes/ici-kendalltau.Rmd              |  2 +-
 28 files changed, 51 insertions(+), 52 deletions(-)

diff --git a/R/kendalltau.R b/R/kendalltau.R
index a493b50..05bf07e 100644
--- a/R/kendalltau.R
+++ b/R/kendalltau.R
@@ -338,7 +338,6 @@ ici_kendalltau = function(data_matrix,
                              return_matrix = TRUE){
   
   do_log_memory = get("memory", envir = icikt_logger)
-  # assume row-wise (because that is what the description states), so need to transpose
   exclude_loc = matrix(FALSE, nrow = nrow(data_matrix), ncol = ncol(data_matrix))
   
   if (is.data.frame(data_matrix)) {
diff --git a/README.Rmd b/README.Rmd
index a2757ab..14da6aa 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -59,10 +59,10 @@ The functions that implement this include:
   * The option `perspective` will control how the `NA` values influence ties.
   * When comparing samples, you likely want to use `perspective = "global"`.
 * `ici_kendallt`: Handles comparisons for a large matrix.
-  * Rows are samples, columns are features.
+  * Rows are features, columns are samples.
   * Implicitly parallel, but have to call:
-    * library(furrr)
-    * plan(multiprocess)
+    * `library(furrr)`
+    * `plan(multiprocess)`
   * Otherwise will only use a single core.
   
 ## Examples
diff --git a/README.md b/README.md
index 56fb0b6..7435e20 100644
--- a/README.md
+++ b/README.md
@@ -60,10 +60,10 @@ The functions that implement this include:
   - When comparing samples, you likely want to use
     `perspective = "global"`.
 - `ici_kendallt`: Handles comparisons for a large matrix.
-  - Rows are samples, columns are features.
+  - Rows are features, columns are samples.
   - Implicitly parallel, but have to call:
-    - library(furrr)
-    - plan(multiprocess)
+    - `library(furrr)`
+    - `plan(multiprocess)`
   - Otherwise will only use a single core.
 
 ## Examples
@@ -136,10 +136,10 @@ microbenchmark(
   times = 5
 )
 #> Unit: microseconds
-#>                           expr      min        lq      mean    median        uq       max
-#>  cor(x, y, method = "kendall") 13568.01 13818.243 14017.885 14090.436 14174.800 14437.933
-#>         ici_kt(x, y, "global")   261.84   272.733   304.271   287.571   335.669   363.542
-#>       ici_kt(x2, y2, "global") 14631.30 15614.509 16419.494 16340.620 17646.365 17864.673
+#>                           expr       min        lq       mean    median        uq       max
+#>  cor(x, y, method = "kendall") 11506.697 11670.094 12169.6628 12006.418 12482.883 13182.222
+#>         ici_kt(x, y, "global")   243.866   250.125   294.6542   275.104   320.058   384.118
+#>       ici_kt(x2, y2, "global") 13467.011 13739.312 14658.5050 14945.446 14987.140 16153.616
 #>  neval
 #>      5
 #>      5
@@ -202,7 +202,7 @@ r_4
 #> 3 s4 s4    0 1.0000000      0 1.000000 1.0000000
 #> 
 #> $run_time
-#> [1] 0.0196352
+#> [1] 0.01606894
 ```
 
 ## Code of Conduct
diff --git a/docs/404.html b/docs/404.html
index 5c1ff30..30f4568 100644
--- a/docs/404.html
+++ b/docs/404.html
@@ -24,7 +24,7 @@
     
     <a class="navbar-brand me-2" href="index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/CODE_OF_CONDUCT.html b/docs/CODE_OF_CONDUCT.html
index 5fd79c6..c62371e 100644
--- a/docs/CODE_OF_CONDUCT.html
+++ b/docs/CODE_OF_CONDUCT.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html
index f031faa..0819d78 100644
--- a/docs/LICENSE-text.html
+++ b/docs/LICENSE-text.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/LICENSE.html b/docs/LICENSE.html
index ab51d25..feb45ca 100644
--- a/docs/LICENSE.html
+++ b/docs/LICENSE.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/articles/ici-kendalltau.html b/docs/articles/ici-kendalltau.html
index 4bf816e..95c3fba 100644
--- a/docs/articles/ici-kendalltau.html
+++ b/docs/articles/ici-kendalltau.html
@@ -26,7 +26,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -284,7 +284,7 @@ <h2 id="functions">Functions<a class="anchor" aria-label="anchor" href="#functio
 <li>
 <code>ici_kendallt</code>: Handles comparisons for a matrix.
 <ul>
-<li>Rows are samples, columns are features.</li>
+<li>Rows are features, columns are samples.</li>
 <li>Implicitly parallel, but have to call:
 <ul>
 <li><code><a href="https://github.com/DavisVaughan/furrr" class="external-link">library(furrr)</a></code></li>
@@ -324,11 +324,11 @@ <h2 id="speed">Speed<a class="anchor" aria-label="anchor" href="#speed"></a>
 <span><span class="op">)</span></span>
 <span><span class="co">#&gt; Unit: microseconds</span></span>
 <span><span class="co">#&gt;                           expr       min        lq       mean    median</span></span>
-<span><span class="co">#&gt;  cor(x, y, method = "kendall") 13491.985 13985.445 14525.5088 14381.588</span></span>
-<span><span class="co">#&gt;         ici_kt(x, y, "global")   301.179   315.922   370.4616   331.543</span></span>
+<span><span class="co">#&gt;  cor(x, y, method = "kendall") 12781.169 13088.783 13795.1100 13290.629</span></span>
+<span><span class="co">#&gt;         ici_kt(x, y, "global")   261.498   304.518   335.7076   305.834</span></span>
 <span><span class="co">#&gt;         uq       max neval</span></span>
-<span><span class="co">#&gt;  14596.294 16172.232     5</span></span>
-<span><span class="co">#&gt;    380.869   522.795     5</span></span></code></pre></div>
+<span><span class="co">#&gt;  14382.628 15432.341     5</span></span>
+<span><span class="co">#&gt;    327.014   479.674     5</span></span></code></pre></div>
 <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/all.equal.html" class="external-link">all.equal</a></span><span class="op">(</span><span class="fu"><a href="../reference/ici_kt.html">ici_kt</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span>, <span class="st">"global"</span><span class="op">)</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span>, <span class="fu"><a href="https://rdrr.io/r/stats/cor.html" class="external-link">cor</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span>, method <span class="op">=</span> <span class="st">"kendall"</span><span class="op">)</span><span class="op">)</span></span>
 <span><span class="co">#&gt; [1] TRUE</span></span></code></pre></div>
diff --git a/docs/articles/index.html b/docs/articles/index.html
index f719324..d8468b7 100644
--- a/docs/articles/index.html
+++ b/docs/articles/index.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/authors.html b/docs/authors.html
index f111c7f..866bf5e 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -68,13 +68,13 @@ <h2 id="citation">Citation</h2>
 
       <p>Flight RM, Moseley HN (2024).
 <em>ICIKendallTau: Calculates information-content-informed Kendall-tau</em>.
-R package version 1.0.1, <a href="https://moseleybioinformaticslab.github.io/ICIKendallTauhttps://github.com/moseleybioinformaticslab/ICIKendallTau" class="external-link">https://moseleybioinformaticslab.github.io/ICIKendallTauhttps://github.com/moseleybioinformaticslab/ICIKendallTau</a>. 
+R package version 1.0.2, <a href="https://moseleybioinformaticslab.github.io/ICIKendallTauhttps://github.com/moseleybioinformaticslab/ICIKendallTau" class="external-link">https://moseleybioinformaticslab.github.io/ICIKendallTauhttps://github.com/moseleybioinformaticslab/ICIKendallTau</a>. 
 </p>
       <pre>@Manual{,
   title = {ICIKendallTau: Calculates information-content-informed Kendall-tau},
   author = {Robert M Flight and Hunter NB Moseley},
   year = {2024},
-  note = {R package version 1.0.1},
+  note = {R package version 1.0.2},
   url = {https://moseleybioinformaticslab.github.io/ICIKendallTau
 https://github.com/moseleybioinformaticslab/ICIKendallTau},
 }</pre>
diff --git a/docs/index.html b/docs/index.html
index 9e161dc..291991f 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -30,7 +30,7 @@
     
     <a class="navbar-brand me-2" href="index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -120,11 +120,11 @@ <h2 id="package-functions">Package Functions<a class="anchor" aria-label="anchor
 <li>
 <code>ici_kendallt</code>: Handles comparisons for a large matrix.
 <ul>
-<li>Rows are samples, columns are features.</li>
+<li>Rows are features, columns are samples.</li>
 <li>Implicitly parallel, but have to call:
 <ul>
-<li>library(furrr)</li>
-<li>plan(multiprocess)</li>
+<li><code><a href="https://github.com/DavisVaughan/furrr" class="external-link">library(furrr)</a></code></li>
+<li><code>plan(multiprocess)</code></li>
 </ul>
 </li>
 <li>Otherwise will only use a single core.</li>
@@ -187,10 +187,10 @@ <h2 id="is-it-fast">Is It Fast?<a class="anchor" aria-label="anchor" href="#is-i
 <span>  times <span class="op">=</span> <span class="fl">5</span></span>
 <span><span class="op">)</span></span>
 <span><span class="co">#&gt; Unit: microseconds</span></span>
-<span><span class="co">#&gt;                           expr      min        lq      mean    median        uq       max</span></span>
-<span><span class="co">#&gt;  cor(x, y, method = "kendall") 13568.01 13818.243 14017.885 14090.436 14174.800 14437.933</span></span>
-<span><span class="co">#&gt;         ici_kt(x, y, "global")   261.84   272.733   304.271   287.571   335.669   363.542</span></span>
-<span><span class="co">#&gt;       ici_kt(x2, y2, "global") 14631.30 15614.509 16419.494 16340.620 17646.365 17864.673</span></span>
+<span><span class="co">#&gt;                           expr       min        lq       mean    median        uq       max</span></span>
+<span><span class="co">#&gt;  cor(x, y, method = "kendall") 11506.697 11670.094 12169.6628 12006.418 12482.883 13182.222</span></span>
+<span><span class="co">#&gt;         ici_kt(x, y, "global")   243.866   250.125   294.6542   275.104   320.058   384.118</span></span>
+<span><span class="co">#&gt;       ici_kt(x2, y2, "global") 13467.011 13739.312 14658.5050 14945.446 14987.140 16153.616</span></span>
 <span><span class="co">#&gt;  neval</span></span>
 <span><span class="co">#&gt;      5</span></span>
 <span><span class="co">#&gt;      5</span></span>
@@ -231,7 +231,7 @@ <h2 id="many-many-comparisons">Many Many Comparisons<a class="anchor" aria-label
 <span><span class="co">#&gt; 3 s4 s4    0 1.0000000      0 1.000000 1.0000000</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; $run_time</span></span>
-<span><span class="co">#&gt; [1] 0.0196352</span></span></code></pre></div>
+<span><span class="co">#&gt; [1] 0.01606894</span></span></code></pre></div>
 </div>
 <div class="section level2">
 <h2 id="code-of-conduct">Code of Conduct<a class="anchor" aria-label="anchor" href="#code-of-conduct"></a>
diff --git a/docs/news/index.html b/docs/news/index.html
index c9f83a8..ec2219f 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 6ecb1f3..36b9e69 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -3,5 +3,5 @@ pkgdown: 2.0.7
 pkgdown_sha: ~
 articles:
   ici-kendalltau: ici-kendalltau.html
-last_built: 2024-01-27T02:43Z
+last_built: 2024-01-27T15:25Z
 
diff --git a/docs/reference/cor_matrix_2_long_df.html b/docs/reference/cor_matrix_2_long_df.html
index ad19733..3e14548 100644
--- a/docs/reference/cor_matrix_2_long_df.html
+++ b/docs/reference/cor_matrix_2_long_df.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/disable_logging.html b/docs/reference/disable_logging.html
index 6b3ca4a..aba9d19 100644
--- a/docs/reference/disable_logging.html
+++ b/docs/reference/disable_logging.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/enable_logging.html b/docs/reference/enable_logging.html
index aba83ea..b0a6339 100644
--- a/docs/reference/enable_logging.html
+++ b/docs/reference/enable_logging.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/ici_kendalltau.html b/docs/reference/ici_kendalltau.html
index 0909174..f909a1b 100644
--- a/docs/reference/ici_kendalltau.html
+++ b/docs/reference/ici_kendalltau.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/ici_kendalltau_ref.html b/docs/reference/ici_kendalltau_ref.html
index 7dc9f6c..8bc41e5 100644
--- a/docs/reference/ici_kendalltau_ref.html
+++ b/docs/reference/ici_kendalltau_ref.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/ici_kt.html b/docs/reference/ici_kt.html
index 7e600b2..db801b3 100644
--- a/docs/reference/ici_kt.html
+++ b/docs/reference/ici_kt.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">ICIKendallTau</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.2</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/docs/reference/index.html b/docs/reference/index.html
index dc8fc3a..51268bc 100644
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index 3d9615f..64e6fdc 100644
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@@ -10,7 +10,7 @@
     
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index bf09c73..242aa26 100644
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Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement rflight79@gmail.com. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. 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Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.0, available https://www.contributor-covenant.org/version/2/0/ code_of_conduct.html. Community Impact Guidelines inspired Mozilla’s code conduct enforcement ladder. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https:// www.contributor-covenant.org/translations.","code":""},{"path":"/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2021 Robert M Flight & Hunter NB Moseley Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"/articles/ici-kendalltau.html","id":"problem","dir":"Articles","previous_headings":"","what":"Problem","title":"Information-Content-Informed Kendall Tau Correlation","text":"handle missing data (.e. NA’s) calculating correlation two variables. However, whether observation made semi-quantitative information many analytical measurements sensitivity limits. .e. many cases, missing observations “missing--random”, “missing---random” due falling detection limit. cases, NA informative.","code":""},{"path":"/articles/ici-kendalltau.html","id":"approach","dir":"Articles","previous_headings":"","what":"Approach","title":"Information-Content-Informed Kendall Tau Correlation","text":"Kendall Tau Correlation coefficient calculates correlation based number concordant discordant pairs: \\(\\tau = \\frac{ | pairs_{concordant} | - | pairs_{discordant} |}{\\binom{n}{2}}\\) pair two x-y data points. \\(x_i > x_j\\) \\(y_i > y_j\\) \\(x_i < x_j\\) \\(y_i < y_j\\) \\(x_i > x_j\\) \\(y_i < y_j\\) \\(x_i < x_j\\) \\(y_i > y_j\\) definitions can expanded handle missing observations: \\(x_i > x_j\\) \\(y_i > y_j\\) \\(x_i < x_j\\) \\(y_i < y_j\\) \\(x_i > x_j\\) \\(y_i \\& !y_j\\) \\(x_i < x_j\\) \\(!y_i \\& y_j\\) \\(x_i \\& !x_j\\) \\(y_i > y_j\\) \\(!x_i \\& x_j\\) \\(y_i < y_j\\) \\(x_i \\& !x_j\\) \\(y_i \\& !y_j\\) (used local perspective version) \\(x_i \\& x_j\\) \\(!y_i \\& y_j\\) (used local perspective version) \\(x_i > x_j\\) \\(y_i < y_j\\) \\(x_i < x_j\\) \\(y_i > y_j\\) \\(x_i > x_j\\) \\(!y_i \\& y_j\\) \\(x_i < x_j\\) \\(y_i \\& !y_j\\) \\(x_i \\& !x_j\\) \\(y_i < y_j\\) \\(!x_i \\& x_j\\) \\(y_i > y_j\\) \\(x_i \\& !x_j\\) \\(!y_i \\& y_j\\) (used local perspective version) \\(!x_i \\& x_j\\) \\(y_i \\& !y_j\\) (used local perspective version) Also data points missing x y values naturally reduce strength correlation value, since can neither concordant discordant another (NA, NA) pair, impact denominator. equivalent removing last two concordant discordant pair tests.","code":""},{"path":"/articles/ici-kendalltau.html","id":"handling-tied-values","dir":"Articles","previous_headings":"","what":"Handling Tied Values","title":"Information-Content-Informed Kendall Tau Correlation","text":"base Kendall tau correlation must adjusted handle tied values, ie. tau-b version equation. \\[\\tau = \\frac{ | pairs_{concordant}  | -  | pairs_{discordant}  |}{\\sqrt{ ( n_0 - n_{xtie}  )  ( n_0 - n_{ytie}  )}} \\] : \\(n_0 = \\frac{n \\left ( n - 1 \\right )}{2}\\) \\(n_{xtie} = \\sum_{}^{} \\frac{t_{xi} \\left ( t_{xi} - 1 \\right )}{2}\\) \\(n_{ytie} = \\sum_{}^{} \\frac{t_{yi} \\left ( t_{yi} - 1 \\right )}{2}\\) \\(t_{xi}\\) - size ith group tied x values. \\(t_{yi}\\) - size ith group tied y values. local perspective, number NAs x y can treated group tied values calculation \\(n_{xtie}\\) \\(n_{ytie}\\), respectively.","code":""},{"path":"/articles/ici-kendalltau.html","id":"scaling-by-the-correlation-with-the-highest-information-content","dir":"Articles","previous_headings":"","what":"Scaling by the correlation with the highest information content","title":"Information-Content-Informed Kendall Tau Correlation","text":"generating correlation matrix (heatmap) large analytical datasets, number observations common can become quite low two variables. becomes advantageous scale pair variables highest information content. One objective scaling factor highest possible absolute correlation maximum information content observed across dataset, dividing maximum possible absolute correlation scale whole dataset appropriately. \\[maxcorr = \\frac{\\binom{n-m}{2} + n * m}{\\binom{n-m}{2} + n * m + \\binom{m}{2}}\\] : Choose two variables least number missing values across dataset. n length variables. formula based perfect correlation given number (NA,NA) pairs added.","code":""},{"path":"/articles/ici-kendalltau.html","id":"functions","dir":"Articles","previous_headings":"","what":"Functions","title":"Information-Content-Informed Kendall Tau Correlation","text":"functions implement include: option perspective control NA values influence ties. comparing multiple samples, likely want use perspective = \"global\". Rows samples, columns features. library(furrr) plan(multiprocess) Otherwise use single core.","code":""},{"path":"/articles/ici-kendalltau.html","id":"implementation","dir":"Articles","previous_headings":"","what":"Implementation","title":"Information-Content-Informed Kendall Tau Correlation","text":"turns , think really hard, truly necessary replace missing values vector value smaller minimum value one. local version, first remove common missing values vector. C++ implementation explicitly can speed, instead wrapping {stats::cor} function. also use double merge-sort algorithm, translating {scipy:: ::stats::kendalltau} function C++ using {Rcpp}.","code":""},{"path":"/articles/ici-kendalltau.html","id":"speed","dir":"Articles","previous_headings":"","what":"Speed","title":"Information-Content-Informed Kendall Tau Correlation","text":"","code":"x = rnorm(1000) y = rnorm(1000)  library(microbenchmark)  microbenchmark(   cor(x, y, method = \"kendall\"),   ici_kt(x, y, \"global\"),   times = 5 ) #> Unit: microseconds #>                           expr       min        lq       mean    median #>  cor(x, y, method = \"kendall\") 13491.985 13985.445 14525.5088 14381.588 #>         ici_kt(x, y, \"global\")   301.179   315.922   370.4616   331.543 #>         uq       max neval #>  14596.294 16172.232     5 #>    380.869   522.795     5 all.equal(ici_kt(x, y, \"global\")[[1]], cor(x, y, method = \"kendall\")) #> [1] TRUE"},{"path":"/articles/ici-kendalltau.html","id":"running-many","dir":"Articles","previous_headings":"","what":"Running Many","title":"Information-Content-Informed Kendall Tau Correlation","text":"Just like R’s cor function, can also calculate correlations many variables. Let’s make fake data try .","code":"set.seed(1234)  s1 = sort(rnorm(1000, mean = 100, sd = 10)) s2 = s1 + 10 s2[sample(length(s1), 100)] = s1[1:100] s3 = s1 s3[c(1:10, sample(length(s1), 5))] = NA  matrix_1 = cbind(s1, s2, s3)  r_1 = ici_kendalltau(matrix_1) r_1$cor #>           s1        s2        s3 #> s1 1.0000000 0.8049209 0.9907488 #> s2 0.8049209 1.0000000 0.7956652 #> s3 0.9907488 0.7956652 0.9850000"},{"path":"/articles/ici-kendalltau.html","id":"parallelism","dir":"Articles","previous_headings":"","what":"Parallelism","title":"Information-Content-Informed Kendall Tau Correlation","text":"{future} {furrr} packages installed, also possible split set matrix comparisons across compute resources multiprocessing engine registered {future}.","code":"library(furrr) future::plan(multicore, workers = 4) r_2 = ici_kendalltau(matrix_1)"},{"path":"/articles/ici-kendalltau.html","id":"many-many-comparisons","dir":"Articles","previous_headings":"","what":"Many Many Comparisons","title":"Information-Content-Informed Kendall Tau Correlation","text":"case hundreds thousands comparisons done, result matrices can become , large, require lots memory storage. also inefficient, lower upper triangular components stored. alternative storage format data.frame, single row comparison performed. actually results stored internally, converted matrix form requested (default).s keep data.frame output, add argument return_matrix=FALSE call ici_kendalltau.","code":"r_3 = ici_kendalltau(matrix_1, return_matrix = FALSE) r_3$cor #>   s1 s2 core       raw pvalue    taumax       cor #> 1 s1 s2    1 0.8049209      0 1.0000000 0.8049209 #> 2 s1 s3    1 0.9907488      0 0.9998949 0.9907488 #> 3 s2 s3    1 0.7956652      0 0.9998949 0.7956652 #> 4 s1 s1    0 1.0000000      0 1.0000000 1.0000000 #> 5 s2 s2    0 1.0000000      0 1.0000000 1.0000000 #> 6 s3 s3    0 0.9850000      0 1.0000000 0.9850000"},{"path":"/articles/ici-kendalltau.html","id":"logging","dir":"Articles","previous_headings":"","what":"Logging","title":"Information-Content-Informed Kendall Tau Correlation","text":"possible log steps done much memory used (Linux least) correlations calculated. can useful running large sets correlations making sure much memory isn’t used, example. enable logging, {logger} package must installed. log_file supplied, one created current date time. default, ici_kendalltau also shows progress messages, want turn , can :","code":"enable_logging() enable_logging(\"/tmp/my_ici_run.log\") show_progress(FALSE)"},{"path":"/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Robert M Flight. Author, maintainer. Hunter NB Moseley. Author.","code":""},{"path":"/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Flight RM, Moseley HN (2024). ICIKendallTau: Calculates information-content-informed Kendall-tau. R package version 1.0.1, https://moseleybioinformaticslab.github.io/ICIKendallTauhttps://github.com/moseleybioinformaticslab/ICIKendallTau.","code":"@Manual{,   title = {ICIKendallTau: Calculates information-content-informed Kendall-tau},   author = {Robert M Flight and Hunter NB Moseley},   year = {2024},   note = {R package version 1.0.1},   url = {https://moseleybioinformaticslab.github.io/ICIKendallTau https://github.com/moseleybioinformaticslab/ICIKendallTau}, }"},{"path":"/index.html","id":"icikendalltau","dir":"","previous_headings":"","what":"Calculates information-content-informed Kendall-tau","title":"Calculates information-content-informed Kendall-tau","text":"can see pkgdown site .","code":""},{"path":"/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Calculates information-content-informed Kendall-tau","text":"can install current version ICIKendallTau via GitHub: can also install Windows Mac binaries using r-universe:","code":"remotes::install_github(\"MoseleyBioinformaticsLab/ICIKendallTau\") options(repos = c(     moseleybioinformaticslab = 'https://moseleybioinformaticslab.r-universe.dev',     CRAN = \"https://cloud.r-project.org\")) install.packages(\"ICIKendallTau\")"},{"path":"/index.html","id":"problem","dir":"","previous_headings":"","what":"Problem","title":"Calculates information-content-informed Kendall-tau","text":"handle missing data (.e. NA’s) calculating correlation two variables. However, whether observation present missing semi-quantitative information many analytical measurements sensitivity limits. .e. many cases, missing observations “missing--random”, “missing---random” due falling detection limit. cases, NA informative. Therefore, analytical measurements (gene expression, proteomics, metabolomics), missing measurements included, contribute correlation. want read solve problem, see package vignette.","code":""},{"path":"/index.html","id":"package-functions","dir":"","previous_headings":"","what":"Package Functions","title":"Calculates information-content-informed Kendall-tau","text":"functions implement include: option perspective control NA values influence ties. comparing samples, likely want use perspective = \"global\". Rows samples, columns features. library(furrr) plan(multiprocess) Otherwise use single core.","code":""},{"path":"/index.html","id":"examples","dir":"","previous_headings":"","what":"Examples","title":"Calculates information-content-informed Kendall-tau","text":"common case large matrix independent samples (columns) measured features samples (.e. gene expression). make artificial data show correlation changes introduce missingness. Now introduce missing values low end one. just simplest thing introduce NA values bottom set.","code":"set.seed(1234) library(ICIKendallTau)  s1 = sort(rnorm(1000, mean = 100, sd = 10)) s2 = s1 + 10   matrix_1 = cbind(s1, s2)  r_1 = ici_kendalltau(matrix_1) r_1$cor #>    s1 s2 #> s1  1  1 #> s2  1  1 s3 = s1 s3[sample(100, 50)] = NA  s4 = s2 s4[sample(100, 50)] = NA  matrix_2 = cbind(s3, s4) r_2 = ici_kendalltau(matrix_2) r_2$cor #>           s3        s4 #> s3 1.0000000 0.9944616 #> s4 0.9944616 1.0000000"},{"path":"/index.html","id":"is-it-fast","dir":"","previous_headings":"","what":"Is It Fast?","title":"Calculates information-content-informed Kendall-tau","text":"C++ code implementation (thanks {Rcpp}!) based SciPy implementation, uses two merge sorts ranks vector, looks differences . fastest method know , complexity O(nlogn). naive way computing , explicitly examines pairs, complexity n^2. implementation compared {pcaPP::cov.fk} function, use {Rcpp} inefficient copying vectors makes 3X slower one. honestly isn’t bad. case 40,000 features, average time modern CPU 14 milliseconds. course, want use calculate Kendall-tau-b without incorporating missingness, can just fine well. also provide kt_fast function, want something treats NA values similarly stats::cor.","code":"library(microbenchmark) x = rnorm(1000) y = rnorm(1000)  x2 = rnorm(40000) y2 = rnorm(40000)  library(microbenchmark)  microbenchmark(   cor(x, y, method = \"kendall\"),   ici_kt(x, y, \"global\"),   ici_kt(x2, y2, \"global\"),   times = 5 ) #> Unit: microseconds #>                           expr      min        lq      mean    median        uq       max #>  cor(x, y, method = \"kendall\") 13568.01 13818.243 14017.885 14090.436 14174.800 14437.933 #>         ici_kt(x, y, \"global\")   261.84   272.733   304.271   287.571   335.669   363.542 #>       ici_kt(x2, y2, \"global\") 14631.30 15614.509 16419.494 16340.620 17646.365 17864.673 #>  neval #>      5 #>      5 #>      5 k_tau = ici_kt(x, y, \"global\") all.equal(k_tau[[1]] ,cor(x, y, method = \"kendall\")) #> [1] TRUE k_tau_fast = kt_fast(x, y) k_tau_fast #>          tau       pvalue  #> -0.003411411  0.871672260"},{"path":"/index.html","id":"parallelism","dir":"","previous_headings":"","what":"Parallelism","title":"Calculates information-content-informed Kendall-tau","text":"{future} {furrr} packages installed, also possible split set matrix comparisons across compute resources multiprocessing engine registered {future}.","code":"library(furrr) future::plan(multicore, workers = 4) r_3 = ici_kendalltau(matrix_2)"},{"path":"/index.html","id":"many-many-comparisons","dir":"","previous_headings":"","what":"Many Many Comparisons","title":"Calculates information-content-informed Kendall-tau","text":"case hundreds thousands comparisons done, result matrices can become , large, require lots memory storage. also inefficient, lower upper triangular components stored. alternative storage format data.frame, single row comparison performed. actually results stored internally, converted matrix form requested (default).s keep data.frame output, add argument return_matrix=FALSE call ici_kendalltau.","code":"r_4 = ici_kendalltau(matrix_2, return_matrix = FALSE) r_4 #> $cor #>   s1 s2 core       raw pvalue   taumax       cor #> 1 s3 s4    1 0.9924359      0 0.997963 0.9944616 #> 2 s3 s3    0 1.0000000      0 1.000000 1.0000000 #> 3 s4 s4    0 1.0000000      0 1.000000 1.0000000 #>  #> $run_time #> [1] 0.0196352"},{"path":"/index.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Calculates information-content-informed Kendall-tau","text":"Please note ICIKendallTau project released Contributor Code Conduct. contributing project, agree abide terms.","code":""},{"path":"/reference/cor_matrix_2_long_df.html","id":null,"dir":"Reference","previous_headings":"","what":"convert matrix to data.frame — cor_matrix_2_long_df","title":"convert matrix to data.frame — cor_matrix_2_long_df","text":"Given square correlation matrix, converts long data.frame, three columns.","code":""},{"path":"/reference/cor_matrix_2_long_df.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"convert matrix to data.frame — cor_matrix_2_long_df","text":"","code":"cor_matrix_2_long_df(in_matrix)"},{"path":"/reference/cor_matrix_2_long_df.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"convert matrix to data.frame — cor_matrix_2_long_df","text":"in_matrix correlation matrix","code":""},{"path":"/reference/cor_matrix_2_long_df.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"convert matrix to data.frame — cor_matrix_2_long_df","text":"data.frame","code":""},{"path":"/reference/cor_matrix_2_long_df.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"convert matrix to data.frame — cor_matrix_2_long_df","text":"data.frame contains three columns: s1: first entry comparison s2: second entry comparison cor: correlation value","code":""},{"path":"/reference/disable_logging.html","id":null,"dir":"Reference","previous_headings":"","what":"turn logging off — disable_logging","title":"turn logging off — disable_logging","text":"may good reasons turn logging turned . basically tells package logger available.","code":""},{"path":"/reference/disable_logging.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"turn logging off — disable_logging","text":"","code":"disable_logging()"},{"path":"/reference/enable_logging.html","id":null,"dir":"Reference","previous_headings":"","what":"turn logging on — enable_logging","title":"turn logging on — enable_logging","text":"Choose enable logging, specific file desired.","code":""},{"path":"/reference/enable_logging.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"turn logging on — enable_logging","text":"","code":"enable_logging(log_file = NULL, memory = FALSE)"},{"path":"/reference/enable_logging.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"turn logging on — enable_logging","text":"log_file file log memory provide memory logging ? available Linux MacOS","code":""},{"path":"/reference/enable_logging.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"turn logging on — enable_logging","text":"Uses logger package hood, suggested dependencies. logging enabled nice see things starting stopping, exactly done, without needing write messages console. especially useful getting errors, really see , can add \"memory\" logging see running memory. Default log file pattern: YYYY.MM.DD.HH.MM.SS_ICIKendallTau_run.log","code":""},{"path":"/reference/ici_kendalltau.html","id":null,"dir":"Reference","previous_headings":"","what":"information-content-informed kendall tau — ici_kendalltau","title":"information-content-informed kendall tau — ici_kendalltau","text":"Given data-matrix, computes information-theoretic Kendall-tau-b samples.","code":""},{"path":"/reference/ici_kendalltau.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"information-content-informed kendall tau — ici_kendalltau","text":"","code":"ici_kendalltau(   data_matrix,   global_na = c(NA, Inf, 0),   perspective = \"global\",   scale_max = TRUE,   diag_good = TRUE,   include_only = NULL,   check_timing = FALSE,   return_matrix = TRUE )"},{"path":"/reference/ici_kendalltau.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"information-content-informed kendall tau — ici_kendalltau","text":"data_matrix samples columns, features rows global_na globally, treated NA? perspective treat missing data denominator ties, see details scale_max everything scaled compared maximum correlation? diag_good diagonal entries reflect many entries sample \"good\"? include_only run correlations include members (vector) combinations (list data.frame) check_timing try estimate run time full dataset? (default FALSE) return_matrix data.frame matrix result returned?","code":""},{"path":"/reference/ici_kendalltau.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"information-content-informed kendall tau — ici_kendalltau","text":"list cor, raw, pval, taumax","code":""},{"path":"/reference/ici_kendalltau.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"information-content-informed kendall tau — ici_kendalltau","text":"details, see ICI-Kendall-tau vignette browseVignettes(\"ICIKendallTau\") default global_na includes values data replace NA Kendall-tau calculation. default global_na = c(NA, Inf, 0). want replace something 0, example, might use global_na = c(NA, Inf, -2), values -2 replaced instead 0. check_timing = TRUE, 5 random pairwise comparisons run generate timings single core, estimates long full set take calculated. data returned data.frame, low side, provide good idea long data take. Returned list containing matrices : cor: scaled correlations raw: raw kendall-tau correlations pval: p-values taumax: theoretical maximum kendall-tau value possible Eventually, plan provide two parameters replacing values, feature_na feature specific NA values sample_na sample specific NA values.","code":""},{"path":"/reference/ici_kendalltau.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"information-content-informed kendall tau — ici_kendalltau","text":"","code":"if (FALSE) { # not run set.seed(1234) s1 = sort(rnorm(1000, mean = 100, sd = 10)) s2 = s1 + 10   matrix_1 = cbind(s1, s2)  r_1 = ici_kendalltau(matrix_1) r_1$cor  #    s1 s2 # s1  1  1 # s2  1  1 names(r_1) # \"cor\", \"raw\", \"pval\", \"taumax\", \"keep\", \"run_time\"  s3 = s1 s3[sample(100, 50)] = NA  s4 = s2 s4[sample(100, 50)] = NA  matrix_2 = cbind(s3, s4) r_2 = ici_kendalltau(matrix_2) r_2$cor #           s3        s4 # s3 1.0000000 0.9944616 # s4 0.9944616 1.0000000  # using include_only set.seed(1234) x = t(matrix(rnorm(5000), nrow = 100, ncol = 50)) colnames(x) = paste0(\"s\", seq(1, nrow(x)))  # only calculate correlations of other columns with \"s1\" include_s1 = \"s1\" s1_only = ici_kendalltau(x, include_only = include_s1)  # include s1 and s3 things both include_s1s3 = c(\"s1\", \"s3\") s1s3_only = ici_kendalltau(x, include_only = include_s1s3)  # only specify certain pairs either as a list include_pairs = list(g1 = \"s1\", g2 = c(\"s2\", \"s3\")) s1_other = ici_kendalltau(x, include_only = include_pairs)  # or a data.frame include_df = as.data.frame(list(g1 = \"s1\", g2 = c(\"s2\", \"s3\"))) s1_df = ici_kendalltau(x, include_only = include_df)  }"},{"path":"/reference/ici_kendalltau_ref.html","id":null,"dir":"Reference","previous_headings":"","what":"information-content-informed kendall tau — ici_kendalltau_ref","title":"information-content-informed kendall tau — ici_kendalltau_ref","text":"Given data-matrix, computes information-content-informed (ICI) Kendall-tau-b samples.","code":""},{"path":"/reference/ici_kendalltau_ref.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"information-content-informed kendall tau — ici_kendalltau_ref","text":"","code":"ici_kendalltau_ref(   data_matrix,   global_na = c(NA, Inf, 0),   zero_value = 0,   perspective = \"global\",   scale_max = TRUE,   diag_good = TRUE,   progress = FALSE )"},{"path":"/reference/ici_kendalltau_ref.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"information-content-informed kendall tau — ici_kendalltau_ref","text":"data_matrix samples columns, features rows global_na values treated missing (NA)? zero_value actual zero value? perspective treat missing data denominator ties, see details scale_max everything scaled compared maximum correlation? diag_good diagonal entries reflect many entries sample \"good\"? progress progress displayed.","code":""},{"path":"/reference/ici_kendalltau_ref.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"information-content-informed kendall tau — ici_kendalltau_ref","text":"numeric","code":""},{"path":"/reference/ici_kendalltau_ref.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"information-content-informed kendall tau — ici_kendalltau_ref","text":"details, see ICI-Kendall-tau vignette: vignette(\"ici-kendalltau\", package = \"ICIKendallTau\")","code":""},{"path":"/reference/ici_kt.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates ici-kendall-tau — ici_kt","title":"Calculates ici-kendall-tau — ici_kt","text":"Calculates ici-kendall-tau","code":""},{"path":"/reference/ici_kt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates ici-kendall-tau — ici_kt","text":"","code":"ici_kt(   x,   y,   perspective = \"local\",   alternative = \"two.sided\",   continuity = FALSE,   output = \"simple\" )"},{"path":"/reference/ici_kt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates ici-kendall-tau — ici_kt","text":"x numeric vector y numeric vector perspective consider \"local\" \"global\" perspective? alternative alternative p-value test? continuity logical: true, continuity correction used output used control reporting values debugging","code":""},{"path":"/reference/ici_kt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates ici-kendall-tau — ici_kt","text":"kendall tau correlation, p-value, max-correlation","code":""},{"path":"/reference/ici_kt.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates ici-kendall-tau — ici_kt","text":"Calculates information-content-informed Kendall-tau correlation measure. correlation based concordant discordant ranked pairs, like Kendall-tau, also includes missing values (NA). Missing values assumed primarily due lack detection due instrumental sensitivity, therefore encode information. details see ICI-Kendall-tau vignette: browseVignettes(\"ICIKendallTau\")","code":""},{"path":"/reference/ici_kt.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates ici-kendall-tau — ici_kt","text":"","code":"x = sort(rnorm(100)) y = x + 1 y2 = y y2[1:10] = NA ici_kt(x, y) #>          tau       pvalue      tau_max  #> 1.000000e+00 3.480281e-49 1.000000e+00  ici_kt(x, y2, \"global\") #>          tau       pvalue      tau_max  #> 9.954442e-01 2.228308e-48 9.954442e-01  ici_kt(x, y2) #>          tau       pvalue      tau_max  #> 9.954442e-01 2.228308e-48 9.954442e-01"},{"path":"/reference/kt_fast.html","id":null,"dir":"Reference","previous_headings":"","what":"fast kendall tau — kt_fast","title":"fast kendall tau — kt_fast","text":"Uses underlying c++ implementation ici_kt provide fast version Kendall-tau correlation.","code":""},{"path":"/reference/kt_fast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"fast kendall tau — kt_fast","text":"","code":"kt_fast(x, y = NULL, use = \"everything\", return_matrix = TRUE)"},{"path":"/reference/kt_fast.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"fast kendall tau — kt_fast","text":"x numeric vector, matrix, data frame. y NULL (default) vector. use optional character string giving method computing correlations presence missing values. must (abbreviation ) one strings \"everything\", \".obs\", \"complete.obs\", \"pairwise.complete.obs\". return_matrix matrices values returned, long data.frame","code":""},{"path":"/reference/kt_fast.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"fast kendall tau — kt_fast","text":"named vector list matrices.","code":""},{"path":"/reference/kt_fast.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"fast kendall tau — kt_fast","text":"Although interface mostly identical built-stats::cor method, differences. providing x y, assumed single vectors. NA values present, function error, either remove return NA, depending option. \"na..complete\" valid option use. named vector named list matrices returned, tau pvalue values.","code":""},{"path":"/reference/log_memory.html","id":null,"dir":"Reference","previous_headings":"","what":"log memory usage — log_memory","title":"log memory usage — log_memory","text":"Logs amount memory used log file available, generating warnings amount RAM hits zero.","code":""},{"path":"/reference/log_memory.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"log memory usage — log_memory","text":"","code":"log_memory()"},{"path":"/reference/log_message.html","id":null,"dir":"Reference","previous_headings":"","what":"log messages — log_message","title":"log messages — log_message","text":"log_appender available, logs given message info level.","code":""},{"path":"/reference/log_message.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"log messages — log_message","text":"","code":"log_message(message_string)"},{"path":"/reference/log_message.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"log messages — log_message","text":"message_string string put message","code":""},{"path":"/reference/long_df_2_cor_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"convert data.frame to matrix — long_df_2_cor_matrix","title":"convert data.frame to matrix — long_df_2_cor_matrix","text":"Given long data.frame, converts possibly square correlation matrix","code":""},{"path":"/reference/long_df_2_cor_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"convert data.frame to matrix — long_df_2_cor_matrix","text":"","code":"long_df_2_cor_matrix(long_df, is_square = TRUE)"},{"path":"/reference/long_df_2_cor_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"convert data.frame to matrix — long_df_2_cor_matrix","text":"long_df long data.frame is_square square matrix?","code":""},{"path":"/reference/long_df_2_cor_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"convert data.frame to matrix — long_df_2_cor_matrix","text":"matrix","code":""},{"path":"/reference/pairwise_completeness.html","id":null,"dir":"Reference","previous_headings":"","what":"pairwise completeness — pairwise_completeness","title":"pairwise completeness — pairwise_completeness","text":"Calculates completeness two samples using \"\", entry missing either X \"\" Y.","code":""},{"path":"/reference/pairwise_completeness.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"pairwise completeness — pairwise_completeness","text":"","code":"pairwise_completeness(   data_matrix,   global_na = c(NA, Inf, 0),   include_only = NULL,   return_matrix = TRUE )"},{"path":"/reference/pairwise_completeness.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"pairwise completeness — pairwise_completeness","text":"data_matrix samples columns, features rows global_na globally, treated NA? include_only certain comparisons ? return_matrix matrix data.frame returned?","code":""},{"path":"/reference/pairwise_completeness.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"pairwise completeness — pairwise_completeness","text":"matrix degree completeness","code":""},{"path":"/reference/show_progress.html","id":null,"dir":"Reference","previous_headings":"","what":"turn progress on off — show_progress","title":"turn progress on off — show_progress","text":"Allow user turn progress messages console . Default provide messages console.","code":""},{"path":"/reference/show_progress.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"turn progress on off — show_progress","text":"","code":"show_progress(progress = TRUE)"},{"path":"/reference/show_progress.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"turn progress on off — show_progress","text":"progress logical ","code":""},{"path":"/news/index.html","id":"icikendalltau-100","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 1.0.0","title":"ICIKendallTau 1.0.0","text":"Calculates correlation columns matrix, rows.","code":""},{"path":"/news/index.html","id":"icikendalltau-0320","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.3.20","title":"ICIKendallTau 0.3.20","text":"kt_fast now uses data.frame format output ici_kendalltau, returns matrix default. data.frame useful large amounts comparisons run.","code":""},{"path":"/news/index.html","id":"icikendalltau-030","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.3.0","title":"ICIKendallTau 0.3.0","text":"Handling parallel execution differently avoid really large matrix issues core. Introduces return_matrix parameter ici_kendalltau allows return results form data.frame instead lists matrices.","code":""},{"path":"/news/index.html","id":"icikendalltau-0210","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.2.10","title":"ICIKendallTau 0.2.10","text":"Provide kt_fast function handles missing NA values similarly stats::cor function, uses ici_kt fast function underneath.","code":""},{"path":"/news/index.html","id":"icikendalltau-028","dir":"Changelog","previous_headings":"","what":"ICIKendalltau 0.2.8","title":"ICIKendalltau 0.2.8","text":"Made error outputs length default output containing NA. Check case one variables ici_kt identical arguments, warns user returns NA.","code":""},{"path":"/news/index.html","id":"icikendalltau-021","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.2.1","title":"ICIKendallTau 0.2.1","text":"Added new argument include_only ici_kendalltau allows user define pairwise correlations actually .","code":""},{"path":"/news/index.html","id":"icikendalltau-0117","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.1.17","title":"ICIKendallTau 0.1.17","text":"switched theme. updated installation instructions use r-universe.","code":""},{"path":"/news/index.html","id":"icikendalltau-0116","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.1.16","title":"ICIKendallTau 0.1.16","text":"updating documentation examples","code":""},{"path":"/news/index.html","id":"icikendalltau-014","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.1.4","title":"ICIKendallTau 0.1.4","text":"Switched pairwise_completeness also use global_na parameter. Oh yes, function pairwise_completeness enable scaling completeness two samples.","code":""},{"path":"/news/index.html","id":"icikendalltau-012","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.1.2","title":"ICIKendallTau 0.1.2","text":"Updated API use single variable, global_na defines values set NA correlation calculation. big API change, bumped version 0.1.","code":""},{"path":"/news/index.html","id":"icikendalltau-006","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.0.6","title":"ICIKendallTau 0.0.6","text":"Fixing bug 55,000 elements vector, match overflows 32 bit 64 bit, results make sense.","code":""},{"path":"/news/index.html","id":"icikendalltau-005","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.0.5","title":"ICIKendallTau 0.0.5","text":"Fixed bug instead returning two element vector, returned zero length value. probably happened one entries contained NA values, tried pass “vectors” less two entries.","code":""},{"path":"/news/index.html","id":"icikendalltau-004","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.0.4","title":"ICIKendallTau 0.0.4","text":"Fixing things came R CMD check documentation. good now (hope).","code":""},{"path":"/news/index.html","id":"icikendalltau-003","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.0.3","title":"ICIKendallTau 0.0.3","text":"Added tests! Removed bunch code wasn’t necessary using incorrect formula’s, correct version ici_kt_pairs function reference purposes.","code":""},{"path":"/news/index.html","id":"icikendalltau-002","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.0.2","title":"ICIKendallTau 0.0.2","text":"Fixed issue warning issued {furrr} installed.","code":""},{"path":"/news/index.html","id":"icikendalltau-001","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.0.1","title":"ICIKendallTau 0.0.1","text":"First release. ’s tested used rather thoroughly , ’d say ’s still rather alpha. Even though use time . Added NEWS.md file track changes package.","code":""}]
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Translations available https:// www.contributor-covenant.org/translations.","code":""},{"path":"/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2021 Robert M Flight & Hunter NB Moseley Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"/articles/ici-kendalltau.html","id":"problem","dir":"Articles","previous_headings":"","what":"Problem","title":"Information-Content-Informed Kendall Tau Correlation","text":"handle missing data (.e. NA’s) calculating correlation two variables. However, whether observation made semi-quantitative information many analytical measurements sensitivity limits. .e. many cases, missing observations “missing--random”, “missing---random” due falling detection limit. cases, NA informative.","code":""},{"path":"/articles/ici-kendalltau.html","id":"approach","dir":"Articles","previous_headings":"","what":"Approach","title":"Information-Content-Informed Kendall Tau Correlation","text":"Kendall Tau Correlation coefficient calculates correlation based number concordant discordant pairs: \\(\\tau = \\frac{ | pairs_{concordant} | - | pairs_{discordant} |}{\\binom{n}{2}}\\) pair two x-y data points. \\(x_i > x_j\\) \\(y_i > y_j\\) \\(x_i < x_j\\) \\(y_i < y_j\\) \\(x_i > x_j\\) \\(y_i < y_j\\) \\(x_i < x_j\\) \\(y_i > y_j\\) definitions can expanded handle missing observations: \\(x_i > x_j\\) \\(y_i > y_j\\) \\(x_i < x_j\\) \\(y_i < y_j\\) \\(x_i > x_j\\) \\(y_i \\& !y_j\\) \\(x_i < x_j\\) \\(!y_i \\& y_j\\) \\(x_i \\& !x_j\\) \\(y_i > y_j\\) \\(!x_i \\& x_j\\) \\(y_i < y_j\\) \\(x_i \\& !x_j\\) \\(y_i \\& !y_j\\) (used local perspective version) \\(x_i \\& x_j\\) \\(!y_i \\& y_j\\) (used local perspective version) \\(x_i > x_j\\) \\(y_i < y_j\\) \\(x_i < x_j\\) \\(y_i > y_j\\) \\(x_i > x_j\\) \\(!y_i \\& y_j\\) \\(x_i < x_j\\) \\(y_i \\& !y_j\\) \\(x_i \\& !x_j\\) \\(y_i < y_j\\) \\(!x_i \\& x_j\\) \\(y_i > y_j\\) \\(x_i \\& !x_j\\) \\(!y_i \\& y_j\\) (used local perspective version) \\(!x_i \\& x_j\\) \\(y_i \\& !y_j\\) (used local perspective version) Also data points missing x y values naturally reduce strength correlation value, since can neither concordant discordant another (NA, NA) pair, impact denominator. equivalent removing last two concordant discordant pair tests.","code":""},{"path":"/articles/ici-kendalltau.html","id":"handling-tied-values","dir":"Articles","previous_headings":"","what":"Handling Tied Values","title":"Information-Content-Informed Kendall Tau Correlation","text":"base Kendall tau correlation must adjusted handle tied values, ie. tau-b version equation. \\[\\tau = \\frac{ | pairs_{concordant}  | -  | pairs_{discordant}  |}{\\sqrt{ ( n_0 - n_{xtie}  )  ( n_0 - n_{ytie}  )}} \\] : \\(n_0 = \\frac{n \\left ( n - 1 \\right )}{2}\\) \\(n_{xtie} = \\sum_{}^{} \\frac{t_{xi} \\left ( t_{xi} - 1 \\right )}{2}\\) \\(n_{ytie} = \\sum_{}^{} \\frac{t_{yi} \\left ( t_{yi} - 1 \\right )}{2}\\) \\(t_{xi}\\) - size ith group tied x values. \\(t_{yi}\\) - size ith group tied y values. local perspective, number NAs x y can treated group tied values calculation \\(n_{xtie}\\) \\(n_{ytie}\\), respectively.","code":""},{"path":"/articles/ici-kendalltau.html","id":"scaling-by-the-correlation-with-the-highest-information-content","dir":"Articles","previous_headings":"","what":"Scaling by the correlation with the highest information content","title":"Information-Content-Informed Kendall Tau Correlation","text":"generating correlation matrix (heatmap) large analytical datasets, number observations common can become quite low two variables. becomes advantageous scale pair variables highest information content. One objective scaling factor highest possible absolute correlation maximum information content observed across dataset, dividing maximum possible absolute correlation scale whole dataset appropriately. \\[maxcorr = \\frac{\\binom{n-m}{2} + n * m}{\\binom{n-m}{2} + n * m + \\binom{m}{2}}\\] : Choose two variables least number missing values across dataset. n length variables. formula based perfect correlation given number (NA,NA) pairs added.","code":""},{"path":"/articles/ici-kendalltau.html","id":"functions","dir":"Articles","previous_headings":"","what":"Functions","title":"Information-Content-Informed Kendall Tau Correlation","text":"functions implement include: option perspective control NA values influence ties. comparing multiple samples, likely want use perspective = \"global\". Rows features, columns samples. library(furrr) plan(multiprocess) Otherwise use single core.","code":""},{"path":"/articles/ici-kendalltau.html","id":"implementation","dir":"Articles","previous_headings":"","what":"Implementation","title":"Information-Content-Informed Kendall Tau Correlation","text":"turns , think really hard, truly necessary replace missing values vector value smaller minimum value one. local version, first remove common missing values vector. C++ implementation explicitly can speed, instead wrapping {stats::cor} function. also use double merge-sort algorithm, translating {scipy:: ::stats::kendalltau} function C++ using {Rcpp}.","code":""},{"path":"/articles/ici-kendalltau.html","id":"speed","dir":"Articles","previous_headings":"","what":"Speed","title":"Information-Content-Informed Kendall Tau Correlation","text":"","code":"x = rnorm(1000) y = rnorm(1000)  library(microbenchmark)  microbenchmark(   cor(x, y, method = \"kendall\"),   ici_kt(x, y, \"global\"),   times = 5 ) #> Unit: microseconds #>                           expr       min        lq       mean    median #>  cor(x, y, method = \"kendall\") 12781.169 13088.783 13795.1100 13290.629 #>         ici_kt(x, y, \"global\")   261.498   304.518   335.7076   305.834 #>         uq       max neval #>  14382.628 15432.341     5 #>    327.014   479.674     5 all.equal(ici_kt(x, y, \"global\")[[1]], cor(x, y, method = \"kendall\")) #> [1] TRUE"},{"path":"/articles/ici-kendalltau.html","id":"running-many","dir":"Articles","previous_headings":"","what":"Running Many","title":"Information-Content-Informed Kendall Tau Correlation","text":"Just like R’s cor function, can also calculate correlations many variables. Let’s make fake data try .","code":"set.seed(1234)  s1 = sort(rnorm(1000, mean = 100, sd = 10)) s2 = s1 + 10 s2[sample(length(s1), 100)] = s1[1:100] s3 = s1 s3[c(1:10, sample(length(s1), 5))] = NA  matrix_1 = cbind(s1, s2, s3)  r_1 = ici_kendalltau(matrix_1) r_1$cor #>           s1        s2        s3 #> s1 1.0000000 0.8049209 0.9907488 #> s2 0.8049209 1.0000000 0.7956652 #> s3 0.9907488 0.7956652 0.9850000"},{"path":"/articles/ici-kendalltau.html","id":"parallelism","dir":"Articles","previous_headings":"","what":"Parallelism","title":"Information-Content-Informed Kendall Tau Correlation","text":"{future} {furrr} packages installed, also possible split set matrix comparisons across compute resources multiprocessing engine registered {future}.","code":"library(furrr) future::plan(multicore, workers = 4) r_2 = ici_kendalltau(matrix_1)"},{"path":"/articles/ici-kendalltau.html","id":"many-many-comparisons","dir":"Articles","previous_headings":"","what":"Many Many Comparisons","title":"Information-Content-Informed Kendall Tau Correlation","text":"case hundreds thousands comparisons done, result matrices can become , large, require lots memory storage. also inefficient, lower upper triangular components stored. alternative storage format data.frame, single row comparison performed. actually results stored internally, converted matrix form requested (default).s keep data.frame output, add argument return_matrix=FALSE call ici_kendalltau.","code":"r_3 = ici_kendalltau(matrix_1, return_matrix = FALSE) r_3$cor #>   s1 s2 core       raw pvalue    taumax       cor #> 1 s1 s2    1 0.8049209      0 1.0000000 0.8049209 #> 2 s1 s3    1 0.9907488      0 0.9998949 0.9907488 #> 3 s2 s3    1 0.7956652      0 0.9998949 0.7956652 #> 4 s1 s1    0 1.0000000      0 1.0000000 1.0000000 #> 5 s2 s2    0 1.0000000      0 1.0000000 1.0000000 #> 6 s3 s3    0 0.9850000      0 1.0000000 0.9850000"},{"path":"/articles/ici-kendalltau.html","id":"logging","dir":"Articles","previous_headings":"","what":"Logging","title":"Information-Content-Informed Kendall Tau Correlation","text":"possible log steps done much memory used (Linux least) correlations calculated. can useful running large sets correlations making sure much memory isn’t used, example. enable logging, {logger} package must installed. log_file supplied, one created current date time. default, ici_kendalltau also shows progress messages, want turn , can :","code":"enable_logging() enable_logging(\"/tmp/my_ici_run.log\") show_progress(FALSE)"},{"path":"/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Robert M Flight. Author, maintainer. Hunter NB Moseley. Author.","code":""},{"path":"/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Flight RM, Moseley HN (2024). ICIKendallTau: Calculates information-content-informed Kendall-tau. R package version 1.0.2, https://moseleybioinformaticslab.github.io/ICIKendallTauhttps://github.com/moseleybioinformaticslab/ICIKendallTau.","code":"@Manual{,   title = {ICIKendallTau: Calculates information-content-informed Kendall-tau},   author = {Robert M Flight and Hunter NB Moseley},   year = {2024},   note = {R package version 1.0.2},   url = {https://moseleybioinformaticslab.github.io/ICIKendallTau https://github.com/moseleybioinformaticslab/ICIKendallTau}, }"},{"path":"/index.html","id":"icikendalltau","dir":"","previous_headings":"","what":"Calculates information-content-informed Kendall-tau","title":"Calculates information-content-informed Kendall-tau","text":"can see pkgdown site .","code":""},{"path":"/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Calculates information-content-informed Kendall-tau","text":"can install current version ICIKendallTau via GitHub: can also install Windows Mac binaries using r-universe:","code":"remotes::install_github(\"MoseleyBioinformaticsLab/ICIKendallTau\") options(repos = c(     moseleybioinformaticslab = 'https://moseleybioinformaticslab.r-universe.dev',     CRAN = \"https://cloud.r-project.org\")) install.packages(\"ICIKendallTau\")"},{"path":"/index.html","id":"problem","dir":"","previous_headings":"","what":"Problem","title":"Calculates information-content-informed Kendall-tau","text":"handle missing data (.e. NA’s) calculating correlation two variables. However, whether observation present missing semi-quantitative information many analytical measurements sensitivity limits. .e. many cases, missing observations “missing--random”, “missing---random” due falling detection limit. cases, NA informative. Therefore, analytical measurements (gene expression, proteomics, metabolomics), missing measurements included, contribute correlation. want read solve problem, see package vignette.","code":""},{"path":"/index.html","id":"package-functions","dir":"","previous_headings":"","what":"Package Functions","title":"Calculates information-content-informed Kendall-tau","text":"functions implement include: option perspective control NA values influence ties. comparing samples, likely want use perspective = \"global\". Rows features, columns samples. library(furrr) plan(multiprocess) Otherwise use single core.","code":""},{"path":"/index.html","id":"examples","dir":"","previous_headings":"","what":"Examples","title":"Calculates information-content-informed Kendall-tau","text":"common case large matrix independent samples (columns) measured features samples (.e. gene expression). make artificial data show correlation changes introduce missingness. Now introduce missing values low end one. just simplest thing introduce NA values bottom set.","code":"set.seed(1234) library(ICIKendallTau)  s1 = sort(rnorm(1000, mean = 100, sd = 10)) s2 = s1 + 10   matrix_1 = cbind(s1, s2)  r_1 = ici_kendalltau(matrix_1) r_1$cor #>    s1 s2 #> s1  1  1 #> s2  1  1 s3 = s1 s3[sample(100, 50)] = NA  s4 = s2 s4[sample(100, 50)] = NA  matrix_2 = cbind(s3, s4) r_2 = ici_kendalltau(matrix_2) r_2$cor #>           s3        s4 #> s3 1.0000000 0.9944616 #> s4 0.9944616 1.0000000"},{"path":"/index.html","id":"is-it-fast","dir":"","previous_headings":"","what":"Is It Fast?","title":"Calculates information-content-informed Kendall-tau","text":"C++ code implementation (thanks {Rcpp}!) based SciPy implementation, uses two merge sorts ranks vector, looks differences . fastest method know , complexity O(nlogn). naive way computing , explicitly examines pairs, complexity n^2. implementation compared {pcaPP::cov.fk} function, use {Rcpp} inefficient copying vectors makes 3X slower one. honestly isn’t bad. case 40,000 features, average time modern CPU 14 milliseconds. course, want use calculate Kendall-tau-b without incorporating missingness, can just fine well. also provide kt_fast function, want something treats NA values similarly stats::cor.","code":"library(microbenchmark) x = rnorm(1000) y = rnorm(1000)  x2 = rnorm(40000) y2 = rnorm(40000)  library(microbenchmark)  microbenchmark(   cor(x, y, method = \"kendall\"),   ici_kt(x, y, \"global\"),   ici_kt(x2, y2, \"global\"),   times = 5 ) #> Unit: microseconds #>                           expr       min        lq       mean    median        uq       max #>  cor(x, y, method = \"kendall\") 11506.697 11670.094 12169.6628 12006.418 12482.883 13182.222 #>         ici_kt(x, y, \"global\")   243.866   250.125   294.6542   275.104   320.058   384.118 #>       ici_kt(x2, y2, \"global\") 13467.011 13739.312 14658.5050 14945.446 14987.140 16153.616 #>  neval #>      5 #>      5 #>      5 k_tau = ici_kt(x, y, \"global\") all.equal(k_tau[[1]] ,cor(x, y, method = \"kendall\")) #> [1] TRUE k_tau_fast = kt_fast(x, y) k_tau_fast #>          tau       pvalue  #> -0.003411411  0.871672260"},{"path":"/index.html","id":"parallelism","dir":"","previous_headings":"","what":"Parallelism","title":"Calculates information-content-informed Kendall-tau","text":"{future} {furrr} packages installed, also possible split set matrix comparisons across compute resources multiprocessing engine registered {future}.","code":"library(furrr) future::plan(multicore, workers = 4) r_3 = ici_kendalltau(matrix_2)"},{"path":"/index.html","id":"many-many-comparisons","dir":"","previous_headings":"","what":"Many Many Comparisons","title":"Calculates information-content-informed Kendall-tau","text":"case hundreds thousands comparisons done, result matrices can become , large, require lots memory storage. also inefficient, lower upper triangular components stored. alternative storage format data.frame, single row comparison performed. actually results stored internally, converted matrix form requested (default).s keep data.frame output, add argument return_matrix=FALSE call ici_kendalltau.","code":"r_4 = ici_kendalltau(matrix_2, return_matrix = FALSE) r_4 #> $cor #>   s1 s2 core       raw pvalue   taumax       cor #> 1 s3 s4    1 0.9924359      0 0.997963 0.9944616 #> 2 s3 s3    0 1.0000000      0 1.000000 1.0000000 #> 3 s4 s4    0 1.0000000      0 1.000000 1.0000000 #>  #> $run_time #> [1] 0.01606894"},{"path":"/index.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Calculates information-content-informed Kendall-tau","text":"Please note ICIKendallTau project released Contributor Code Conduct. contributing project, agree abide terms.","code":""},{"path":"/reference/cor_matrix_2_long_df.html","id":null,"dir":"Reference","previous_headings":"","what":"convert matrix to data.frame — cor_matrix_2_long_df","title":"convert matrix to data.frame — cor_matrix_2_long_df","text":"Given square correlation matrix, converts long data.frame, three columns.","code":""},{"path":"/reference/cor_matrix_2_long_df.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"convert matrix to data.frame — cor_matrix_2_long_df","text":"","code":"cor_matrix_2_long_df(in_matrix)"},{"path":"/reference/cor_matrix_2_long_df.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"convert matrix to data.frame — cor_matrix_2_long_df","text":"in_matrix correlation matrix","code":""},{"path":"/reference/cor_matrix_2_long_df.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"convert matrix to data.frame — cor_matrix_2_long_df","text":"data.frame","code":""},{"path":"/reference/cor_matrix_2_long_df.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"convert matrix to data.frame — cor_matrix_2_long_df","text":"data.frame contains three columns: s1: first entry comparison s2: second entry comparison cor: correlation value","code":""},{"path":"/reference/disable_logging.html","id":null,"dir":"Reference","previous_headings":"","what":"turn logging off — disable_logging","title":"turn logging off — disable_logging","text":"may good reasons turn logging turned . basically tells package logger available.","code":""},{"path":"/reference/disable_logging.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"turn logging off — disable_logging","text":"","code":"disable_logging()"},{"path":"/reference/enable_logging.html","id":null,"dir":"Reference","previous_headings":"","what":"turn logging on — enable_logging","title":"turn logging on — enable_logging","text":"Choose enable logging, specific file desired.","code":""},{"path":"/reference/enable_logging.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"turn logging on — enable_logging","text":"","code":"enable_logging(log_file = NULL, memory = FALSE)"},{"path":"/reference/enable_logging.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"turn logging on — enable_logging","text":"log_file file log memory provide memory logging ? available Linux MacOS","code":""},{"path":"/reference/enable_logging.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"turn logging on — enable_logging","text":"Uses logger package hood, suggested dependencies. logging enabled nice see things starting stopping, exactly done, without needing write messages console. especially useful getting errors, really see , can add \"memory\" logging see running memory. Default log file pattern: YYYY.MM.DD.HH.MM.SS_ICIKendallTau_run.log","code":""},{"path":"/reference/ici_kendalltau.html","id":null,"dir":"Reference","previous_headings":"","what":"information-content-informed kendall tau — ici_kendalltau","title":"information-content-informed kendall tau — ici_kendalltau","text":"Given data-matrix, computes information-theoretic Kendall-tau-b samples.","code":""},{"path":"/reference/ici_kendalltau.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"information-content-informed kendall tau — ici_kendalltau","text":"","code":"ici_kendalltau(   data_matrix,   global_na = c(NA, Inf, 0),   perspective = \"global\",   scale_max = TRUE,   diag_good = TRUE,   include_only = NULL,   check_timing = FALSE,   return_matrix = TRUE )"},{"path":"/reference/ici_kendalltau.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"information-content-informed kendall tau — ici_kendalltau","text":"data_matrix samples columns, features rows global_na globally, treated NA? perspective treat missing data denominator ties, see details scale_max everything scaled compared maximum correlation? diag_good diagonal entries reflect many entries sample \"good\"? include_only run correlations include members (vector) combinations (list data.frame) check_timing try estimate run time full dataset? (default FALSE) return_matrix data.frame matrix result returned?","code":""},{"path":"/reference/ici_kendalltau.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"information-content-informed kendall tau — ici_kendalltau","text":"list cor, raw, pval, taumax","code":""},{"path":"/reference/ici_kendalltau.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"information-content-informed kendall tau — ici_kendalltau","text":"details, see ICI-Kendall-tau vignette browseVignettes(\"ICIKendallTau\") default global_na includes values data replace NA Kendall-tau calculation. default global_na = c(NA, Inf, 0). want replace something 0, example, might use global_na = c(NA, Inf, -2), values -2 replaced instead 0. check_timing = TRUE, 5 random pairwise comparisons run generate timings single core, estimates long full set take calculated. data returned data.frame, low side, provide good idea long data take. Returned list containing matrices : cor: scaled correlations raw: raw kendall-tau correlations pval: p-values taumax: theoretical maximum kendall-tau value possible Eventually, plan provide two parameters replacing values, feature_na feature specific NA values sample_na sample specific NA values.","code":""},{"path":"/reference/ici_kendalltau.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"information-content-informed kendall tau — ici_kendalltau","text":"","code":"if (FALSE) { # not run set.seed(1234) s1 = sort(rnorm(1000, mean = 100, sd = 10)) s2 = s1 + 10   matrix_1 = cbind(s1, s2)  r_1 = ici_kendalltau(matrix_1) r_1$cor  #    s1 s2 # s1  1  1 # s2  1  1 names(r_1) # \"cor\", \"raw\", \"pval\", \"taumax\", \"keep\", \"run_time\"  s3 = s1 s3[sample(100, 50)] = NA  s4 = s2 s4[sample(100, 50)] = NA  matrix_2 = cbind(s3, s4) r_2 = ici_kendalltau(matrix_2) r_2$cor #           s3        s4 # s3 1.0000000 0.9944616 # s4 0.9944616 1.0000000  # using include_only set.seed(1234) x = t(matrix(rnorm(5000), nrow = 100, ncol = 50)) colnames(x) = paste0(\"s\", seq(1, nrow(x)))  # only calculate correlations of other columns with \"s1\" include_s1 = \"s1\" s1_only = ici_kendalltau(x, include_only = include_s1)  # include s1 and s3 things both include_s1s3 = c(\"s1\", \"s3\") s1s3_only = ici_kendalltau(x, include_only = include_s1s3)  # only specify certain pairs either as a list include_pairs = list(g1 = \"s1\", g2 = c(\"s2\", \"s3\")) s1_other = ici_kendalltau(x, include_only = include_pairs)  # or a data.frame include_df = as.data.frame(list(g1 = \"s1\", g2 = c(\"s2\", \"s3\"))) s1_df = ici_kendalltau(x, include_only = include_df)  }"},{"path":"/reference/ici_kendalltau_ref.html","id":null,"dir":"Reference","previous_headings":"","what":"information-content-informed kendall tau — ici_kendalltau_ref","title":"information-content-informed kendall tau — ici_kendalltau_ref","text":"Given data-matrix, computes information-content-informed (ICI) Kendall-tau-b samples.","code":""},{"path":"/reference/ici_kendalltau_ref.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"information-content-informed kendall tau — ici_kendalltau_ref","text":"","code":"ici_kendalltau_ref(   data_matrix,   global_na = c(NA, Inf, 0),   zero_value = 0,   perspective = \"global\",   scale_max = TRUE,   diag_good = TRUE,   progress = FALSE )"},{"path":"/reference/ici_kendalltau_ref.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"information-content-informed kendall tau — ici_kendalltau_ref","text":"data_matrix samples columns, features rows global_na values treated missing (NA)? zero_value actual zero value? perspective treat missing data denominator ties, see details scale_max everything scaled compared maximum correlation? diag_good diagonal entries reflect many entries sample \"good\"? progress progress displayed.","code":""},{"path":"/reference/ici_kendalltau_ref.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"information-content-informed kendall tau — ici_kendalltau_ref","text":"numeric","code":""},{"path":"/reference/ici_kendalltau_ref.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"information-content-informed kendall tau — ici_kendalltau_ref","text":"details, see ICI-Kendall-tau vignette: vignette(\"ici-kendalltau\", package = \"ICIKendallTau\")","code":""},{"path":"/reference/ici_kt.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates ici-kendall-tau — ici_kt","title":"Calculates ici-kendall-tau — ici_kt","text":"Calculates ici-kendall-tau","code":""},{"path":"/reference/ici_kt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates ici-kendall-tau — ici_kt","text":"","code":"ici_kt(   x,   y,   perspective = \"local\",   alternative = \"two.sided\",   continuity = FALSE,   output = \"simple\" )"},{"path":"/reference/ici_kt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates ici-kendall-tau — ici_kt","text":"x numeric vector y numeric vector perspective consider \"local\" \"global\" perspective? alternative alternative p-value test? continuity logical: true, continuity correction used output used control reporting values debugging","code":""},{"path":"/reference/ici_kt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates ici-kendall-tau — ici_kt","text":"kendall tau correlation, p-value, max-correlation","code":""},{"path":"/reference/ici_kt.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates ici-kendall-tau — ici_kt","text":"Calculates information-content-informed Kendall-tau correlation measure. correlation based concordant discordant ranked pairs, like Kendall-tau, also includes missing values (NA). Missing values assumed primarily due lack detection due instrumental sensitivity, therefore encode information. details see ICI-Kendall-tau vignette: browseVignettes(\"ICIKendallTau\")","code":""},{"path":"/reference/ici_kt.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates ici-kendall-tau — ici_kt","text":"","code":"x = sort(rnorm(100)) y = x + 1 y2 = y y2[1:10] = NA ici_kt(x, y) #>          tau       pvalue      tau_max  #> 1.000000e+00 3.480281e-49 1.000000e+00  ici_kt(x, y2, \"global\") #>          tau       pvalue      tau_max  #> 9.954442e-01 2.228308e-48 9.954442e-01  ici_kt(x, y2) #>          tau       pvalue      tau_max  #> 9.954442e-01 2.228308e-48 9.954442e-01"},{"path":"/reference/kt_fast.html","id":null,"dir":"Reference","previous_headings":"","what":"fast kendall tau — kt_fast","title":"fast kendall tau — kt_fast","text":"Uses underlying c++ implementation ici_kt provide fast version Kendall-tau correlation.","code":""},{"path":"/reference/kt_fast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"fast kendall tau — kt_fast","text":"","code":"kt_fast(x, y = NULL, use = \"everything\", return_matrix = TRUE)"},{"path":"/reference/kt_fast.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"fast kendall tau — kt_fast","text":"x numeric vector, matrix, data frame. y NULL (default) vector. use optional character string giving method computing correlations presence missing values. must (abbreviation ) one strings \"everything\", \".obs\", \"complete.obs\", \"pairwise.complete.obs\". return_matrix matrices values returned, long data.frame","code":""},{"path":"/reference/kt_fast.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"fast kendall tau — kt_fast","text":"named vector list matrices.","code":""},{"path":"/reference/kt_fast.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"fast kendall tau — kt_fast","text":"Although interface mostly identical built-stats::cor method, differences. providing x y, assumed single vectors. NA values present, function error, either remove return NA, depending option. \"na..complete\" valid option use. named vector named list matrices returned, tau pvalue values.","code":""},{"path":"/reference/log_memory.html","id":null,"dir":"Reference","previous_headings":"","what":"log memory usage — log_memory","title":"log memory usage — log_memory","text":"Logs amount memory used log file available, generating warnings amount RAM hits zero.","code":""},{"path":"/reference/log_memory.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"log memory usage — log_memory","text":"","code":"log_memory()"},{"path":"/reference/log_message.html","id":null,"dir":"Reference","previous_headings":"","what":"log messages — log_message","title":"log messages — log_message","text":"log_appender available, logs given message info level.","code":""},{"path":"/reference/log_message.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"log messages — log_message","text":"","code":"log_message(message_string)"},{"path":"/reference/log_message.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"log messages — log_message","text":"message_string string put message","code":""},{"path":"/reference/long_df_2_cor_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"convert data.frame to matrix — long_df_2_cor_matrix","title":"convert data.frame to matrix — long_df_2_cor_matrix","text":"Given long data.frame, converts possibly square correlation matrix","code":""},{"path":"/reference/long_df_2_cor_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"convert data.frame to matrix — long_df_2_cor_matrix","text":"","code":"long_df_2_cor_matrix(long_df, is_square = TRUE)"},{"path":"/reference/long_df_2_cor_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"convert data.frame to matrix — long_df_2_cor_matrix","text":"long_df long data.frame is_square square matrix?","code":""},{"path":"/reference/long_df_2_cor_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"convert data.frame to matrix — long_df_2_cor_matrix","text":"matrix","code":""},{"path":"/reference/pairwise_completeness.html","id":null,"dir":"Reference","previous_headings":"","what":"pairwise completeness — pairwise_completeness","title":"pairwise completeness — pairwise_completeness","text":"Calculates completeness two samples using \"\", entry missing either X \"\" Y.","code":""},{"path":"/reference/pairwise_completeness.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"pairwise completeness — pairwise_completeness","text":"","code":"pairwise_completeness(   data_matrix,   global_na = c(NA, Inf, 0),   include_only = NULL,   return_matrix = TRUE )"},{"path":"/reference/pairwise_completeness.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"pairwise completeness — pairwise_completeness","text":"data_matrix samples columns, features rows global_na globally, treated NA? include_only certain comparisons ? return_matrix matrix data.frame returned?","code":""},{"path":"/reference/pairwise_completeness.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"pairwise completeness — pairwise_completeness","text":"matrix degree completeness","code":""},{"path":"/reference/show_progress.html","id":null,"dir":"Reference","previous_headings":"","what":"turn progress on off — show_progress","title":"turn progress on off — show_progress","text":"Allow user turn progress messages console . Default provide messages console.","code":""},{"path":"/reference/show_progress.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"turn progress on off — show_progress","text":"","code":"show_progress(progress = TRUE)"},{"path":"/reference/show_progress.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"turn progress on off — show_progress","text":"progress logical ","code":""},{"path":"/news/index.html","id":"icikendalltau-100","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 1.0.0","title":"ICIKendallTau 1.0.0","text":"Calculates correlation columns matrix, rows.","code":""},{"path":"/news/index.html","id":"icikendalltau-0320","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.3.20","title":"ICIKendallTau 0.3.20","text":"kt_fast now uses data.frame format output ici_kendalltau, returns matrix default. data.frame useful large amounts comparisons run.","code":""},{"path":"/news/index.html","id":"icikendalltau-030","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.3.0","title":"ICIKendallTau 0.3.0","text":"Handling parallel execution differently avoid really large matrix issues core. Introduces return_matrix parameter ici_kendalltau allows return results form data.frame instead lists matrices.","code":""},{"path":"/news/index.html","id":"icikendalltau-0210","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.2.10","title":"ICIKendallTau 0.2.10","text":"Provide kt_fast function handles missing NA values similarly stats::cor function, uses ici_kt fast function underneath.","code":""},{"path":"/news/index.html","id":"icikendalltau-028","dir":"Changelog","previous_headings":"","what":"ICIKendalltau 0.2.8","title":"ICIKendalltau 0.2.8","text":"Made error outputs length default output containing NA. Check case one variables ici_kt identical arguments, warns user returns NA.","code":""},{"path":"/news/index.html","id":"icikendalltau-021","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.2.1","title":"ICIKendallTau 0.2.1","text":"Added new argument include_only ici_kendalltau allows user define pairwise correlations actually .","code":""},{"path":"/news/index.html","id":"icikendalltau-0117","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.1.17","title":"ICIKendallTau 0.1.17","text":"switched theme. updated installation instructions use r-universe.","code":""},{"path":"/news/index.html","id":"icikendalltau-0116","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.1.16","title":"ICIKendallTau 0.1.16","text":"updating documentation examples","code":""},{"path":"/news/index.html","id":"icikendalltau-014","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.1.4","title":"ICIKendallTau 0.1.4","text":"Switched pairwise_completeness also use global_na parameter. Oh yes, function pairwise_completeness enable scaling completeness two samples.","code":""},{"path":"/news/index.html","id":"icikendalltau-012","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.1.2","title":"ICIKendallTau 0.1.2","text":"Updated API use single variable, global_na defines values set NA correlation calculation. big API change, bumped version 0.1.","code":""},{"path":"/news/index.html","id":"icikendalltau-006","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.0.6","title":"ICIKendallTau 0.0.6","text":"Fixing bug 55,000 elements vector, match overflows 32 bit 64 bit, results make sense.","code":""},{"path":"/news/index.html","id":"icikendalltau-005","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.0.5","title":"ICIKendallTau 0.0.5","text":"Fixed bug instead returning two element vector, returned zero length value. probably happened one entries contained NA values, tried pass “vectors” less two entries.","code":""},{"path":"/news/index.html","id":"icikendalltau-004","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.0.4","title":"ICIKendallTau 0.0.4","text":"Fixing things came R CMD check documentation. good now (hope).","code":""},{"path":"/news/index.html","id":"icikendalltau-003","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.0.3","title":"ICIKendallTau 0.0.3","text":"Added tests! Removed bunch code wasn’t necessary using incorrect formula’s, correct version ici_kt_pairs function reference purposes.","code":""},{"path":"/news/index.html","id":"icikendalltau-002","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.0.2","title":"ICIKendallTau 0.0.2","text":"Fixed issue warning issued {furrr} installed.","code":""},{"path":"/news/index.html","id":"icikendalltau-001","dir":"Changelog","previous_headings":"","what":"ICIKendallTau 0.0.1","title":"ICIKendallTau 0.0.1","text":"First release. ’s tested used rather thoroughly , ’d say ’s still rather alpha. Even though use time . Added NEWS.md file track changes package.","code":""}]
diff --git a/vignettes/ici-kendalltau.Rmd b/vignettes/ici-kendalltau.Rmd
index e4a30ec..8238c31 100644
--- a/vignettes/ici-kendalltau.Rmd
+++ b/vignettes/ici-kendalltau.Rmd
@@ -102,7 +102,7 @@ The functions that implement this include:
   * The option `perspective` will control how the `NA` values influence ties.
   * When comparing multiple samples, you likely want to use `perspective = "global"`.
 * `ici_kendallt`: Handles comparisons for a matrix.
-  * Rows are samples, columns are features.
+  * Rows are features, columns are samples.
   * Implicitly parallel, but have to call:
     * `library(furrr)`
     * `plan(multiprocess)`