Introduction to RNA-seq
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -661,7 +661,7 @@Key Points
RStudio Project and Experimental Data
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -653,7 +653,7 @@Key Points
Importing and annotating quantified data into R
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -524,7 +524,7 @@Challenge: Discuss the following points with
-
+
- In
counts
, the rows are genes just like the rows in
rowranges
. The columns in counts
are the
@@ -644,7 +644,7 @@ Challenge
Show me the solution
-
+
R
@@ -1021,7 +1021,7 @@ Challenge
Show me the solution
-
+
R
@@ -1148,7 +1148,7 @@ Challenge: How to subset to mRNA genes
Show me the solution
-
+
R
@@ -1332,23 +1332,23 @@ OUTPUT<
[1] hgu95av2.db_3.13.0 org.Hs.eg.db_3.17.0
[3] org.Mm.eg.db_3.17.0 AnnotationDbi_1.62.2
[5] SummarizedExperiment_1.30.2 Biobase_2.60.0
- [7] MatrixGenerics_1.12.3 matrixStats_1.0.0
+ [7] MatrixGenerics_1.12.3 matrixStats_1.2.0
[9] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4
[11] IRanges_2.34.1 S4Vectors_0.38.2
[13] BiocGenerics_0.46.0 knitr_1.45
loaded via a namespace (and not attached):
- [1] Matrix_1.6-1.1 bit_4.0.5 highr_0.10
+ [1] Matrix_1.6-4 bit_4.0.5 highr_0.10
[4] compiler_4.3.2 BiocManager_1.30.22 renv_1.0.3
[7] crayon_1.5.2 blob_1.2.4 Biostrings_2.68.1
[10] bitops_1.0-7 png_0.1-8 fastmap_1.1.1
-[13] yaml_2.3.7 lattice_0.22-5 R6_2.5.1
+[13] yaml_2.3.8 lattice_0.22-5 R6_2.5.1
[16] XVector_0.40.0 S4Arrays_1.0.6 DelayedArray_0.26.7
-[19] GenomeInfoDbData_1.2.10 DBI_1.1.3 rlang_1.1.2
+[19] GenomeInfoDbData_1.2.10 DBI_1.2.0 rlang_1.1.2
[22] KEGGREST_1.40.1 cachem_1.0.8 xfun_0.41
-[25] bit64_4.0.5 RSQLite_2.3.3 memoise_2.0.1
-[28] cli_3.6.1 zlibbioc_1.46.0 grid_4.3.2
-[31] vctrs_0.6.4 evaluate_0.23 abind_1.4-5
+[25] bit64_4.0.5 RSQLite_2.3.4 memoise_2.0.1
+[28] cli_3.6.2 zlibbioc_1.46.0 grid_4.3.2
+[31] vctrs_0.6.5 evaluate_0.23 abind_1.4-5
[34] RCurl_1.98-1.13 httr_1.4.7 pkgconfig_2.0.3
[37] tools_4.3.2
@@ -1424,7 +1424,7 @@ Key Points
Exploratory analysis and quality control
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -834,7 +834,7 @@ OUTPUT<
[5] ComplexHeatmap_2.16.0 ggplot2_3.4.4
[7] vsn_3.68.0 DESeq2_1.40.2
[9] SummarizedExperiment_1.30.2 Biobase_2.60.0
-[11] MatrixGenerics_1.12.3 matrixStats_1.0.0
+[11] MatrixGenerics_1.12.3 matrixStats_1.2.0
[13] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4
[15] IRanges_2.34.1 S4Vectors_0.38.2
[17] BiocGenerics_0.46.0
@@ -842,34 +842,34 @@ OUTPUT<
loaded via a namespace (and not attached):
[1] bitops_1.0-7 rlang_1.1.2 magrittr_2.0.3
[4] shinydashboard_0.7.2 clue_0.3-65 GetoptLong_1.0.5
- [7] compiler_4.3.2 mgcv_1.9-0 png_0.1-8
-[10] vctrs_0.6.4 pkgconfig_2.0.3 shape_1.4.6
+ [7] compiler_4.3.2 mgcv_1.9-1 png_0.1-8
+[10] vctrs_0.6.5 pkgconfig_2.0.3 shape_1.4.6
[13] crayon_1.5.2 fastmap_1.1.1 XVector_0.40.0
[16] ellipsis_0.3.2 labeling_0.4.3 utf8_1.2.4
[19] promises_1.2.1 preprocessCore_1.62.1 shinyAce_0.4.2
[22] xfun_0.41 cachem_1.0.8 zlibbioc_1.46.0
-[25] jsonlite_1.8.7 highr_0.10 later_1.3.1
+[25] jsonlite_1.8.8 highr_0.10 later_1.3.2
[28] DelayedArray_0.26.7 BiocParallel_1.34.2 parallel_4.3.2
-[31] cluster_2.1.4 R6_2.5.1 bslib_0.5.1
+[31] cluster_2.1.6 R6_2.5.1 bslib_0.6.1
[34] limma_3.56.2 jquerylib_0.1.4 Rcpp_1.0.11
-[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.12
-[40] Matrix_1.6-1.1 splines_4.3.2 igraph_1.5.1
-[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.7
+[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.13
+[40] Matrix_1.6-4 splines_4.3.2 igraph_1.6.0
+[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.8
[46] doParallel_1.0.17 codetools_0.2-19 affy_1.78.2
[49] miniUI_0.1.1.1 lattice_0.22-5 tibble_3.2.1
-[52] shiny_1.7.5.1 withr_2.5.2 evaluate_0.23
+[52] shiny_1.8.0 withr_2.5.2 evaluate_0.23
[55] circlize_0.4.15 pillar_1.9.0 affyio_1.70.0
-[58] BiocManager_1.30.22 renv_1.0.3 DT_0.30
+[58] BiocManager_1.30.22 renv_1.0.3 DT_0.31
[61] foreach_1.5.2 shinyjs_2.1.0 generics_0.1.3
-[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.2.1
+[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.3.0
[67] xtable_1.8-4 glue_1.6.2 tools_4.3.2
[70] colourpicker_1.3.0 locfit_1.5-9.8 colorspace_2.1-0
-[73] nlme_3.1-163 GenomeInfoDbData_1.2.10 vipor_0.4.5
-[76] cli_3.6.1 fansi_1.0.5 viridisLite_0.4.2
-[79] S4Arrays_1.0.6 dplyr_1.1.3 gtable_0.3.4
-[82] rintrojs_0.3.3 sass_0.4.7 digest_0.6.33
+[73] nlme_3.1-164 GenomeInfoDbData_1.2.10 vipor_0.4.7
+[76] cli_3.6.2 fansi_1.0.6 viridisLite_0.4.2
+[79] S4Arrays_1.0.6 dplyr_1.1.4 gtable_0.3.4
+[82] rintrojs_0.3.3 sass_0.4.8 digest_0.6.33
[85] ggrepel_0.9.4 farver_2.1.1 rjson_0.2.21
-[88] htmlwidgets_1.6.2 htmltools_0.5.7 lifecycle_1.0.3
+[88] htmlwidgets_1.6.4 htmltools_0.5.7 lifecycle_1.0.4
[91] shinyWidgets_0.8.0 GlobalOptions_0.1.2 mime_0.12
Differential expression analysis
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -1025,7 +1025,7 @@ Key Points
Extra exploration of design matrices
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -657,7 +657,7 @@ Challenge
Show me the solution
-
+
R
@@ -744,7 +744,7 @@ Challenge
Show me the solution
-
+
Gene set enrichment analysis
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -842,9 +842,9 @@ ROUTPUT
Unit: microseconds
- expr min lq mean median uq max neval
- fisher 238.465 243.715 252.68149 246.8705 252.3760 488.411 100
- hyper 1.352 1.543 2.23699 2.5545 2.8355 5.901 100
+ expr min lq mean median uq max neval
+ fisher 238.455 241.8405 250.98679 244.1705 251.2475 552.429 100
+ hyper 1.332 1.5180 2.38207 2.5445 2.8055 17.983 100
It is very astonishing that phyper()
is hundreds of
times faster than fisher.test()
. Main reason is in
@@ -1001,7 +1001,7 @@
Challenge
Show me the solution
-
+
R
@@ -1625,7 +1625,7 @@ OUTPUT<
OUTPUT
---> Expected input gene ID: 76867,320214,23797,110355,217011,103583
+--> Expected input gene ID: 20317,622554,21681,105988,67000,239731
OUTPUT
@@ -1896,12 +1896,12 @@ OUTPUT<
mmu04913 Ovarian steroidogenesis - Mus musculus (house mouse)
mmu04061 Viral protein interaction with cytokine and cytokine receptor - Mus musculus (house mouse)
GeneRatio BgRatio pvalue p.adjust qvalue
-mmu00590 16/454 85/9392 2.456998e-06 0.0007542983 0.0006620963
-mmu00565 11/454 48/9392 1.327107e-05 0.0014975168 0.0013144670
-mmu00592 8/454 25/9392 1.463371e-05 0.0014975168 0.0013144670
-mmu00591 11/454 50/9392 2.009867e-05 0.0015425732 0.0013540159
-mmu04913 12/454 63/9392 3.956222e-05 0.0024291201 0.0021321953
-mmu04061 14/454 95/9392 1.740468e-04 0.0079696743 0.0069954967
+mmu00590 16/454 85/9408 2.403809e-06 0.0007379694 0.0006452329
+mmu00565 11/454 48/9408 1.306159e-05 0.0014791271 0.0012932536
+mmu00592 8/454 25/9408 1.445401e-05 0.0014791271 0.0012932536
+mmu00591 11/454 50/9408 1.978440e-05 0.0015184527 0.0013276373
+mmu04913 12/454 63/9408 3.891349e-05 0.0023892882 0.0020890399
+mmu04061 14/454 95/9408 1.710081e-04 0.0078109667 0.0068294068
geneID
mmu00590 18783/19215/211429/329502/78390/19223/67103/242546/13118/18781/18784/11689/232889/15446/237625/11687
mmu00565 18783/211429/329502/78390/22239/18781/18784/232889/320981/237625/53897
@@ -2647,7 +2647,7 @@ Key Points
Next steps
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -433,7 +433,7 @@ Key Points
Contributor Code of Conduct
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -346,7 +346,7 @@ Contributor Code of Conduct
"url": "https://carpentries-incubator.github.io/bioc-rnaseq/CODE_OF_CONDUCT.html",
"identifier": "https://carpentries-incubator.github.io/bioc-rnaseq/CODE_OF_CONDUCT.html",
"dateCreated": "2020-09-15",
- "dateModified": "2023-11-21",
+ "dateModified": "2024-01-02",
"datePublished": "2024-01-02"
}
diff --git a/LICENSE.html b/LICENSE.html
index 5492e03c..576527ec 100644
--- a/LICENSE.html
+++ b/LICENSE.html
@@ -271,7 +271,7 @@
Licenses
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -397,7 +397,7 @@ Licenses
"url": "https://carpentries-incubator.github.io/bioc-rnaseq/LICENSE.html",
"identifier": "https://carpentries-incubator.github.io/bioc-rnaseq/LICENSE.html",
"dateCreated": "2020-09-15",
- "dateModified": "2023-11-21",
+ "dateModified": "2024-01-02",
"datePublished": "2024-01-02"
}
diff --git a/aio.html b/aio.html
index b97dfa46..548329a1 100644
--- a/aio.html
+++ b/aio.html
@@ -335,7 +335,7 @@
Content from Introduction to RNA-seq
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -682,7 +682,7 @@ Key PointsContent from RStudio Project and Experimental Data
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -1023,7 +1023,7 @@ Key PointsContent from Importing and annotating quantified data into R
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -1264,7 +1264,7 @@ Challenge: Discuss the following points with
-
+
- In
counts
, the rows are genes just like the rows in
@@ -1391,7 +1391,7 @@ Challenge
Show me the solution
-
+
R
@@ -1770,7 +1770,7 @@ Challenge
Show me the solution
-
+
R
@@ -1899,7 +1899,7 @@ Challenge: How to subset to mRNA genes
Show me the solution
-
+
R
@@ -2090,23 +2090,23 @@ OUTPUT<
[1] hgu95av2.db_3.13.0 org.Hs.eg.db_3.17.0
[3] org.Mm.eg.db_3.17.0 AnnotationDbi_1.62.2
[5] SummarizedExperiment_1.30.2 Biobase_2.60.0
- [7] MatrixGenerics_1.12.3 matrixStats_1.0.0
+ [7] MatrixGenerics_1.12.3 matrixStats_1.2.0
[9] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4
[11] IRanges_2.34.1 S4Vectors_0.38.2
[13] BiocGenerics_0.46.0 knitr_1.45
loaded via a namespace (and not attached):
- [1] Matrix_1.6-1.1 bit_4.0.5 highr_0.10
+ [1] Matrix_1.6-4 bit_4.0.5 highr_0.10
[4] compiler_4.3.2 BiocManager_1.30.22 renv_1.0.3
[7] crayon_1.5.2 blob_1.2.4 Biostrings_2.68.1
[10] bitops_1.0-7 png_0.1-8 fastmap_1.1.1
-[13] yaml_2.3.7 lattice_0.22-5 R6_2.5.1
+[13] yaml_2.3.8 lattice_0.22-5 R6_2.5.1
[16] XVector_0.40.0 S4Arrays_1.0.6 DelayedArray_0.26.7
-[19] GenomeInfoDbData_1.2.10 DBI_1.1.3 rlang_1.1.2
+[19] GenomeInfoDbData_1.2.10 DBI_1.2.0 rlang_1.1.2
[22] KEGGREST_1.40.1 cachem_1.0.8 xfun_0.41
-[25] bit64_4.0.5 RSQLite_2.3.3 memoise_2.0.1
-[28] cli_3.6.1 zlibbioc_1.46.0 grid_4.3.2
-[31] vctrs_0.6.4 evaluate_0.23 abind_1.4-5
+[25] bit64_4.0.5 RSQLite_2.3.4 memoise_2.0.1
+[28] cli_3.6.2 zlibbioc_1.46.0 grid_4.3.2
+[31] vctrs_0.6.5 evaluate_0.23 abind_1.4-5
[34] RCurl_1.98-1.13 httr_1.4.7 pkgconfig_2.0.3
[37] tools_4.3.2
@@ -2132,7 +2132,7 @@ Key PointsContent from Exploratory analysis and quality control
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -2700,7 +2700,7 @@ OUTPUT<
[5] ComplexHeatmap_2.16.0 ggplot2_3.4.4
[7] vsn_3.68.0 DESeq2_1.40.2
[9] SummarizedExperiment_1.30.2 Biobase_2.60.0
-[11] MatrixGenerics_1.12.3 matrixStats_1.0.0
+[11] MatrixGenerics_1.12.3 matrixStats_1.2.0
[13] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4
[15] IRanges_2.34.1 S4Vectors_0.38.2
[17] BiocGenerics_0.46.0
@@ -2708,34 +2708,34 @@ OUTPUT<
loaded via a namespace (and not attached):
[1] bitops_1.0-7 rlang_1.1.2 magrittr_2.0.3
[4] shinydashboard_0.7.2 clue_0.3-65 GetoptLong_1.0.5
- [7] compiler_4.3.2 mgcv_1.9-0 png_0.1-8
-[10] vctrs_0.6.4 pkgconfig_2.0.3 shape_1.4.6
+ [7] compiler_4.3.2 mgcv_1.9-1 png_0.1-8
+[10] vctrs_0.6.5 pkgconfig_2.0.3 shape_1.4.6
[13] crayon_1.5.2 fastmap_1.1.1 XVector_0.40.0
[16] ellipsis_0.3.2 labeling_0.4.3 utf8_1.2.4
[19] promises_1.2.1 preprocessCore_1.62.1 shinyAce_0.4.2
[22] xfun_0.41 cachem_1.0.8 zlibbioc_1.46.0
-[25] jsonlite_1.8.7 highr_0.10 later_1.3.1
+[25] jsonlite_1.8.8 highr_0.10 later_1.3.2
[28] DelayedArray_0.26.7 BiocParallel_1.34.2 parallel_4.3.2
-[31] cluster_2.1.4 R6_2.5.1 bslib_0.5.1
+[31] cluster_2.1.6 R6_2.5.1 bslib_0.6.1
[34] limma_3.56.2 jquerylib_0.1.4 Rcpp_1.0.11
-[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.12
-[40] Matrix_1.6-1.1 splines_4.3.2 igraph_1.5.1
-[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.7
+[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.13
+[40] Matrix_1.6-4 splines_4.3.2 igraph_1.6.0
+[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.8
[46] doParallel_1.0.17 codetools_0.2-19 affy_1.78.2
[49] miniUI_0.1.1.1 lattice_0.22-5 tibble_3.2.1
-[52] shiny_1.7.5.1 withr_2.5.2 evaluate_0.23
+[52] shiny_1.8.0 withr_2.5.2 evaluate_0.23
[55] circlize_0.4.15 pillar_1.9.0 affyio_1.70.0
-[58] BiocManager_1.30.22 renv_1.0.3 DT_0.30
+[58] BiocManager_1.30.22 renv_1.0.3 DT_0.31
[61] foreach_1.5.2 shinyjs_2.1.0 generics_0.1.3
-[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.2.1
+[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.3.0
[67] xtable_1.8-4 glue_1.6.2 tools_4.3.2
[70] colourpicker_1.3.0 locfit_1.5-9.8 colorspace_2.1-0
-[73] nlme_3.1-163 GenomeInfoDbData_1.2.10 vipor_0.4.5
-[76] cli_3.6.1 fansi_1.0.5 viridisLite_0.4.2
-[79] S4Arrays_1.0.6 dplyr_1.1.3 gtable_0.3.4
-[82] rintrojs_0.3.3 sass_0.4.7 digest_0.6.33
+[73] nlme_3.1-164 GenomeInfoDbData_1.2.10 vipor_0.4.7
+[76] cli_3.6.2 fansi_1.0.6 viridisLite_0.4.2
+[79] S4Arrays_1.0.6 dplyr_1.1.4 gtable_0.3.4
+[82] rintrojs_0.3.3 sass_0.4.8 digest_0.6.33
[85] ggrepel_0.9.4 farver_2.1.1 rjson_0.2.21
-[88] htmlwidgets_1.6.2 htmltools_0.5.7 lifecycle_1.0.3
+[88] htmlwidgets_1.6.4 htmltools_0.5.7 lifecycle_1.0.4
[91] shinyWidgets_0.8.0 GlobalOptions_0.1.2 mime_0.12
@@ -2760,7 +2760,7 @@ Key PointsContent from Differential expression analysis
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -3460,7 +3460,7 @@ Key PointsContent from Extra exploration of design matrices
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -3826,7 +3826,7 @@ Challenge
Show me the solution
-
+
R
@@ -3914,7 +3914,7 @@ Challenge
Show me the solution
-
+
R
@@ -5127,7 +5127,7 @@ Key PointsContent from Gene set enrichment analysis
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -5724,9 +5724,9 @@ ROUTPUT
Unit: microseconds
- expr min lq mean median uq max neval
- fisher 238.465 243.715 252.68149 246.8705 252.3760 488.411 100
- hyper 1.352 1.543 2.23699 2.5545 2.8355 5.901 100
+ expr min lq mean median uq max neval
+ fisher 238.455 241.8405 250.98679 244.1705 251.2475 552.429 100
+ hyper 1.332 1.5180 2.38207 2.5445 2.8055 17.983 100
It is very astonishing that phyper()
is hundreds of
times faster than fisher.test()
. Main reason is in
@@ -5886,7 +5886,7 @@
Challenge
Show me the solution
-
+
R
@@ -6545,7 +6545,7 @@ OUTPUT<
OUTPUT
---> Expected input gene ID: 76867,320214,23797,110355,217011,103583
+--> Expected input gene ID: 20317,622554,21681,105988,67000,239731
OUTPUT
@@ -6823,12 +6823,12 @@ OUTPUT<
mmu04913 Ovarian steroidogenesis - Mus musculus (house mouse)
mmu04061 Viral protein interaction with cytokine and cytokine receptor - Mus musculus (house mouse)
GeneRatio BgRatio pvalue p.adjust qvalue
-mmu00590 16/454 85/9392 2.456998e-06 0.0007542983 0.0006620963
-mmu00565 11/454 48/9392 1.327107e-05 0.0014975168 0.0013144670
-mmu00592 8/454 25/9392 1.463371e-05 0.0014975168 0.0013144670
-mmu00591 11/454 50/9392 2.009867e-05 0.0015425732 0.0013540159
-mmu04913 12/454 63/9392 3.956222e-05 0.0024291201 0.0021321953
-mmu04061 14/454 95/9392 1.740468e-04 0.0079696743 0.0069954967
+mmu00590 16/454 85/9408 2.403809e-06 0.0007379694 0.0006452329
+mmu00565 11/454 48/9408 1.306159e-05 0.0014791271 0.0012932536
+mmu00592 8/454 25/9408 1.445401e-05 0.0014791271 0.0012932536
+mmu00591 11/454 50/9408 1.978440e-05 0.0015184527 0.0013276373
+mmu04913 12/454 63/9408 3.891349e-05 0.0023892882 0.0020890399
+mmu04061 14/454 95/9408 1.710081e-04 0.0078109667 0.0068294068
geneID
mmu00590 18783/19215/211429/329502/78390/19223/67103/242546/13118/18781/18784/11689/232889/15446/237625/11687
mmu00565 18783/211429/329502/78390/22239/18781/18784/232889/320981/237625/53897
@@ -7549,7 +7549,7 @@ Key PointsContent from Next steps
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
diff --git a/discuss.html b/discuss.html
index 90ba1cf1..86ecf245 100644
--- a/discuss.html
+++ b/discuss.html
@@ -271,7 +271,7 @@
Discussion
- Last updated on 2023-11-21 |
+
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@@ -339,7 +339,7 @@ Discussion
"url": "https://carpentries-incubator.github.io/bioc-rnaseq/discuss.html",
"identifier": "https://carpentries-incubator.github.io/bioc-rnaseq/discuss.html",
"dateCreated": "2020-09-15",
- "dateModified": "2023-11-21",
+ "dateModified": "2024-01-02",
"datePublished": "2024-01-02"
}
diff --git a/fig/04-exploratory-qc-rendered-pca-exercise-1.png b/fig/04-exploratory-qc-rendered-pca-exercise-1.png
index 3a80b3f2..25e565b8 100644
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diff --git a/fig/05-differential-expression-rendered-heatmap-time-1.png b/fig/05-differential-expression-rendered-heatmap-time-1.png
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diff --git a/fig/07-gene-set-analysis-rendered-hypergeom-1.png b/fig/07-gene-set-analysis-rendered-hypergeom-1.png
index 950e15f0..a02c0f23 100644
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diff --git a/instructor/01-intro-to-rnaseq.html b/instructor/01-intro-to-rnaseq.html
index 67d1fd31..0307f54a 100644
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@@ -275,7 +275,7 @@
Introduction to RNA-seq
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -663,7 +663,7 @@ Key Points
RStudio Project and Experimental Data
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
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@@ -655,7 +655,7 @@ Key Points
Importing and annotating quantified data into R
- Last updated on 2023-11-21 |
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Last updated on 2024-01-02 |
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@@ -526,7 +526,7 @@ Challenge: Discuss the following points with
-
+
- In
counts
, the rows are genes just like the rows in
rowranges
. The columns in counts
are the
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Show me the solution
-
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R
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Show me the solution
-
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R
@@ -1150,7 +1150,7 @@ Challenge: How to subset to mRNA genes
Show me the solution
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R
@@ -1334,23 +1334,23 @@ OUTPUT<
[1] hgu95av2.db_3.13.0 org.Hs.eg.db_3.17.0
[3] org.Mm.eg.db_3.17.0 AnnotationDbi_1.62.2
[5] SummarizedExperiment_1.30.2 Biobase_2.60.0
- [7] MatrixGenerics_1.12.3 matrixStats_1.0.0
+ [7] MatrixGenerics_1.12.3 matrixStats_1.2.0
[9] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4
[11] IRanges_2.34.1 S4Vectors_0.38.2
[13] BiocGenerics_0.46.0 knitr_1.45
loaded via a namespace (and not attached):
- [1] Matrix_1.6-1.1 bit_4.0.5 highr_0.10
+ [1] Matrix_1.6-4 bit_4.0.5 highr_0.10
[4] compiler_4.3.2 BiocManager_1.30.22 renv_1.0.3
[7] crayon_1.5.2 blob_1.2.4 Biostrings_2.68.1
[10] bitops_1.0-7 png_0.1-8 fastmap_1.1.1
-[13] yaml_2.3.7 lattice_0.22-5 R6_2.5.1
+[13] yaml_2.3.8 lattice_0.22-5 R6_2.5.1
[16] XVector_0.40.0 S4Arrays_1.0.6 DelayedArray_0.26.7
-[19] GenomeInfoDbData_1.2.10 DBI_1.1.3 rlang_1.1.2
+[19] GenomeInfoDbData_1.2.10 DBI_1.2.0 rlang_1.1.2
[22] KEGGREST_1.40.1 cachem_1.0.8 xfun_0.41
-[25] bit64_4.0.5 RSQLite_2.3.3 memoise_2.0.1
-[28] cli_3.6.1 zlibbioc_1.46.0 grid_4.3.2
-[31] vctrs_0.6.4 evaluate_0.23 abind_1.4-5
+[25] bit64_4.0.5 RSQLite_2.3.4 memoise_2.0.1
+[28] cli_3.6.2 zlibbioc_1.46.0 grid_4.3.2
+[31] vctrs_0.6.5 evaluate_0.23 abind_1.4-5
[34] RCurl_1.98-1.13 httr_1.4.7 pkgconfig_2.0.3
[37] tools_4.3.2
@@ -1426,7 +1426,7 @@ Key Points
Exploratory analysis and quality control
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -836,7 +836,7 @@ OUTPUT<
[5] ComplexHeatmap_2.16.0 ggplot2_3.4.4
[7] vsn_3.68.0 DESeq2_1.40.2
[9] SummarizedExperiment_1.30.2 Biobase_2.60.0
-[11] MatrixGenerics_1.12.3 matrixStats_1.0.0
+[11] MatrixGenerics_1.12.3 matrixStats_1.2.0
[13] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4
[15] IRanges_2.34.1 S4Vectors_0.38.2
[17] BiocGenerics_0.46.0
@@ -844,34 +844,34 @@ OUTPUT<
loaded via a namespace (and not attached):
[1] bitops_1.0-7 rlang_1.1.2 magrittr_2.0.3
[4] shinydashboard_0.7.2 clue_0.3-65 GetoptLong_1.0.5
- [7] compiler_4.3.2 mgcv_1.9-0 png_0.1-8
-[10] vctrs_0.6.4 pkgconfig_2.0.3 shape_1.4.6
+ [7] compiler_4.3.2 mgcv_1.9-1 png_0.1-8
+[10] vctrs_0.6.5 pkgconfig_2.0.3 shape_1.4.6
[13] crayon_1.5.2 fastmap_1.1.1 XVector_0.40.0
[16] ellipsis_0.3.2 labeling_0.4.3 utf8_1.2.4
[19] promises_1.2.1 preprocessCore_1.62.1 shinyAce_0.4.2
[22] xfun_0.41 cachem_1.0.8 zlibbioc_1.46.0
-[25] jsonlite_1.8.7 highr_0.10 later_1.3.1
+[25] jsonlite_1.8.8 highr_0.10 later_1.3.2
[28] DelayedArray_0.26.7 BiocParallel_1.34.2 parallel_4.3.2
-[31] cluster_2.1.4 R6_2.5.1 bslib_0.5.1
+[31] cluster_2.1.6 R6_2.5.1 bslib_0.6.1
[34] limma_3.56.2 jquerylib_0.1.4 Rcpp_1.0.11
-[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.12
-[40] Matrix_1.6-1.1 splines_4.3.2 igraph_1.5.1
-[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.7
+[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.13
+[40] Matrix_1.6-4 splines_4.3.2 igraph_1.6.0
+[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.8
[46] doParallel_1.0.17 codetools_0.2-19 affy_1.78.2
[49] miniUI_0.1.1.1 lattice_0.22-5 tibble_3.2.1
-[52] shiny_1.7.5.1 withr_2.5.2 evaluate_0.23
+[52] shiny_1.8.0 withr_2.5.2 evaluate_0.23
[55] circlize_0.4.15 pillar_1.9.0 affyio_1.70.0
-[58] BiocManager_1.30.22 renv_1.0.3 DT_0.30
+[58] BiocManager_1.30.22 renv_1.0.3 DT_0.31
[61] foreach_1.5.2 shinyjs_2.1.0 generics_0.1.3
-[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.2.1
+[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.3.0
[67] xtable_1.8-4 glue_1.6.2 tools_4.3.2
[70] colourpicker_1.3.0 locfit_1.5-9.8 colorspace_2.1-0
-[73] nlme_3.1-163 GenomeInfoDbData_1.2.10 vipor_0.4.5
-[76] cli_3.6.1 fansi_1.0.5 viridisLite_0.4.2
-[79] S4Arrays_1.0.6 dplyr_1.1.3 gtable_0.3.4
-[82] rintrojs_0.3.3 sass_0.4.7 digest_0.6.33
+[73] nlme_3.1-164 GenomeInfoDbData_1.2.10 vipor_0.4.7
+[76] cli_3.6.2 fansi_1.0.6 viridisLite_0.4.2
+[79] S4Arrays_1.0.6 dplyr_1.1.4 gtable_0.3.4
+[82] rintrojs_0.3.3 sass_0.4.8 digest_0.6.33
[85] ggrepel_0.9.4 farver_2.1.1 rjson_0.2.21
-[88] htmlwidgets_1.6.2 htmltools_0.5.7 lifecycle_1.0.3
+[88] htmlwidgets_1.6.4 htmltools_0.5.7 lifecycle_1.0.4
[91] shinyWidgets_0.8.0 GlobalOptions_0.1.2 mime_0.12
Differential expression analysis
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -1092,7 +1092,7 @@ Key Points
Extra exploration of design matrices
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -659,7 +659,7 @@ Challenge
Show me the solution
-
+
R
@@ -746,7 +746,7 @@ Challenge
Show me the solution
-
+
Gene set enrichment analysis
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
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@@ -844,9 +844,9 @@ ROUTPUT
Unit: microseconds
- expr min lq mean median uq max neval
- fisher 238.465 243.715 252.68149 246.8705 252.3760 488.411 100
- hyper 1.352 1.543 2.23699 2.5545 2.8355 5.901 100
+ expr min lq mean median uq max neval
+ fisher 238.455 241.8405 250.98679 244.1705 251.2475 552.429 100
+ hyper 1.332 1.5180 2.38207 2.5445 2.8055 17.983 100
It is very astonishing that phyper()
is hundreds of
times faster than fisher.test()
. Main reason is in
@@ -1003,7 +1003,7 @@
Challenge
Show me the solution
-
+
R
@@ -1627,7 +1627,7 @@ OUTPUT<
OUTPUT
---> Expected input gene ID: 76867,320214,23797,110355,217011,103583
+--> Expected input gene ID: 20317,622554,21681,105988,67000,239731
OUTPUT
@@ -1898,12 +1898,12 @@ OUTPUT<
mmu04913 Ovarian steroidogenesis - Mus musculus (house mouse)
mmu04061 Viral protein interaction with cytokine and cytokine receptor - Mus musculus (house mouse)
GeneRatio BgRatio pvalue p.adjust qvalue
-mmu00590 16/454 85/9392 2.456998e-06 0.0007542983 0.0006620963
-mmu00565 11/454 48/9392 1.327107e-05 0.0014975168 0.0013144670
-mmu00592 8/454 25/9392 1.463371e-05 0.0014975168 0.0013144670
-mmu00591 11/454 50/9392 2.009867e-05 0.0015425732 0.0013540159
-mmu04913 12/454 63/9392 3.956222e-05 0.0024291201 0.0021321953
-mmu04061 14/454 95/9392 1.740468e-04 0.0079696743 0.0069954967
+mmu00590 16/454 85/9408 2.403809e-06 0.0007379694 0.0006452329
+mmu00565 11/454 48/9408 1.306159e-05 0.0014791271 0.0012932536
+mmu00592 8/454 25/9408 1.445401e-05 0.0014791271 0.0012932536
+mmu00591 11/454 50/9408 1.978440e-05 0.0015184527 0.0013276373
+mmu04913 12/454 63/9408 3.891349e-05 0.0023892882 0.0020890399
+mmu04061 14/454 95/9408 1.710081e-04 0.0078109667 0.0068294068
geneID
mmu00590 18783/19215/211429/329502/78390/19223/67103/242546/13118/18781/18784/11689/232889/15446/237625/11687
mmu00565 18783/211429/329502/78390/22239/18781/18784/232889/320981/237625/53897
@@ -2649,7 +2649,7 @@ Key Points
Next steps
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
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@@ -435,7 +435,7 @@ Key Points
Contributor Code of Conduct
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
@@ -348,7 +348,7 @@ Contributor Code of Conduct
"url": "https://carpentries-incubator.github.io/bioc-rnaseq/instructor/CODE_OF_CONDUCT.html",
"identifier": "https://carpentries-incubator.github.io/bioc-rnaseq/instructor/CODE_OF_CONDUCT.html",
"dateCreated": "2020-09-15",
- "dateModified": "2023-11-21",
+ "dateModified": "2024-01-02",
"datePublished": "2024-01-02"
}
diff --git a/instructor/LICENSE.html b/instructor/LICENSE.html
index e3f22897..82c00c92 100644
--- a/instructor/LICENSE.html
+++ b/instructor/LICENSE.html
@@ -271,7 +271,7 @@
Licenses
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
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@@ -399,7 +399,7 @@ Licenses
"url": "https://carpentries-incubator.github.io/bioc-rnaseq/instructor/LICENSE.html",
"identifier": "https://carpentries-incubator.github.io/bioc-rnaseq/instructor/LICENSE.html",
"dateCreated": "2020-09-15",
- "dateModified": "2023-11-21",
+ "dateModified": "2024-01-02",
"datePublished": "2024-01-02"
}
diff --git a/instructor/aio.html b/instructor/aio.html
index 79c38c27..a3ce2f48 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -337,7 +337,7 @@
Content from Introduction to RNA-seq
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
Estimated time 100 minutes
@@ -685,7 +685,7 @@ Key PointsContent from RStudio Project and Experimental Data
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
Estimated time 30 minutes
@@ -1027,7 +1027,7 @@ Key PointsContent from Importing and annotating quantified data into R
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
Estimated time 120 minutes
@@ -1269,7 +1269,7 @@ Challenge: Discuss the following points with
-
+
- In
counts
, the rows are genes just like the rows in
@@ -1396,7 +1396,7 @@ Challenge
Show me the solution
-
+
R
@@ -1775,7 +1775,7 @@ Challenge
Show me the solution
-
+
R
@@ -1904,7 +1904,7 @@ Challenge: How to subset to mRNA genes
Show me the solution
-
+
R
@@ -2095,23 +2095,23 @@ OUTPUT<
[1] hgu95av2.db_3.13.0 org.Hs.eg.db_3.17.0
[3] org.Mm.eg.db_3.17.0 AnnotationDbi_1.62.2
[5] SummarizedExperiment_1.30.2 Biobase_2.60.0
- [7] MatrixGenerics_1.12.3 matrixStats_1.0.0
+ [7] MatrixGenerics_1.12.3 matrixStats_1.2.0
[9] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4
[11] IRanges_2.34.1 S4Vectors_0.38.2
[13] BiocGenerics_0.46.0 knitr_1.45
loaded via a namespace (and not attached):
- [1] Matrix_1.6-1.1 bit_4.0.5 highr_0.10
+ [1] Matrix_1.6-4 bit_4.0.5 highr_0.10
[4] compiler_4.3.2 BiocManager_1.30.22 renv_1.0.3
[7] crayon_1.5.2 blob_1.2.4 Biostrings_2.68.1
[10] bitops_1.0-7 png_0.1-8 fastmap_1.1.1
-[13] yaml_2.3.7 lattice_0.22-5 R6_2.5.1
+[13] yaml_2.3.8 lattice_0.22-5 R6_2.5.1
[16] XVector_0.40.0 S4Arrays_1.0.6 DelayedArray_0.26.7
-[19] GenomeInfoDbData_1.2.10 DBI_1.1.3 rlang_1.1.2
+[19] GenomeInfoDbData_1.2.10 DBI_1.2.0 rlang_1.1.2
[22] KEGGREST_1.40.1 cachem_1.0.8 xfun_0.41
-[25] bit64_4.0.5 RSQLite_2.3.3 memoise_2.0.1
-[28] cli_3.6.1 zlibbioc_1.46.0 grid_4.3.2
-[31] vctrs_0.6.4 evaluate_0.23 abind_1.4-5
+[25] bit64_4.0.5 RSQLite_2.3.4 memoise_2.0.1
+[28] cli_3.6.2 zlibbioc_1.46.0 grid_4.3.2
+[31] vctrs_0.6.5 evaluate_0.23 abind_1.4-5
[34] RCurl_1.98-1.13 httr_1.4.7 pkgconfig_2.0.3
[37] tools_4.3.2
@@ -2137,7 +2137,7 @@ Key PointsContent from Exploratory analysis and quality control
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
Estimated time 180 minutes
@@ -2706,7 +2706,7 @@ OUTPUT<
[5] ComplexHeatmap_2.16.0 ggplot2_3.4.4
[7] vsn_3.68.0 DESeq2_1.40.2
[9] SummarizedExperiment_1.30.2 Biobase_2.60.0
-[11] MatrixGenerics_1.12.3 matrixStats_1.0.0
+[11] MatrixGenerics_1.12.3 matrixStats_1.2.0
[13] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4
[15] IRanges_2.34.1 S4Vectors_0.38.2
[17] BiocGenerics_0.46.0
@@ -2714,34 +2714,34 @@ OUTPUT<
loaded via a namespace (and not attached):
[1] bitops_1.0-7 rlang_1.1.2 magrittr_2.0.3
[4] shinydashboard_0.7.2 clue_0.3-65 GetoptLong_1.0.5
- [7] compiler_4.3.2 mgcv_1.9-0 png_0.1-8
-[10] vctrs_0.6.4 pkgconfig_2.0.3 shape_1.4.6
+ [7] compiler_4.3.2 mgcv_1.9-1 png_0.1-8
+[10] vctrs_0.6.5 pkgconfig_2.0.3 shape_1.4.6
[13] crayon_1.5.2 fastmap_1.1.1 XVector_0.40.0
[16] ellipsis_0.3.2 labeling_0.4.3 utf8_1.2.4
[19] promises_1.2.1 preprocessCore_1.62.1 shinyAce_0.4.2
[22] xfun_0.41 cachem_1.0.8 zlibbioc_1.46.0
-[25] jsonlite_1.8.7 highr_0.10 later_1.3.1
+[25] jsonlite_1.8.8 highr_0.10 later_1.3.2
[28] DelayedArray_0.26.7 BiocParallel_1.34.2 parallel_4.3.2
-[31] cluster_2.1.4 R6_2.5.1 bslib_0.5.1
+[31] cluster_2.1.6 R6_2.5.1 bslib_0.6.1
[34] limma_3.56.2 jquerylib_0.1.4 Rcpp_1.0.11
-[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.12
-[40] Matrix_1.6-1.1 splines_4.3.2 igraph_1.5.1
-[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.7
+[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.13
+[40] Matrix_1.6-4 splines_4.3.2 igraph_1.6.0
+[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.8
[46] doParallel_1.0.17 codetools_0.2-19 affy_1.78.2
[49] miniUI_0.1.1.1 lattice_0.22-5 tibble_3.2.1
-[52] shiny_1.7.5.1 withr_2.5.2 evaluate_0.23
+[52] shiny_1.8.0 withr_2.5.2 evaluate_0.23
[55] circlize_0.4.15 pillar_1.9.0 affyio_1.70.0
-[58] BiocManager_1.30.22 renv_1.0.3 DT_0.30
+[58] BiocManager_1.30.22 renv_1.0.3 DT_0.31
[61] foreach_1.5.2 shinyjs_2.1.0 generics_0.1.3
-[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.2.1
+[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.3.0
[67] xtable_1.8-4 glue_1.6.2 tools_4.3.2
[70] colourpicker_1.3.0 locfit_1.5-9.8 colorspace_2.1-0
-[73] nlme_3.1-163 GenomeInfoDbData_1.2.10 vipor_0.4.5
-[76] cli_3.6.1 fansi_1.0.5 viridisLite_0.4.2
-[79] S4Arrays_1.0.6 dplyr_1.1.3 gtable_0.3.4
-[82] rintrojs_0.3.3 sass_0.4.7 digest_0.6.33
+[73] nlme_3.1-164 GenomeInfoDbData_1.2.10 vipor_0.4.7
+[76] cli_3.6.2 fansi_1.0.6 viridisLite_0.4.2
+[79] S4Arrays_1.0.6 dplyr_1.1.4 gtable_0.3.4
+[82] rintrojs_0.3.3 sass_0.4.8 digest_0.6.33
[85] ggrepel_0.9.4 farver_2.1.1 rjson_0.2.21
-[88] htmlwidgets_1.6.2 htmltools_0.5.7 lifecycle_1.0.3
+[88] htmlwidgets_1.6.4 htmltools_0.5.7 lifecycle_1.0.4
[91] shinyWidgets_0.8.0 GlobalOptions_0.1.2 mime_0.12
@@ -2766,7 +2766,7 @@ Key PointsContent from Differential expression analysis
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
Estimated time 105 minutes
@@ -3532,7 +3532,7 @@ Key PointsContent from Extra exploration of design matrices
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
Estimated time 60 minutes
@@ -3899,7 +3899,7 @@ Challenge
Show me the solution
-
+
R
@@ -3987,7 +3987,7 @@ Challenge
Show me the solution
-
+
R
@@ -5200,7 +5200,7 @@ Key PointsContent from Gene set enrichment analysis
- Last updated on 2023-11-21 |
+
Last updated on 2024-01-02 |
Edit this page
Estimated time 105 minutes
@@ -5798,9 +5798,9 @@ ROUTPUT
Unit: microseconds
- expr min lq mean median uq max neval
- fisher 238.465 243.715 252.68149 246.8705 252.3760 488.411 100
- hyper 1.352 1.543 2.23699 2.5545 2.8355 5.901 100
+ expr min lq mean median uq max neval
+ fisher 238.455 241.8405 250.98679 244.1705 251.2475 552.429 100
+ hyper 1.332 1.5180 2.38207 2.5445 2.8055 17.983 100
It is very astonishing that phyper()
is hundreds of
times faster than fisher.test()
. Main reason is in
@@ -5960,7 +5960,7 @@
Challenge
Show me the solution
-
+
R
@@ -6619,7 +6619,7 @@ OUTPUT<
OUTPUT
---> Expected input gene ID: 76867,320214,23797,110355,217011,103583
+--> Expected input gene ID: 20317,622554,21681,105988,67000,239731
OUTPUT
@@ -6897,12 +6897,12 @@ OUTPUT<
mmu04913 Ovarian steroidogenesis - Mus musculus (house mouse)
mmu04061 Viral protein interaction with cytokine and cytokine receptor - Mus musculus (house mouse)
GeneRatio BgRatio pvalue p.adjust qvalue
-mmu00590 16/454 85/9392 2.456998e-06 0.0007542983 0.0006620963
-mmu00565 11/454 48/9392 1.327107e-05 0.0014975168 0.0013144670
-mmu00592 8/454 25/9392 1.463371e-05 0.0014975168 0.0013144670
-mmu00591 11/454 50/9392 2.009867e-05 0.0015425732 0.0013540159
-mmu04913 12/454 63/9392 3.956222e-05 0.0024291201 0.0021321953
-mmu04061 14/454 95/9392 1.740468e-04 0.0079696743 0.0069954967
+mmu00590 16/454 85/9408 2.403809e-06 0.0007379694 0.0006452329
+mmu00565 11/454 48/9408 1.306159e-05 0.0014791271 0.0012932536
+mmu00592 8/454 25/9408 1.445401e-05 0.0014791271 0.0012932536
+mmu00591 11/454 50/9408 1.978440e-05 0.0015184527 0.0013276373
+mmu04913 12/454 63/9408 3.891349e-05 0.0023892882 0.0020890399
+mmu04061 14/454 95/9408 1.710081e-04 0.0078109667 0.0068294068
geneID
mmu00590 18783/19215/211429/329502/78390/19223/67103/242546/13118/18781/18784/11689/232889/15446/237625/11687
mmu00565 18783/211429/329502/78390/22239/18781/18784/232889/320981/237625/53897
@@ -7623,7 +7623,7 @@ Key PointsContent from
- In
counts
, the rows are genes just like the rows inrowranges
. The columns incounts
are the @@ -644,7 +644,7 @@Challenge
Show me the solution
-+R @@ -1021,7 +1021,7 @@
Challenge
Show me the solution
-+R @@ -1148,7 +1148,7 @@
Challenge: How to subset to mRNA genes
Show me the solution
-+R @@ -1332,23 +1332,23 @@
OUTPUT< [1] hgu95av2.db_3.13.0 org.Hs.eg.db_3.17.0 [3] org.Mm.eg.db_3.17.0 AnnotationDbi_1.62.2 [5] SummarizedExperiment_1.30.2 Biobase_2.60.0 - [7] MatrixGenerics_1.12.3 matrixStats_1.0.0 + [7] MatrixGenerics_1.12.3 matrixStats_1.2.0 [9] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4 [11] IRanges_2.34.1 S4Vectors_0.38.2 [13] BiocGenerics_0.46.0 knitr_1.45 loaded via a namespace (and not attached): - [1] Matrix_1.6-1.1 bit_4.0.5 highr_0.10 + [1] Matrix_1.6-4 bit_4.0.5 highr_0.10 [4] compiler_4.3.2 BiocManager_1.30.22 renv_1.0.3 [7] crayon_1.5.2 blob_1.2.4 Biostrings_2.68.1 [10] bitops_1.0-7 png_0.1-8 fastmap_1.1.1 -[13] yaml_2.3.7 lattice_0.22-5 R6_2.5.1 +[13] yaml_2.3.8 lattice_0.22-5 R6_2.5.1 [16] XVector_0.40.0 S4Arrays_1.0.6 DelayedArray_0.26.7 -[19] GenomeInfoDbData_1.2.10 DBI_1.1.3 rlang_1.1.2 +[19] GenomeInfoDbData_1.2.10 DBI_1.2.0 rlang_1.1.2 [22] KEGGREST_1.40.1 cachem_1.0.8 xfun_0.41 -[25] bit64_4.0.5 RSQLite_2.3.3 memoise_2.0.1 -[28] cli_3.6.1 zlibbioc_1.46.0 grid_4.3.2 -[31] vctrs_0.6.4 evaluate_0.23 abind_1.4-5 +[25] bit64_4.0.5 RSQLite_2.3.4 memoise_2.0.1 +[28] cli_3.6.2 zlibbioc_1.46.0 grid_4.3.2 +[31] vctrs_0.6.5 evaluate_0.23 abind_1.4-5 [34] RCurl_1.98-1.13 httr_1.4.7 pkgconfig_2.0.3 [37] tools_4.3.2
Key Points
Exploratory analysis and quality control
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -834,7 +834,7 @@OUTPUT< [5] ComplexHeatmap_2.16.0 ggplot2_3.4.4 [7] vsn_3.68.0 DESeq2_1.40.2 [9] SummarizedExperiment_1.30.2 Biobase_2.60.0 -[11] MatrixGenerics_1.12.3 matrixStats_1.0.0 +[11] MatrixGenerics_1.12.3 matrixStats_1.2.0 [13] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4 [15] IRanges_2.34.1 S4Vectors_0.38.2 [17] BiocGenerics_0.46.0 @@ -842,34 +842,34 @@
OUTPUT< loaded via a namespace (and not attached): [1] bitops_1.0-7 rlang_1.1.2 magrittr_2.0.3 [4] shinydashboard_0.7.2 clue_0.3-65 GetoptLong_1.0.5 - [7] compiler_4.3.2 mgcv_1.9-0 png_0.1-8 -[10] vctrs_0.6.4 pkgconfig_2.0.3 shape_1.4.6 + [7] compiler_4.3.2 mgcv_1.9-1 png_0.1-8 +[10] vctrs_0.6.5 pkgconfig_2.0.3 shape_1.4.6 [13] crayon_1.5.2 fastmap_1.1.1 XVector_0.40.0 [16] ellipsis_0.3.2 labeling_0.4.3 utf8_1.2.4 [19] promises_1.2.1 preprocessCore_1.62.1 shinyAce_0.4.2 [22] xfun_0.41 cachem_1.0.8 zlibbioc_1.46.0 -[25] jsonlite_1.8.7 highr_0.10 later_1.3.1 +[25] jsonlite_1.8.8 highr_0.10 later_1.3.2 [28] DelayedArray_0.26.7 BiocParallel_1.34.2 parallel_4.3.2 -[31] cluster_2.1.4 R6_2.5.1 bslib_0.5.1 +[31] cluster_2.1.6 R6_2.5.1 bslib_0.6.1 [34] limma_3.56.2 jquerylib_0.1.4 Rcpp_1.0.11 -[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.12 -[40] Matrix_1.6-1.1 splines_4.3.2 igraph_1.5.1 -[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.7 +[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.13 +[40] Matrix_1.6-4 splines_4.3.2 igraph_1.6.0 +[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.8 [46] doParallel_1.0.17 codetools_0.2-19 affy_1.78.2 [49] miniUI_0.1.1.1 lattice_0.22-5 tibble_3.2.1 -[52] shiny_1.7.5.1 withr_2.5.2 evaluate_0.23 +[52] shiny_1.8.0 withr_2.5.2 evaluate_0.23 [55] circlize_0.4.15 pillar_1.9.0 affyio_1.70.0 -[58] BiocManager_1.30.22 renv_1.0.3 DT_0.30 +[58] BiocManager_1.30.22 renv_1.0.3 DT_0.31 [61] foreach_1.5.2 shinyjs_2.1.0 generics_0.1.3 -[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.2.1 +[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.3.0 [67] xtable_1.8-4 glue_1.6.2 tools_4.3.2 [70] colourpicker_1.3.0 locfit_1.5-9.8 colorspace_2.1-0 -[73] nlme_3.1-163 GenomeInfoDbData_1.2.10 vipor_0.4.5 -[76] cli_3.6.1 fansi_1.0.5 viridisLite_0.4.2 -[79] S4Arrays_1.0.6 dplyr_1.1.3 gtable_0.3.4 -[82] rintrojs_0.3.3 sass_0.4.7 digest_0.6.33 +[73] nlme_3.1-164 GenomeInfoDbData_1.2.10 vipor_0.4.7 +[76] cli_3.6.2 fansi_1.0.6 viridisLite_0.4.2 +[79] S4Arrays_1.0.6 dplyr_1.1.4 gtable_0.3.4 +[82] rintrojs_0.3.3 sass_0.4.8 digest_0.6.33 [85] ggrepel_0.9.4 farver_2.1.1 rjson_0.2.21 -[88] htmlwidgets_1.6.2 htmltools_0.5.7 lifecycle_1.0.3 +[88] htmlwidgets_1.6.4 htmltools_0.5.7 lifecycle_1.0.4 [91] shinyWidgets_0.8.0 GlobalOptions_0.1.2 mime_0.12
Differential expression analysis
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -1025,7 +1025,7 @@Key Points
Extra exploration of design matrices
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -657,7 +657,7 @@Challenge
Show me the solution
-+R @@ -744,7 +744,7 @@
Challenge
Show me the solution
-+Gene set enrichment analysis
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -842,9 +842,9 @@ROUTPUT
+ expr min lq mean median uq max neval + fisher 238.455 241.8405 250.98679 244.1705 251.2475 552.429 100 + hyper 1.332 1.5180 2.38207 2.5445 2.8055 17.983 100Unit: microseconds - expr min lq mean median uq max neval - fisher 238.465 243.715 252.68149 246.8705 252.3760 488.411 100 - hyper 1.352 1.543 2.23699 2.5545 2.8355 5.901 100
It is very astonishing that
phyper()
is hundreds of times faster thanfisher.test()
. Main reason is in @@ -1001,7 +1001,7 @@Challenge
Show me the solution
-+R @@ -1625,7 +1625,7 @@
OUTPUT<
OUTPUT
-
+--> Expected input gene ID: 76867,320214,23797,110355,217011,103583
--> Expected input gene ID: 20317,622554,21681,105988,67000,239731
OUTPUT @@ -1896,12 +1896,12 @@
OUTPUT< mmu04913 Ovarian steroidogenesis - Mus musculus (house mouse) mmu04061 Viral protein interaction with cytokine and cytokine receptor - Mus musculus (house mouse) GeneRatio BgRatio pvalue p.adjust qvalue -mmu00590 16/454 85/9392 2.456998e-06 0.0007542983 0.0006620963 -mmu00565 11/454 48/9392 1.327107e-05 0.0014975168 0.0013144670 -mmu00592 8/454 25/9392 1.463371e-05 0.0014975168 0.0013144670 -mmu00591 11/454 50/9392 2.009867e-05 0.0015425732 0.0013540159 -mmu04913 12/454 63/9392 3.956222e-05 0.0024291201 0.0021321953 -mmu04061 14/454 95/9392 1.740468e-04 0.0079696743 0.0069954967 +mmu00590 16/454 85/9408 2.403809e-06 0.0007379694 0.0006452329 +mmu00565 11/454 48/9408 1.306159e-05 0.0014791271 0.0012932536 +mmu00592 8/454 25/9408 1.445401e-05 0.0014791271 0.0012932536 +mmu00591 11/454 50/9408 1.978440e-05 0.0015184527 0.0013276373 +mmu04913 12/454 63/9408 3.891349e-05 0.0023892882 0.0020890399 +mmu04061 14/454 95/9408 1.710081e-04 0.0078109667 0.0068294068 geneID mmu00590 18783/19215/211429/329502/78390/19223/67103/242546/13118/18781/18784/11689/232889/15446/237625/11687 mmu00565 18783/211429/329502/78390/22239/18781/18784/232889/320981/237625/53897 @@ -2647,7 +2647,7 @@
Key Points
Next steps
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -433,7 +433,7 @@Key Points
Contributor Code of Conduct
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -346,7 +346,7 @@Contributor Code of Conduct
"url": "https://carpentries-incubator.github.io/bioc-rnaseq/CODE_OF_CONDUCT.html", "identifier": "https://carpentries-incubator.github.io/bioc-rnaseq/CODE_OF_CONDUCT.html", "dateCreated": "2020-09-15", - "dateModified": "2023-11-21", + "dateModified": "2024-01-02", "datePublished": "2024-01-02" } diff --git a/LICENSE.html b/LICENSE.html index 5492e03c..576527ec 100644 --- a/LICENSE.html +++ b/LICENSE.html @@ -271,7 +271,7 @@Licenses
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -397,7 +397,7 @@Licenses
"url": "https://carpentries-incubator.github.io/bioc-rnaseq/LICENSE.html", "identifier": "https://carpentries-incubator.github.io/bioc-rnaseq/LICENSE.html", "dateCreated": "2020-09-15", - "dateModified": "2023-11-21", + "dateModified": "2024-01-02", "datePublished": "2024-01-02" } diff --git a/aio.html b/aio.html index b97dfa46..548329a1 100644 --- a/aio.html +++ b/aio.html @@ -335,7 +335,7 @@Content from Introduction to RNA-seq
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -682,7 +682,7 @@Key Points
Content from RStudio Project and Experimental Data
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -1023,7 +1023,7 @@Key Points
Content from Importing and annotating quantified data into R
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -1264,7 +1264,7 @@Challenge: Discuss the following points with -
+- In
counts
, the rows are genes just like the rows in @@ -1391,7 +1391,7 @@Challenge
Show me the solution
-+R @@ -1770,7 +1770,7 @@
Challenge
Show me the solution
-+R @@ -1899,7 +1899,7 @@
Challenge: How to subset to mRNA genes
Show me the solution
-+R @@ -2090,23 +2090,23 @@
OUTPUT< [1] hgu95av2.db_3.13.0 org.Hs.eg.db_3.17.0 [3] org.Mm.eg.db_3.17.0 AnnotationDbi_1.62.2 [5] SummarizedExperiment_1.30.2 Biobase_2.60.0 - [7] MatrixGenerics_1.12.3 matrixStats_1.0.0 + [7] MatrixGenerics_1.12.3 matrixStats_1.2.0 [9] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4 [11] IRanges_2.34.1 S4Vectors_0.38.2 [13] BiocGenerics_0.46.0 knitr_1.45 loaded via a namespace (and not attached): - [1] Matrix_1.6-1.1 bit_4.0.5 highr_0.10 + [1] Matrix_1.6-4 bit_4.0.5 highr_0.10 [4] compiler_4.3.2 BiocManager_1.30.22 renv_1.0.3 [7] crayon_1.5.2 blob_1.2.4 Biostrings_2.68.1 [10] bitops_1.0-7 png_0.1-8 fastmap_1.1.1 -[13] yaml_2.3.7 lattice_0.22-5 R6_2.5.1 +[13] yaml_2.3.8 lattice_0.22-5 R6_2.5.1 [16] XVector_0.40.0 S4Arrays_1.0.6 DelayedArray_0.26.7 -[19] GenomeInfoDbData_1.2.10 DBI_1.1.3 rlang_1.1.2 +[19] GenomeInfoDbData_1.2.10 DBI_1.2.0 rlang_1.1.2 [22] KEGGREST_1.40.1 cachem_1.0.8 xfun_0.41 -[25] bit64_4.0.5 RSQLite_2.3.3 memoise_2.0.1 -[28] cli_3.6.1 zlibbioc_1.46.0 grid_4.3.2 -[31] vctrs_0.6.4 evaluate_0.23 abind_1.4-5 +[25] bit64_4.0.5 RSQLite_2.3.4 memoise_2.0.1 +[28] cli_3.6.2 zlibbioc_1.46.0 grid_4.3.2 +[31] vctrs_0.6.5 evaluate_0.23 abind_1.4-5 [34] RCurl_1.98-1.13 httr_1.4.7 pkgconfig_2.0.3 [37] tools_4.3.2
Key Points
Content from Exploratory analysis and quality control
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -2700,7 +2700,7 @@OUTPUT< [5] ComplexHeatmap_2.16.0 ggplot2_3.4.4 [7] vsn_3.68.0 DESeq2_1.40.2 [9] SummarizedExperiment_1.30.2 Biobase_2.60.0 -[11] MatrixGenerics_1.12.3 matrixStats_1.0.0 +[11] MatrixGenerics_1.12.3 matrixStats_1.2.0 [13] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4 [15] IRanges_2.34.1 S4Vectors_0.38.2 [17] BiocGenerics_0.46.0 @@ -2708,34 +2708,34 @@
OUTPUT< loaded via a namespace (and not attached): [1] bitops_1.0-7 rlang_1.1.2 magrittr_2.0.3 [4] shinydashboard_0.7.2 clue_0.3-65 GetoptLong_1.0.5 - [7] compiler_4.3.2 mgcv_1.9-0 png_0.1-8 -[10] vctrs_0.6.4 pkgconfig_2.0.3 shape_1.4.6 + [7] compiler_4.3.2 mgcv_1.9-1 png_0.1-8 +[10] vctrs_0.6.5 pkgconfig_2.0.3 shape_1.4.6 [13] crayon_1.5.2 fastmap_1.1.1 XVector_0.40.0 [16] ellipsis_0.3.2 labeling_0.4.3 utf8_1.2.4 [19] promises_1.2.1 preprocessCore_1.62.1 shinyAce_0.4.2 [22] xfun_0.41 cachem_1.0.8 zlibbioc_1.46.0 -[25] jsonlite_1.8.7 highr_0.10 later_1.3.1 +[25] jsonlite_1.8.8 highr_0.10 later_1.3.2 [28] DelayedArray_0.26.7 BiocParallel_1.34.2 parallel_4.3.2 -[31] cluster_2.1.4 R6_2.5.1 bslib_0.5.1 +[31] cluster_2.1.6 R6_2.5.1 bslib_0.6.1 [34] limma_3.56.2 jquerylib_0.1.4 Rcpp_1.0.11 -[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.12 -[40] Matrix_1.6-1.1 splines_4.3.2 igraph_1.5.1 -[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.7 +[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.13 +[40] Matrix_1.6-4 splines_4.3.2 igraph_1.6.0 +[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.8 [46] doParallel_1.0.17 codetools_0.2-19 affy_1.78.2 [49] miniUI_0.1.1.1 lattice_0.22-5 tibble_3.2.1 -[52] shiny_1.7.5.1 withr_2.5.2 evaluate_0.23 +[52] shiny_1.8.0 withr_2.5.2 evaluate_0.23 [55] circlize_0.4.15 pillar_1.9.0 affyio_1.70.0 -[58] BiocManager_1.30.22 renv_1.0.3 DT_0.30 +[58] BiocManager_1.30.22 renv_1.0.3 DT_0.31 [61] foreach_1.5.2 shinyjs_2.1.0 generics_0.1.3 -[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.2.1 +[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.3.0 [67] xtable_1.8-4 glue_1.6.2 tools_4.3.2 [70] colourpicker_1.3.0 locfit_1.5-9.8 colorspace_2.1-0 -[73] nlme_3.1-163 GenomeInfoDbData_1.2.10 vipor_0.4.5 -[76] cli_3.6.1 fansi_1.0.5 viridisLite_0.4.2 -[79] S4Arrays_1.0.6 dplyr_1.1.3 gtable_0.3.4 -[82] rintrojs_0.3.3 sass_0.4.7 digest_0.6.33 +[73] nlme_3.1-164 GenomeInfoDbData_1.2.10 vipor_0.4.7 +[76] cli_3.6.2 fansi_1.0.6 viridisLite_0.4.2 +[79] S4Arrays_1.0.6 dplyr_1.1.4 gtable_0.3.4 +[82] rintrojs_0.3.3 sass_0.4.8 digest_0.6.33 [85] ggrepel_0.9.4 farver_2.1.1 rjson_0.2.21 -[88] htmlwidgets_1.6.2 htmltools_0.5.7 lifecycle_1.0.3 +[88] htmlwidgets_1.6.4 htmltools_0.5.7 lifecycle_1.0.4 [91] shinyWidgets_0.8.0 GlobalOptions_0.1.2 mime_0.12
@@ -2760,7 +2760,7 @@Key Points
Content from Differential expression analysis
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -3460,7 +3460,7 @@Key Points
Content from Extra exploration of design matrices
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -3826,7 +3826,7 @@Challenge
Show me the solution
-+R @@ -3914,7 +3914,7 @@
Challenge
Show me the solution
-+R @@ -5127,7 +5127,7 @@
Key Points
Content from Gene set enrichment analysis
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -5724,9 +5724,9 @@ROUTPUT
+ expr min lq mean median uq max neval + fisher 238.455 241.8405 250.98679 244.1705 251.2475 552.429 100 + hyper 1.332 1.5180 2.38207 2.5445 2.8055 17.983 100Unit: microseconds - expr min lq mean median uq max neval - fisher 238.465 243.715 252.68149 246.8705 252.3760 488.411 100 - hyper 1.352 1.543 2.23699 2.5545 2.8355 5.901 100
It is very astonishing that
phyper()
is hundreds of times faster thanfisher.test()
. Main reason is in @@ -5886,7 +5886,7 @@Challenge
Show me the solution
-+R @@ -6545,7 +6545,7 @@
OUTPUT<
OUTPUT
-
+--> Expected input gene ID: 76867,320214,23797,110355,217011,103583
--> Expected input gene ID: 20317,622554,21681,105988,67000,239731
OUTPUT @@ -6823,12 +6823,12 @@
OUTPUT< mmu04913 Ovarian steroidogenesis - Mus musculus (house mouse) mmu04061 Viral protein interaction with cytokine and cytokine receptor - Mus musculus (house mouse) GeneRatio BgRatio pvalue p.adjust qvalue -mmu00590 16/454 85/9392 2.456998e-06 0.0007542983 0.0006620963 -mmu00565 11/454 48/9392 1.327107e-05 0.0014975168 0.0013144670 -mmu00592 8/454 25/9392 1.463371e-05 0.0014975168 0.0013144670 -mmu00591 11/454 50/9392 2.009867e-05 0.0015425732 0.0013540159 -mmu04913 12/454 63/9392 3.956222e-05 0.0024291201 0.0021321953 -mmu04061 14/454 95/9392 1.740468e-04 0.0079696743 0.0069954967 +mmu00590 16/454 85/9408 2.403809e-06 0.0007379694 0.0006452329 +mmu00565 11/454 48/9408 1.306159e-05 0.0014791271 0.0012932536 +mmu00592 8/454 25/9408 1.445401e-05 0.0014791271 0.0012932536 +mmu00591 11/454 50/9408 1.978440e-05 0.0015184527 0.0013276373 +mmu04913 12/454 63/9408 3.891349e-05 0.0023892882 0.0020890399 +mmu04061 14/454 95/9408 1.710081e-04 0.0078109667 0.0068294068 geneID mmu00590 18783/19215/211429/329502/78390/19223/67103/242546/13118/18781/18784/11689/232889/15446/237625/11687 mmu00565 18783/211429/329502/78390/22239/18781/18784/232889/320981/237625/53897 @@ -7549,7 +7549,7 @@
Key Points
Content from Next steps
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
diff --git a/discuss.html b/discuss.html index 90ba1cf1..86ecf245 100644 --- a/discuss.html +++ b/discuss.html @@ -271,7 +271,7 @@Discussion
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -339,7 +339,7 @@Discussion
"url": "https://carpentries-incubator.github.io/bioc-rnaseq/discuss.html", "identifier": "https://carpentries-incubator.github.io/bioc-rnaseq/discuss.html", "dateCreated": "2020-09-15", - "dateModified": "2023-11-21", + "dateModified": "2024-01-02", "datePublished": "2024-01-02" } diff --git a/fig/04-exploratory-qc-rendered-pca-exercise-1.png b/fig/04-exploratory-qc-rendered-pca-exercise-1.png index 3a80b3f2..25e565b8 100644 Binary files a/fig/04-exploratory-qc-rendered-pca-exercise-1.png and b/fig/04-exploratory-qc-rendered-pca-exercise-1.png differ diff --git a/fig/05-differential-expression-rendered-heatmap-time-1.png b/fig/05-differential-expression-rendered-heatmap-time-1.png index fcae0d16..7a365516 100644 Binary files a/fig/05-differential-expression-rendered-heatmap-time-1.png and b/fig/05-differential-expression-rendered-heatmap-time-1.png differ diff --git a/fig/07-gene-set-analysis-rendered-hypergeom-1.png b/fig/07-gene-set-analysis-rendered-hypergeom-1.png index 950e15f0..a02c0f23 100644 Binary files a/fig/07-gene-set-analysis-rendered-hypergeom-1.png and b/fig/07-gene-set-analysis-rendered-hypergeom-1.png differ diff --git a/instructor/01-intro-to-rnaseq.html b/instructor/01-intro-to-rnaseq.html index 67d1fd31..0307f54a 100644 --- a/instructor/01-intro-to-rnaseq.html +++ b/instructor/01-intro-to-rnaseq.html @@ -275,7 +275,7 @@Introduction to RNA-seq
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -663,7 +663,7 @@Key Points
RStudio Project and Experimental Data
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -655,7 +655,7 @@Key Points
Importing and annotating quantified data into R
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -526,7 +526,7 @@Challenge: Discuss the following points with -
+- In
counts
, the rows are genes just like the rows inrowranges
. The columns incounts
are the @@ -646,7 +646,7 @@Challenge
Show me the solution
-+R @@ -1023,7 +1023,7 @@
Challenge
Show me the solution
-+R @@ -1150,7 +1150,7 @@
Challenge: How to subset to mRNA genes
Show me the solution
-+R @@ -1334,23 +1334,23 @@
OUTPUT< [1] hgu95av2.db_3.13.0 org.Hs.eg.db_3.17.0 [3] org.Mm.eg.db_3.17.0 AnnotationDbi_1.62.2 [5] SummarizedExperiment_1.30.2 Biobase_2.60.0 - [7] MatrixGenerics_1.12.3 matrixStats_1.0.0 + [7] MatrixGenerics_1.12.3 matrixStats_1.2.0 [9] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4 [11] IRanges_2.34.1 S4Vectors_0.38.2 [13] BiocGenerics_0.46.0 knitr_1.45 loaded via a namespace (and not attached): - [1] Matrix_1.6-1.1 bit_4.0.5 highr_0.10 + [1] Matrix_1.6-4 bit_4.0.5 highr_0.10 [4] compiler_4.3.2 BiocManager_1.30.22 renv_1.0.3 [7] crayon_1.5.2 blob_1.2.4 Biostrings_2.68.1 [10] bitops_1.0-7 png_0.1-8 fastmap_1.1.1 -[13] yaml_2.3.7 lattice_0.22-5 R6_2.5.1 +[13] yaml_2.3.8 lattice_0.22-5 R6_2.5.1 [16] XVector_0.40.0 S4Arrays_1.0.6 DelayedArray_0.26.7 -[19] GenomeInfoDbData_1.2.10 DBI_1.1.3 rlang_1.1.2 +[19] GenomeInfoDbData_1.2.10 DBI_1.2.0 rlang_1.1.2 [22] KEGGREST_1.40.1 cachem_1.0.8 xfun_0.41 -[25] bit64_4.0.5 RSQLite_2.3.3 memoise_2.0.1 -[28] cli_3.6.1 zlibbioc_1.46.0 grid_4.3.2 -[31] vctrs_0.6.4 evaluate_0.23 abind_1.4-5 +[25] bit64_4.0.5 RSQLite_2.3.4 memoise_2.0.1 +[28] cli_3.6.2 zlibbioc_1.46.0 grid_4.3.2 +[31] vctrs_0.6.5 evaluate_0.23 abind_1.4-5 [34] RCurl_1.98-1.13 httr_1.4.7 pkgconfig_2.0.3 [37] tools_4.3.2
Key Points
Exploratory analysis and quality control
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -836,7 +836,7 @@OUTPUT< [5] ComplexHeatmap_2.16.0 ggplot2_3.4.4 [7] vsn_3.68.0 DESeq2_1.40.2 [9] SummarizedExperiment_1.30.2 Biobase_2.60.0 -[11] MatrixGenerics_1.12.3 matrixStats_1.0.0 +[11] MatrixGenerics_1.12.3 matrixStats_1.2.0 [13] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4 [15] IRanges_2.34.1 S4Vectors_0.38.2 [17] BiocGenerics_0.46.0 @@ -844,34 +844,34 @@
OUTPUT< loaded via a namespace (and not attached): [1] bitops_1.0-7 rlang_1.1.2 magrittr_2.0.3 [4] shinydashboard_0.7.2 clue_0.3-65 GetoptLong_1.0.5 - [7] compiler_4.3.2 mgcv_1.9-0 png_0.1-8 -[10] vctrs_0.6.4 pkgconfig_2.0.3 shape_1.4.6 + [7] compiler_4.3.2 mgcv_1.9-1 png_0.1-8 +[10] vctrs_0.6.5 pkgconfig_2.0.3 shape_1.4.6 [13] crayon_1.5.2 fastmap_1.1.1 XVector_0.40.0 [16] ellipsis_0.3.2 labeling_0.4.3 utf8_1.2.4 [19] promises_1.2.1 preprocessCore_1.62.1 shinyAce_0.4.2 [22] xfun_0.41 cachem_1.0.8 zlibbioc_1.46.0 -[25] jsonlite_1.8.7 highr_0.10 later_1.3.1 +[25] jsonlite_1.8.8 highr_0.10 later_1.3.2 [28] DelayedArray_0.26.7 BiocParallel_1.34.2 parallel_4.3.2 -[31] cluster_2.1.4 R6_2.5.1 bslib_0.5.1 +[31] cluster_2.1.6 R6_2.5.1 bslib_0.6.1 [34] limma_3.56.2 jquerylib_0.1.4 Rcpp_1.0.11 -[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.12 -[40] Matrix_1.6-1.1 splines_4.3.2 igraph_1.5.1 -[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.7 +[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.13 +[40] Matrix_1.6-4 splines_4.3.2 igraph_1.6.0 +[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.8 [46] doParallel_1.0.17 codetools_0.2-19 affy_1.78.2 [49] miniUI_0.1.1.1 lattice_0.22-5 tibble_3.2.1 -[52] shiny_1.7.5.1 withr_2.5.2 evaluate_0.23 +[52] shiny_1.8.0 withr_2.5.2 evaluate_0.23 [55] circlize_0.4.15 pillar_1.9.0 affyio_1.70.0 -[58] BiocManager_1.30.22 renv_1.0.3 DT_0.30 +[58] BiocManager_1.30.22 renv_1.0.3 DT_0.31 [61] foreach_1.5.2 shinyjs_2.1.0 generics_0.1.3 -[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.2.1 +[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.3.0 [67] xtable_1.8-4 glue_1.6.2 tools_4.3.2 [70] colourpicker_1.3.0 locfit_1.5-9.8 colorspace_2.1-0 -[73] nlme_3.1-163 GenomeInfoDbData_1.2.10 vipor_0.4.5 -[76] cli_3.6.1 fansi_1.0.5 viridisLite_0.4.2 -[79] S4Arrays_1.0.6 dplyr_1.1.3 gtable_0.3.4 -[82] rintrojs_0.3.3 sass_0.4.7 digest_0.6.33 +[73] nlme_3.1-164 GenomeInfoDbData_1.2.10 vipor_0.4.7 +[76] cli_3.6.2 fansi_1.0.6 viridisLite_0.4.2 +[79] S4Arrays_1.0.6 dplyr_1.1.4 gtable_0.3.4 +[82] rintrojs_0.3.3 sass_0.4.8 digest_0.6.33 [85] ggrepel_0.9.4 farver_2.1.1 rjson_0.2.21 -[88] htmlwidgets_1.6.2 htmltools_0.5.7 lifecycle_1.0.3 +[88] htmlwidgets_1.6.4 htmltools_0.5.7 lifecycle_1.0.4 [91] shinyWidgets_0.8.0 GlobalOptions_0.1.2 mime_0.12
Differential expression analysis
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -1092,7 +1092,7 @@Key Points
Extra exploration of design matrices
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -659,7 +659,7 @@Challenge
Show me the solution
-+R @@ -746,7 +746,7 @@
Challenge
Show me the solution
-+Gene set enrichment analysis
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -844,9 +844,9 @@ROUTPUT
+ expr min lq mean median uq max neval + fisher 238.455 241.8405 250.98679 244.1705 251.2475 552.429 100 + hyper 1.332 1.5180 2.38207 2.5445 2.8055 17.983 100Unit: microseconds - expr min lq mean median uq max neval - fisher 238.465 243.715 252.68149 246.8705 252.3760 488.411 100 - hyper 1.352 1.543 2.23699 2.5545 2.8355 5.901 100
It is very astonishing that
phyper()
is hundreds of times faster thanfisher.test()
. Main reason is in @@ -1003,7 +1003,7 @@Challenge
Show me the solution
-+R @@ -1627,7 +1627,7 @@
OUTPUT<
OUTPUT
-
+--> Expected input gene ID: 76867,320214,23797,110355,217011,103583
--> Expected input gene ID: 20317,622554,21681,105988,67000,239731
OUTPUT @@ -1898,12 +1898,12 @@
OUTPUT< mmu04913 Ovarian steroidogenesis - Mus musculus (house mouse) mmu04061 Viral protein interaction with cytokine and cytokine receptor - Mus musculus (house mouse) GeneRatio BgRatio pvalue p.adjust qvalue -mmu00590 16/454 85/9392 2.456998e-06 0.0007542983 0.0006620963 -mmu00565 11/454 48/9392 1.327107e-05 0.0014975168 0.0013144670 -mmu00592 8/454 25/9392 1.463371e-05 0.0014975168 0.0013144670 -mmu00591 11/454 50/9392 2.009867e-05 0.0015425732 0.0013540159 -mmu04913 12/454 63/9392 3.956222e-05 0.0024291201 0.0021321953 -mmu04061 14/454 95/9392 1.740468e-04 0.0079696743 0.0069954967 +mmu00590 16/454 85/9408 2.403809e-06 0.0007379694 0.0006452329 +mmu00565 11/454 48/9408 1.306159e-05 0.0014791271 0.0012932536 +mmu00592 8/454 25/9408 1.445401e-05 0.0014791271 0.0012932536 +mmu00591 11/454 50/9408 1.978440e-05 0.0015184527 0.0013276373 +mmu04913 12/454 63/9408 3.891349e-05 0.0023892882 0.0020890399 +mmu04061 14/454 95/9408 1.710081e-04 0.0078109667 0.0068294068 geneID mmu00590 18783/19215/211429/329502/78390/19223/67103/242546/13118/18781/18784/11689/232889/15446/237625/11687 mmu00565 18783/211429/329502/78390/22239/18781/18784/232889/320981/237625/53897 @@ -2649,7 +2649,7 @@
Key Points
Next steps
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -435,7 +435,7 @@Key Points
Contributor Code of Conduct
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -348,7 +348,7 @@Contributor Code of Conduct
"url": "https://carpentries-incubator.github.io/bioc-rnaseq/instructor/CODE_OF_CONDUCT.html", "identifier": "https://carpentries-incubator.github.io/bioc-rnaseq/instructor/CODE_OF_CONDUCT.html", "dateCreated": "2020-09-15", - "dateModified": "2023-11-21", + "dateModified": "2024-01-02", "datePublished": "2024-01-02" } diff --git a/instructor/LICENSE.html b/instructor/LICENSE.html index e3f22897..82c00c92 100644 --- a/instructor/LICENSE.html +++ b/instructor/LICENSE.html @@ -271,7 +271,7 @@Licenses
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
@@ -399,7 +399,7 @@Licenses
"url": "https://carpentries-incubator.github.io/bioc-rnaseq/instructor/LICENSE.html", "identifier": "https://carpentries-incubator.github.io/bioc-rnaseq/instructor/LICENSE.html", "dateCreated": "2020-09-15", - "dateModified": "2023-11-21", + "dateModified": "2024-01-02", "datePublished": "2024-01-02" } diff --git a/instructor/aio.html b/instructor/aio.html index 79c38c27..a3ce2f48 100644 --- a/instructor/aio.html +++ b/instructor/aio.html @@ -337,7 +337,7 @@Content from Introduction to RNA-seq
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
Estimated time 100 minutes
@@ -685,7 +685,7 @@Key Points
Content from RStudio Project and Experimental Data
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
Estimated time 30 minutes
@@ -1027,7 +1027,7 @@Key Points
Content from Importing and annotating quantified data into R
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
Estimated time 120 minutes
@@ -1269,7 +1269,7 @@Challenge: Discuss the following points with -
+- In
counts
, the rows are genes just like the rows in @@ -1396,7 +1396,7 @@Challenge
Show me the solution
-+R @@ -1775,7 +1775,7 @@
Challenge
Show me the solution
-+R @@ -1904,7 +1904,7 @@
Challenge: How to subset to mRNA genes
Show me the solution
-+R @@ -2095,23 +2095,23 @@
OUTPUT< [1] hgu95av2.db_3.13.0 org.Hs.eg.db_3.17.0 [3] org.Mm.eg.db_3.17.0 AnnotationDbi_1.62.2 [5] SummarizedExperiment_1.30.2 Biobase_2.60.0 - [7] MatrixGenerics_1.12.3 matrixStats_1.0.0 + [7] MatrixGenerics_1.12.3 matrixStats_1.2.0 [9] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4 [11] IRanges_2.34.1 S4Vectors_0.38.2 [13] BiocGenerics_0.46.0 knitr_1.45 loaded via a namespace (and not attached): - [1] Matrix_1.6-1.1 bit_4.0.5 highr_0.10 + [1] Matrix_1.6-4 bit_4.0.5 highr_0.10 [4] compiler_4.3.2 BiocManager_1.30.22 renv_1.0.3 [7] crayon_1.5.2 blob_1.2.4 Biostrings_2.68.1 [10] bitops_1.0-7 png_0.1-8 fastmap_1.1.1 -[13] yaml_2.3.7 lattice_0.22-5 R6_2.5.1 +[13] yaml_2.3.8 lattice_0.22-5 R6_2.5.1 [16] XVector_0.40.0 S4Arrays_1.0.6 DelayedArray_0.26.7 -[19] GenomeInfoDbData_1.2.10 DBI_1.1.3 rlang_1.1.2 +[19] GenomeInfoDbData_1.2.10 DBI_1.2.0 rlang_1.1.2 [22] KEGGREST_1.40.1 cachem_1.0.8 xfun_0.41 -[25] bit64_4.0.5 RSQLite_2.3.3 memoise_2.0.1 -[28] cli_3.6.1 zlibbioc_1.46.0 grid_4.3.2 -[31] vctrs_0.6.4 evaluate_0.23 abind_1.4-5 +[25] bit64_4.0.5 RSQLite_2.3.4 memoise_2.0.1 +[28] cli_3.6.2 zlibbioc_1.46.0 grid_4.3.2 +[31] vctrs_0.6.5 evaluate_0.23 abind_1.4-5 [34] RCurl_1.98-1.13 httr_1.4.7 pkgconfig_2.0.3 [37] tools_4.3.2
Key Points
Content from Exploratory analysis and quality control
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
Estimated time 180 minutes
@@ -2706,7 +2706,7 @@OUTPUT< [5] ComplexHeatmap_2.16.0 ggplot2_3.4.4 [7] vsn_3.68.0 DESeq2_1.40.2 [9] SummarizedExperiment_1.30.2 Biobase_2.60.0 -[11] MatrixGenerics_1.12.3 matrixStats_1.0.0 +[11] MatrixGenerics_1.12.3 matrixStats_1.2.0 [13] GenomicRanges_1.52.1 GenomeInfoDb_1.36.4 [15] IRanges_2.34.1 S4Vectors_0.38.2 [17] BiocGenerics_0.46.0 @@ -2714,34 +2714,34 @@
OUTPUT< loaded via a namespace (and not attached): [1] bitops_1.0-7 rlang_1.1.2 magrittr_2.0.3 [4] shinydashboard_0.7.2 clue_0.3-65 GetoptLong_1.0.5 - [7] compiler_4.3.2 mgcv_1.9-0 png_0.1-8 -[10] vctrs_0.6.4 pkgconfig_2.0.3 shape_1.4.6 + [7] compiler_4.3.2 mgcv_1.9-1 png_0.1-8 +[10] vctrs_0.6.5 pkgconfig_2.0.3 shape_1.4.6 [13] crayon_1.5.2 fastmap_1.1.1 XVector_0.40.0 [16] ellipsis_0.3.2 labeling_0.4.3 utf8_1.2.4 [19] promises_1.2.1 preprocessCore_1.62.1 shinyAce_0.4.2 [22] xfun_0.41 cachem_1.0.8 zlibbioc_1.46.0 -[25] jsonlite_1.8.7 highr_0.10 later_1.3.1 +[25] jsonlite_1.8.8 highr_0.10 later_1.3.2 [28] DelayedArray_0.26.7 BiocParallel_1.34.2 parallel_4.3.2 -[31] cluster_2.1.4 R6_2.5.1 bslib_0.5.1 +[31] cluster_2.1.6 R6_2.5.1 bslib_0.6.1 [34] limma_3.56.2 jquerylib_0.1.4 Rcpp_1.0.11 -[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.12 -[40] Matrix_1.6-1.1 splines_4.3.2 igraph_1.5.1 -[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.7 +[37] iterators_1.0.14 knitr_1.45 httpuv_1.6.13 +[40] Matrix_1.6-4 splines_4.3.2 igraph_1.6.0 +[43] tidyselect_1.2.0 abind_1.4-5 yaml_2.3.8 [46] doParallel_1.0.17 codetools_0.2-19 affy_1.78.2 [49] miniUI_0.1.1.1 lattice_0.22-5 tibble_3.2.1 -[52] shiny_1.7.5.1 withr_2.5.2 evaluate_0.23 +[52] shiny_1.8.0 withr_2.5.2 evaluate_0.23 [55] circlize_0.4.15 pillar_1.9.0 affyio_1.70.0 -[58] BiocManager_1.30.22 renv_1.0.3 DT_0.30 +[58] BiocManager_1.30.22 renv_1.0.3 DT_0.31 [61] foreach_1.5.2 shinyjs_2.1.0 generics_0.1.3 -[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.2.1 +[64] RCurl_1.98-1.13 munsell_0.5.0 scales_1.3.0 [67] xtable_1.8-4 glue_1.6.2 tools_4.3.2 [70] colourpicker_1.3.0 locfit_1.5-9.8 colorspace_2.1-0 -[73] nlme_3.1-163 GenomeInfoDbData_1.2.10 vipor_0.4.5 -[76] cli_3.6.1 fansi_1.0.5 viridisLite_0.4.2 -[79] S4Arrays_1.0.6 dplyr_1.1.3 gtable_0.3.4 -[82] rintrojs_0.3.3 sass_0.4.7 digest_0.6.33 +[73] nlme_3.1-164 GenomeInfoDbData_1.2.10 vipor_0.4.7 +[76] cli_3.6.2 fansi_1.0.6 viridisLite_0.4.2 +[79] S4Arrays_1.0.6 dplyr_1.1.4 gtable_0.3.4 +[82] rintrojs_0.3.3 sass_0.4.8 digest_0.6.33 [85] ggrepel_0.9.4 farver_2.1.1 rjson_0.2.21 -[88] htmlwidgets_1.6.2 htmltools_0.5.7 lifecycle_1.0.3 +[88] htmlwidgets_1.6.4 htmltools_0.5.7 lifecycle_1.0.4 [91] shinyWidgets_0.8.0 GlobalOptions_0.1.2 mime_0.12
@@ -2766,7 +2766,7 @@Key Points
Content from Differential expression analysis
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
Estimated time 105 minutes
@@ -3532,7 +3532,7 @@Key Points
Content from Extra exploration of design matrices
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
Estimated time 60 minutes
@@ -3899,7 +3899,7 @@Challenge
Show me the solution
-+R @@ -3987,7 +3987,7 @@
Challenge
Show me the solution
-+R @@ -5200,7 +5200,7 @@
Key Points
Content from Gene set enrichment analysis
-Last updated on 2023-11-21 | +
Last updated on 2024-01-02 | Edit this page
Estimated time 105 minutes
@@ -5798,9 +5798,9 @@ROUTPUT
+ expr min lq mean median uq max neval + fisher 238.455 241.8405 250.98679 244.1705 251.2475 552.429 100 + hyper 1.332 1.5180 2.38207 2.5445 2.8055 17.983 100Unit: microseconds - expr min lq mean median uq max neval - fisher 238.465 243.715 252.68149 246.8705 252.3760 488.411 100 - hyper 1.352 1.543 2.23699 2.5545 2.8355 5.901 100
It is very astonishing that
phyper()
is hundreds of times faster thanfisher.test()
. Main reason is in @@ -5960,7 +5960,7 @@Challenge
Show me the solution
-+R @@ -6619,7 +6619,7 @@
OUTPUT<
OUTPUT
-
+--> Expected input gene ID: 76867,320214,23797,110355,217011,103583
--> Expected input gene ID: 20317,622554,21681,105988,67000,239731
OUTPUT @@ -6897,12 +6897,12 @@
OUTPUT< mmu04913 Ovarian steroidogenesis - Mus musculus (house mouse) mmu04061 Viral protein interaction with cytokine and cytokine receptor - Mus musculus (house mouse) GeneRatio BgRatio pvalue p.adjust qvalue -mmu00590 16/454 85/9392 2.456998e-06 0.0007542983 0.0006620963 -mmu00565 11/454 48/9392 1.327107e-05 0.0014975168 0.0013144670 -mmu00592 8/454 25/9392 1.463371e-05 0.0014975168 0.0013144670 -mmu00591 11/454 50/9392 2.009867e-05 0.0015425732 0.0013540159 -mmu04913 12/454 63/9392 3.956222e-05 0.0024291201 0.0021321953 -mmu04061 14/454 95/9392 1.740468e-04 0.0079696743 0.0069954967 +mmu00590 16/454 85/9408 2.403809e-06 0.0007379694 0.0006452329 +mmu00565 11/454 48/9408 1.306159e-05 0.0014791271 0.0012932536 +mmu00592 8/454 25/9408 1.445401e-05 0.0014791271 0.0012932536 +mmu00591 11/454 50/9408 1.978440e-05 0.0015184527 0.0013276373 +mmu04913 12/454 63/9408 3.891349e-05 0.0023892882 0.0020890399 +mmu04061 14/454 95/9408 1.710081e-04 0.0078109667 0.0068294068 geneID mmu00590 18783/19215/211429/329502/78390/19223/67103/242546/13118/18781/18784/11689/232889/15446/237625/11687 mmu00565 18783/211429/329502/78390/22239/18781/18784/232889/320981/237625/53897 @@ -7623,7 +7623,7 @@
Key Points
Content from
- In
- In
- In