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dinithins committed Apr 18, 2024
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20 changes: 20 additions & 0 deletions doc/.ipynb_checkpoints/Makefile-checkpoint
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# Minimal makefile for Sphinx documentation
#

# You can set these variables from the command line, and also
# from the environment for the first two.
SPHINXOPTS ?=
SPHINXBUILD ?= sphinx-build
SOURCEDIR = source
BUILDDIR = build

# Put it first so that "make" without argument is like "make help".
help:
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

.PHONY: help Makefile

# Catch-all target: route all unknown targets to Sphinx using the new
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
%: Makefile
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
35 changes: 35 additions & 0 deletions doc/.ipynb_checkpoints/make-checkpoint.bat
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@ECHO OFF

pushd %~dp0

REM Command file for Sphinx documentation

if "%SPHINXBUILD%" == "" (
set SPHINXBUILD=sphinx-build
)
set SOURCEDIR=source
set BUILDDIR=build

if "%1" == "" goto help

%SPHINXBUILD% >NUL 2>NUL
if errorlevel 9009 (
echo.
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
echo.installed, then set the SPHINXBUILD environment variable to point
echo.to the full path of the 'sphinx-build' executable. Alternatively you
echo.may add the Sphinx directory to PATH.
echo.
echo.If you don't have Sphinx installed, grab it from
echo.http://sphinx-doc.org/
exit /b 1
)

%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
goto end

:help
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%

:end
popd
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2 changes: 1 addition & 1 deletion doc/build/html/.buildinfo
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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: 6e59a27ad7a662760f493dfdc52ce191
config: 2d92bab5530a9992afd79242fd06b61f
tags: 645f666f9bcd5a90fca523b33c5a78b7
57 changes: 31 additions & 26 deletions doc/build/html/.ipynb_checkpoints/index-checkpoint.html
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<meta charset="utf-8" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />

<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Genes2Genes &mdash; Genes2Genes v1.0 documentation</title>
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<title>Genes2Genes &mdash; Genes2Genes v0.2.0 documentation</title>
<link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=80d5e7a1" />
<link rel="stylesheet" type="text/css" href="../_static/css/theme.css?v=19f00094" />


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<script src="_static/doctools.js?v=888ff710"></script>
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<script src="_static/js/theme.js"></script>
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<script src="../_static/jquery.js?v=5d32c60e"></script>
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<script src="../_static/doctools.js?v=888ff710"></script>
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</head>

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<a href="#" class="icon icon-home">
<a href="../index.html" class="icon icon-home">
Genes2Genes
</a>
<div role="search">
<form id="rtd-search-form" class="wy-form" action="search.html" method="get">
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<ul>
<li class="toctree-l1"><a class="reference internal" href="../index.html">Genes2Genes</a></li>
</ul>

</div>
Expand All @@ -53,17 +52,17 @@

<section data-toggle="wy-nav-shift" class="wy-nav-content-wrap"><nav class="wy-nav-top" aria-label="Mobile navigation menu" >
<i data-toggle="wy-nav-top" class="fa fa-bars"></i>
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<hr/>
Expand All @@ -86,6 +85,7 @@ <h1><a class="toc-backref" href="#id1" role="doc-backlink">Genes2Genes</a><a cla
</li>
<li><p><a class="reference internal" href="#getting-started" id="id5">Getting started</a></p></li>
<li><p><a class="reference internal" href="#citing-genes2genes" id="id6">Citing Genes2Genes</a></p></li>
<li><p><a class="reference internal" href="#funding-acknowledgement" id="id7">Funding Acknowledgement</a></p></li>
</ul>
</nav>
<p>Genes2Genes (G2G) is a new Python framework for aligning single-cell pseudotime trajectories of gene expression between any reference and query for a pairwise comparison such as:</p>
Expand All @@ -99,14 +99,14 @@ <h1><a class="toc-backref" href="#id1" role="doc-backlink">Genes2Genes</a><a cla
<section id="trajectory-alignment-what-why">
<h2><a class="toc-backref" href="#id2" role="doc-backlink">Trajectory alignment: What &amp; Why?</a><a class="headerlink" href="#trajectory-alignment-what-why" title="Permalink to this heading"></a></h2>
<p>A single-cell trajectory describes the transcriptomic state of cells along some axis of progression (such as time), due to undergoing some dynamic process (e.g. cell differentiation, treatment response, or disease infection). Given an scRNA-seq profile, there are various tools available today to infer such trajectory by estimating a pseudo ordering of the cells along an axis, commonly referred to as ‘pseudotime’. The pseudotime axis of a trajectory can be descritized to represent it as a sequence of discrete time points. Given two such discrete pseudotime sequences of two trajectories, a pairwise alignment between them defines a non-linear mapping between their time points. This mapping could have 1-to-1 matches as well as 1-to-many/many-to-1 matches (a.k.a warps) between the time points, while unmapping the time points which have significantly different transcriptomic states. Below is an example visualization of two cell differentiation trajectories.</p>
<a class="reference internal image-reference" href="_images/DocFigs1.png"><img alt="What is trajectory alignment?" class="align-center" src="_images/DocFigs1.png" style="width: 600px;" /></a>
<a class="reference internal image-reference" href=".ipynb_checkpoints/images/DocFigs1.png"><img alt="What is trajectory alignment?" class="align-center" src=".ipynb_checkpoints/images/DocFigs1.png" style="width: 600px;" /></a>
<p>For two trajectories representing single lineages as above, G2G generates an <strong>optimal pairwise trajectory alignment</strong> that captures the matches and mismatches between their time points in sequential order, allowing a user to quantify the degree of similarity between them.</p>
<a class="reference internal image-reference" href="_images/DocFigs1-1.png"><img alt="Example mapping" class="align-center" src="_images/DocFigs1-1.png" style="width: 600px;" /></a>
<a class="reference internal image-reference" href=".ipynb_checkpoints/images/DocFigs1-1.png"><img alt="Example mapping" class="align-center" src=".ipynb_checkpoints/images/DocFigs1-1.png" style="width: 600px;" /></a>
<div class="line-block">
<div class="line"><br /></div>
</div>
<p>G2G defines 5 different states of alignment between any two <strong>R</strong> and <strong>Q</strong> time points, corresponding to all possible match and mismatch states. They are: 1-to-1 match (<code class="docutils literal notranslate"><span class="pre">M</span></code>), 1-to-many match (<code class="docutils literal notranslate"><span class="pre">V</span></code>), many-to-1 match (<code class="docutils literal notranslate"><span class="pre">W</span></code>), insertion (<code class="docutils literal notranslate"><span class="pre">I</span></code>) and deletion (<code class="docutils literal notranslate"><span class="pre">D</span></code>). Here, <code class="docutils literal notranslate"><span class="pre">I</span></code> or <code class="docutils literal notranslate"><span class="pre">D</span></code> refer to a mismatched time point in Q or R, respectively. These states jointly cover the alignment states defined in classical dynamic time warping and biological sequence alignment.</p>
<a class="reference internal image-reference" href="_images/DocFigs1-3.png"><img alt="5 states of alignment" class="align-center" src="_images/DocFigs1-3.png" style="width: 600px;" /></a>
<a class="reference internal image-reference" href=".ipynb_checkpoints/images/DocFigs1-3.png"><img alt="5 states of alignment" class="align-center" src=".ipynb_checkpoints/images/DocFigs1-3.png" style="width: 600px;" /></a>
<div class="line-block">
<div class="line"><br /></div>
</div>
Expand All @@ -120,7 +120,7 @@ <h2><a class="toc-backref" href="#id2" role="doc-backlink">Trajectory alignment:
<h2><a class="toc-backref" href="#id3" role="doc-backlink">Outputs from Genes2Genes</a><a class="headerlink" href="#outputs-from-genes2genes" title="Permalink to this heading"></a></h2>
<p>Given an scRNA-seq dataset with their pseudotime estimates and a specified set of genes (e.g. all transcription factors, highly variable genes, biological/signaling pathway genes), G2G generates fully-descriptive alignments for each gene (i.e. <strong>gene-level alignment</strong>), as well as an average (aggregate) alignment (i.e. <strong>cell-level alignment</strong>) across all genes.</p>
<p>Below is an example gene-level alignment of the gene <em>JUNB</em> in T cell differentiation between a pan-fetal reference and an artificial thymic organoid system:</p>
<a class="reference internal image-reference" href="_images/DocFigs2.png"><img alt="Example gene-level alignment?" class="align-center" src="_images/DocFigs2.png" style="width: 600px;" /></a>
<a class="reference internal image-reference" href=".ipynb_checkpoints/images/DocFigs2.png"><img alt="Example gene-level alignment?" class="align-center" src=".ipynb_checkpoints/images/DocFigs2.png" style="width: 600px;" /></a>
<div class="line-block">
<div class="line"><br /></div>
</div>
Expand Down Expand Up @@ -160,12 +160,17 @@ <h1><a class="toc-backref" href="#id5" role="doc-backlink">Getting started</a><a
</ul>
<p>The user can estimate pseudotime of the cells in their datasets using any suitable method available (such as <a class="reference external" href="https://scanpy.readthedocs.io/en/stable/generated/scanpy.tl.dpt.html">Diffusion pseudotime</a>, <a class="reference external" href="https://github.com/dpeerlab/Palantir">Palantir</a>, <a class="reference external" href="https://pyro.ai/examples/gplvm.html">GPLVM</a>, <a class="reference external" href="http://cole-trapnell-lab.github.io/monocle-release/">Monocle</a> etc.).
For better visualisation and interpretation of the alignment results, we recommend the data to be annotated with their cell types (manually and/or using an automatic annotation tool such as <a class="reference external" href="https://www.celltypist.org">CellTypist</a>).</p>
<p>Please refer to our <a class="reference internal" href="G2Gtutorial.html"><span class="doc">Tutorial</span></a> for an example analysis between a reference and query dataset from literature.</p>
<p>Please refer to our <a class="reference external" href="https://github.com/Teichlab/Genes2Genes/blob/main/notebooks/Tutorial.ipynb">Tutorial</a> for an example analysis between a reference and query dataset from literature.</p>
</section>
<section id="citing-genes2genes">
<h1><a class="toc-backref" href="#id6" role="doc-backlink">Citing Genes2Genes</a><a class="headerlink" href="#citing-genes2genes" title="Permalink to this heading"></a></h1>
<p>Our manuscript is currently available as a <a class="reference external" href="https://doi.org/10.1101/2023.03.08.531713">preprint</a> at bioRxiv:</p>
<p><em>Sumanaweera, D., Suo, C., Cujba, A.M., Muraro, D., Dann, E., Polanski, K., Steemers, A.S., Lee, W., Oliver, A.J., Park, J.E. and Meyer, K.B., 2023.</em> <strong>Gene-level alignment of single cell trajectories informs the progression of in vitro T cell differentiation</strong>. <em>bioRxiv, pp.2023-03.</em></p>
<p><em>Sumanaweera, D., Suo, C., Cujba, A.M., Muraro, D., Dann, E., Polanski, K., Steemers, A.S., Lee, W., Oliver, A.J., Park, J.E. and Meyer, K.B., 2023.</em> <strong>Gene-level alignment of single cell trajectories</strong>. <em>bioRxiv, pp.2023-03.</em></p>
<p>This publication is part of the <a class="reference external" href="https://www.humancellatlas.org">Human Cell Atlas</a></p>
</section>
<section id="funding-acknowledgement">
<h1><a class="toc-backref" href="#id7" role="doc-backlink">Funding Acknowledgement</a><a class="headerlink" href="#funding-acknowledgement" title="Permalink to this heading"></a></h1>
<p>Marie Skłodowska-Curie grant agreement No: 101026506 (Marie Curie Individual Fellowship) under the European Union’s Horizon 2020 research and innovation programme; Wellcome Trust Ph.D. Fellowship for Clinicians; Wellcome Trust (WT206194); ERC Consolidator Grant (646794); Wellcome Sanger Institute’s Translation Committee Fund.</p>
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