docs

README.rst

@@ -42,12 +42,12 @@ GSEAPY is a python wrapper for **GSEA** and **Enrichr**.
 GSEAPY could be used for **RNA-seq, ChIP-seq, Microarry** data. It's used for convenient GO enrichments and produce **publishable quality figures** in python. 
 
 
-GSEAPY has five sub-commands available: ``gsea``, ``prerank``, ``single``, ``replot`` ``enrichr``.
+GSEAPY has five sub-commands available: ``gsea``, ``prerank``, ``ssgsea``, ``replot`` ``enrichr``.
 
 
 :gsea:    The ``gsea`` module produce `GSEA  <http://www.broadinstitute.org/cancer/software/gsea/wiki/index.php/Main_Page>`_ results.The input requries a txt file(FPKM, Expected Counts, TPM, et.al), a cls file, and gene_sets file in gmt format. 
 :prerank: The ``prerank`` module produce **Prerank tool** results.  The input expects a pre-ranked gene list dataset with correlation values, which in .rnk format, and gene_sets file in gmt format.  ``prerank`` module is an API to `GSEA` pre-rank tools.
-:single: The ``single`` module perform **single sample GSEA(ssGSEA)** analysis.  The input expects a gene list with expression values(same with ``.rnk`` file, and gene_sets file in gmt format. ssGSEA enrichment score for the gene set as described by `D. Barbie et al 2009 <http://www.nature.com/nature/journal/v462/n7269/abs/nature08460.html>`_.
+:ssgsea: The ``ssgsea`` module perform **single sample GSEA(ssGSEA)** analysis.  The input expects a gene list with expression values(same with ``.rnk`` file, and gene_sets file in gmt format. ssGSEA enrichment score for the gene set as described by `D. Barbie et al 2009 <http://www.nature.com/nature/journal/v462/n7269/abs/nature08460.html>`_.
 
 :replot: The ``replot`` module reproduce GSEA desktop version results.  The only input for GSEAPY is the location to ``GSEA`` Desktop output results.
 
@@ -221,8 +221,8 @@ For command line usage:
   # An example to run Prerank using gseapy prerank module
   $ gseapy prerank -r gsea_data.rnk -g gene_sets.gmt -o test
 
-  # An example to run ssGSEA using gseapy single module
-  $ gseapy single -d expression.txt -g gene_sets.gmt -o test
+  # An example to run ssGSEA using gseapy ssgsea module
+  $ gseapy ssgsea -d expression.txt -g gene_sets.gmt -o test
 
   # An example to use enrichr api
   # see details of -g below, -d  is optional
@@ -271,10 +271,8 @@ Run gseapy inside python console:
     gseapy.prerank(rnk=gene_ranked_dataframe, gene_sets='KEGG_2016', outdir='test')
 
     # using ssGSEA
-    from gseapy.gsea import SingleSampleGSEA
-    ssGSEA_dataframe = pd.DataFrame()
-    ss = SingleSampleGSEA(data=ssGSEA_dataframe, gene_sets='KEGG_2016', outdir='test')
-    ss.run()
+    gseapy.ssgsea(data=ssGSEA_dataframe, gene_sets='KEGG_2016', outdir='test')
+
 
 3. For ``enrichr`` , you could assign a list object or a txt file 
 

docs/_build/html/_sources/gseapy_example.rst.txt

@@ -33,7 +33,7 @@ Examples to walk through ``GSEApy`` and enrichr
 See all gseapy supported enrichr library names
 ==============================================
 
-Enrichr library could be used for ``call`` and ``prerank``, too
+Enrichr library could be used for ``gsea`` and ``prerank``, too
 
 .. code:: ipython3
 
@@ -137,15 +137,15 @@ i. Assign enrichr with gene list object
 
     # run gseapy
     # if you are only intrested in dataframe that enrichr returned, please set no_plot=True
-    enrichr_results = gp.enrichr(gene_list=glist, description='test_name', gene_sets='KEGG_2016',
+    enr = gp.enrichr(gene_list=glist, description='test_name', gene_sets='KEGG_2016',
                                  outdir='enrichr_kegg', cutoff=0.5, no_plot=False)
     # and provide a txt file for enrichr will also work
-    #enrichr_results = gp.enrichr(gene_list='./gene_list.txt', description='KEGG', 
+    #enr = gp.enrichr(gene_list='./gene_list.txt', description='KEGG', 
     #                             gene_sets='KEGG_2016', outdir='enrichr_kegg')
 
 .. code:: ipython3
 
-    enrichr_results.iloc[:5,:6]
+    enr.res2d.iloc[:5,:6]
 
 
 
@@ -848,7 +848,7 @@ You may also want to use gsea in command line
 5. Single Sample GSEA example
 =============================
 
-**Note: When you run ssGSEA, all genes names in your gene\_sets file
+**Note: When you run ssGSEA, all genes names in your gene_sets file
 should be found in your expression table**
 
 i. Assign ssgsea() with a txt file or a dataframe
@@ -1030,7 +1030,7 @@ ii. command line usage of single sample gsea
 
 .. code:: ipython3
 
-    !gseapy single -d ./temp.txt -g temp.gmt -o ssgsea_report2 -v 
+    !gseapy ssgsea -d ./temp.txt -g temp.gmt -o ssgsea_report2 -v 
 
 
 .. parsed-literal::

docs/_build/html/_sources/gseapy_tutorial.rst.txt

@@ -222,19 +222,19 @@ Or run inside python.
 
 
 
-Use ``single`` command, or :func:`ssgsea`
+Use ``ssgsea`` command, or :func:`ssgsea`
 ===============================================================
 
 
 .. code:: bash
  
-    gseapy single -d expression.txt -g gene_sets.gmt -o test
+    gseapy ssgsea -d expression.txt -g gene_sets.gmt -o test
 
 
 .. code:: python
 
     #ssGSEA
-    ss = ssgsea(data="expression.txt", gene_sets= "gene_sets.gmt", outdir='test')
+    gseapy.ssgsea(data="expression.txt", gene_sets= "gene_sets.gmt", outdir='test')
 
 
 

docs/_build/html/_sources/index.rst.txt

@@ -36,15 +36,15 @@ GSEAPY: Gene Set Enrichment Analysis in Python.
 GSEAPY is a python wrapper for **GSEA** and **Enrichr**. 
 --------------------------------------------------------------------------------------------
 
-GSEAPY has five subcommands: ``gsea``, ``prerank``, ``single``, ``replot`` ``enrichr``.
+GSEAPY has five subcommands: ``gsea``, ``prerank``, ``ssgsea``, ``replot`` ``enrichr``.
 
 1. The ``gsea`` module produce **GSEA** results.    
 The input requries a txt file(FPKM, Expected Counts, TPM, et.al), a cls file, and gene_sets file in gmt format. 
 
 2. The ``prerank`` module produce **Prerank tool** results.  
 The input expects a pre-ranked gene list dataset with correlation values, which in .rnk format, and gene_sets file in gmt format.  ``prerank`` module is an API to `GSEA` pre-rank tools.
 
-3. The ``single`` module perform **single sample GSEA(ssGSEA)** analysis.  
+3. The ``ssgsea`` module perform **single sample GSEA(ssGSEA)** analysis.  
 The input expects a gene list with expression values(same with ``.rnk`` file, and gene_sets file in gmt format. ssGSEA enrichment score for the gene set as described by `D. Barbie et al 2009 <http://www.nature.com/nature/journal/v462/n7269/abs/nature08460.html>`_.
 
 4. The ``replot`` module reproduce GSEA desktop version results.  
@@ -70,7 +70,7 @@ do gene set enrichment analysis in python. So, here is my reason:
 
 * **Running inside python interactive console without switch to R!!!**
 * User friendly for both wet and dry lab usrers.
-* Produce pubilishable figures.
+* Produce and reproduce pubilishable figures.
 * Perform batch jobs easy(using for loops).
 * Easy to use in bash shell or your  data analysis workflow, e.g. snakemake.  
 

docs/_build/html/_sources/run.rst.txt

@@ -110,15 +110,15 @@ To See help information of GSEAPY
    
    $ gseapy --help 
    
-    usage: gseapy [-h] [--version] {gsea,prerank,single,replot,enrichr} ...
+    usage: gseapy [-h] [--version] {gsea,prerank,ssgsea,replot,enrichr} ...
 
     gseapy -- Gene Set Enrichment Analysis in Python
 
     positional arguments:
-      {gsea,replot}
+      {gsea,prerank,ssgsea,replot,enrichr}
         gsea       Main GSEAPY Function: run GSEAPY instead of GSEA.
         prerank    Using pre-ranked tool to run GSEAPY.
-        single     Run Single Sample GSEA.
+        ssgsea     Run Single Sample GSEA.
         replot     Reproduce GSEA desktop figures.
         enrichr    Peform GSEA using enrichr API.
     optional arguments:
@@ -141,9 +141,12 @@ For command line options of each command, type: gseapy COMMAND -h
    # or
    $ gseapy prerank -h
    # or 
+   $ gseapy ssgsea -h
+   # or 
    $ gseapy enrichr -h
 
 
+
 							
 
 
@@ -152,17 +155,18 @@ Module APIs
 ---------------------
 
 
-.. autofunction:: replot()
-
-
 .. autofunction:: gsea()
 
 
 .. autofunction:: prerank()
 
+.. autofunction:: ssgsea()
+
 
 .. autofunction:: enrichr()
 
+.. autofunction:: replot()
+
 
 Algorithm 
 -------------------------

docs/_build/html/genindex.html

@@ -215,6 +215,8 @@ <h2 id="E">E</h2>
 </li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
+      <li><a href="run.html#gseapy.enrichr.Enrichr">Enrichr (class in gseapy.enrichr)</a>
+</li>
       <li><a href="run.html#gseapy.enrichr">enrichr() (in module gseapy)</a>
 
       <ul>
@@ -240,14 +242,12 @@ <h2 id="G">G</h2>
       <li><a href="run.html#gseapy.parser.gsea_edb_parser">gsea_edb_parser() (in module gseapy.parser)</a>
 </li>
       <li><a href="run.html#gseapy.parser.gsea_gmt_parser">gsea_gmt_parser() (in module gseapy.parser)</a>
-</li>
-      <li><a href="run.html#gseapy.plot.gsea_plot">gsea_plot() (in module gseapy.plot)</a>
 </li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="run.html#gseapy.algorithm.gsea_pval">gsea_pval() (in module gseapy.algorithm)</a>
+      <li><a href="run.html#gseapy.plot.gsea_plot">gsea_plot() (in module gseapy.plot)</a>
 </li>
-      <li><a href="run.html#gseapy.parser.gsea_rank_metric">gsea_rank_metric() (in module gseapy.parser)</a>
+      <li><a href="run.html#gseapy.algorithm.gsea_pval">gsea_pval() (in module gseapy.algorithm)</a>
 </li>
       <li><a href="run.html#gseapy.algorithm.gsea_significance">gsea_significance() (in module gseapy.algorithm)</a>
 </li>
@@ -300,6 +300,8 @@ <h2 id="R">R</h2>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="run.html#gseapy.replot">replot() (in module gseapy)</a>
+</li>
+      <li><a href="run.html#gseapy.enrichr.Enrichr.run">run() (gseapy.enrichr.Enrichr method)</a>
 </li>
   </ul></td>
 </tr></table>
@@ -308,6 +310,10 @@ <h2 id="S">S</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="run.html#gseapy.algorithm.shuffle_list">shuffle_list() (in module gseapy.algorithm)</a>
+</li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
+      <li><a href="run.html#gseapy.ssgsea">ssgsea() (in module gseapy)</a>
 </li>
   </ul></td>
 </tr></table>

docs/_build/html/gseapy_example.html

@@ -194,7 +194,7 @@ <h1>1. Load essential packages<a class="headerlink" href="#load-essential-packag
 </div>
 <div class="section" id="see-all-gseapy-supported-enrichr-library-names">
 <h1>See all gseapy supported enrichr library names<a class="headerlink" href="#see-all-gseapy-supported-enrichr-library-names" title="Permalink to this headline">¶</a></h1>
-<p>Enrichr library could be used for <code class="docutils literal"><span class="pre">call</span></code> and <code class="docutils literal"><span class="pre">prerank</span></code>, too</p>
+<p>Enrichr library could be used for <code class="docutils literal"><span class="pre">gsea</span></code> and <code class="docutils literal"><span class="pre">prerank</span></code>, too</p>
 <div class="highlight-default"><div class="highlight"><pre><span></span><span class="p">[</span><span class="s1">&#39;Achilles_fitness_decrease&#39;</span><span class="p">,</span>
  <span class="s1">&#39;Achilles_fitness_increase&#39;</span><span class="p">,</span>
  <span class="s1">&#39;Aging_Perturbations_from_GEO_down&#39;</span><span class="p">,</span>

docs/_build/html/gseapy_tutorial.html

@@ -102,7 +102,7 @@
 </ul>
 </li>
 <li class="toctree-l2"><a class="reference internal" href="#use-prerank-command-or-prerank">Use <code class="docutils literal"><span class="pre">prerank</span></code> Command, or <code class="docutils literal"><span class="pre">prerank()</span></code></a></li>
-<li class="toctree-l2"><a class="reference internal" href="#use-single-command-or-ssgsea">Use <code class="docutils literal"><span class="pre">single</span></code> command, or <code class="docutils literal"><span class="pre">ssgsea()</span></code></a></li>
+<li class="toctree-l2"><a class="reference internal" href="#use-ssgsea-command-or-ssgsea">Use <code class="docutils literal"><span class="pre">ssgsea</span></code> command, or <code class="docutils literal"><span class="pre">ssgsea()</span></code></a></li>
 <li class="toctree-l2"><a class="reference internal" href="#use-enrichr-command-or-enrichr">Use <code class="docutils literal"><span class="pre">enrichr</span></code> command, or <code class="docutils literal"><span class="pre">enrichr()</span></code></a></li>
 <li class="toctree-l2"><a class="reference internal" href="#use-replot-command-or-replot">Use <code class="docutils literal"><span class="pre">replot</span></code> Command, or <code class="docutils literal"><span class="pre">replot()</span></code></a></li>
 </ul>
@@ -347,13 +347,13 @@ <h2>Use <code class="docutils literal"><span class="pre">prerank</span></code> C
 </pre></div>
 </div>
 </div>
-<div class="section" id="use-single-command-or-ssgsea">
-<h2>Use <code class="docutils literal"><span class="pre">single</span></code> command, or <code class="xref py py-func docutils literal"><span class="pre">ssgsea()</span></code><a class="headerlink" href="#use-single-command-or-ssgsea" title="Permalink to this headline">¶</a></h2>
-<div class="code bash highlight-default"><div class="highlight"><pre><span></span><span class="n">gseapy</span> <span class="n">single</span> <span class="o">-</span><span class="n">d</span> <span class="n">expression</span><span class="o">.</span><span class="n">txt</span> <span class="o">-</span><span class="n">g</span> <span class="n">gene_sets</span><span class="o">.</span><span class="n">gmt</span> <span class="o">-</span><span class="n">o</span> <span class="n">test</span>
+<div class="section" id="use-ssgsea-command-or-ssgsea">
+<h2>Use <code class="docutils literal"><span class="pre">ssgsea</span></code> command, or <code class="xref py py-func docutils literal"><span class="pre">ssgsea()</span></code><a class="headerlink" href="#use-ssgsea-command-or-ssgsea" title="Permalink to this headline">¶</a></h2>
+<div class="code bash highlight-default"><div class="highlight"><pre><span></span><span class="n">gseapy</span> <span class="n">ssgsea</span> <span class="o">-</span><span class="n">d</span> <span class="n">expression</span><span class="o">.</span><span class="n">txt</span> <span class="o">-</span><span class="n">g</span> <span class="n">gene_sets</span><span class="o">.</span><span class="n">gmt</span> <span class="o">-</span><span class="n">o</span> <span class="n">test</span>
 </pre></div>
 </div>
 <div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="c1">#ssGSEA</span>
-<span class="n">ss</span> <span class="o">=</span> <span class="n">ssgsea</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s2">&quot;expression.txt&quot;</span><span class="p">,</span> <span class="n">gene_sets</span><span class="o">=</span> <span class="s2">&quot;gene_sets.gmt&quot;</span><span class="p">,</span> <span class="n">outdir</span><span class="o">=</span><span class="s1">&#39;test&#39;</span><span class="p">)</span>
+<span class="n">gseapy</span><span class="o">.</span><span class="n">ssgsea</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s2">&quot;expression.txt&quot;</span><span class="p">,</span> <span class="n">gene_sets</span><span class="o">=</span> <span class="s2">&quot;gene_sets.gmt&quot;</span><span class="p">,</span> <span class="n">outdir</span><span class="o">=</span><span class="s1">&#39;test&#39;</span><span class="p">)</span>
 </pre></div>
 </div>
 </div>

docs/_build/html/index.html

@@ -182,12 +182,12 @@ <h2>GSEAPY: Gene Set Enrichment Analysis in Python.<a class="headerlink" href="#
 </div>
 <div class="section" id="gseapy-is-a-python-wrapper-for-gsea-and-enrichr">
 <h2>GSEAPY is a python wrapper for <strong>GSEA</strong> and <strong>Enrichr</strong>.<a class="headerlink" href="#gseapy-is-a-python-wrapper-for-gsea-and-enrichr" title="Permalink to this headline">¶</a></h2>
-<p>GSEAPY has five subcommands: <code class="docutils literal"><span class="pre">gsea</span></code>, <code class="docutils literal"><span class="pre">prerank</span></code>, <code class="docutils literal"><span class="pre">single</span></code>, <code class="docutils literal"><span class="pre">replot</span></code> <code class="docutils literal"><span class="pre">enrichr</span></code>.</p>
+<p>GSEAPY has five subcommands: <code class="docutils literal"><span class="pre">gsea</span></code>, <code class="docutils literal"><span class="pre">prerank</span></code>, <code class="docutils literal"><span class="pre">ssgsea</span></code>, <code class="docutils literal"><span class="pre">replot</span></code> <code class="docutils literal"><span class="pre">enrichr</span></code>.</p>
 <p>1. The <code class="docutils literal"><span class="pre">gsea</span></code> module produce <strong>GSEA</strong> results.
 The input requries a txt file(FPKM, Expected Counts, TPM, et.al), a cls file, and gene_sets file in gmt format.</p>
 <p>2. The <code class="docutils literal"><span class="pre">prerank</span></code> module produce <strong>Prerank tool</strong> results.
 The input expects a pre-ranked gene list dataset with correlation values, which in .rnk format, and gene_sets file in gmt format.  <code class="docutils literal"><span class="pre">prerank</span></code> module is an API to <cite>GSEA</cite> pre-rank tools.</p>
-<p>3. The <code class="docutils literal"><span class="pre">single</span></code> module perform <strong>single sample GSEA(ssGSEA)</strong> analysis.
+<p>3. The <code class="docutils literal"><span class="pre">ssgsea</span></code> module perform <strong>single sample GSEA(ssGSEA)</strong> analysis.
 The input expects a gene list with expression values(same with <code class="docutils literal"><span class="pre">.rnk</span></code> file, and gene_sets file in gmt format. ssGSEA enrichment score for the gene set as described by <a class="reference external" href="http://www.nature.com/nature/journal/v462/n7269/abs/nature08460.html">D. Barbie et al 2009</a>.</p>
 <p>4. The <code class="docutils literal"><span class="pre">replot</span></code> module reproduce GSEA desktop version results.
 The only input for GSEAPY is the location to GSEA Desktop output results.</p>
@@ -205,7 +205,7 @@ <h2>Why GSEAPY<a class="headerlink" href="#why-gseapy" title="Permalink to this
 <ul class="simple">
 <li><strong>Running inside python interactive console without switch to R!!!</strong></li>
 <li>User friendly for both wet and dry lab usrers.</li>
-<li>Produce pubilishable figures.</li>
+<li>Produce and reproduce pubilishable figures.</li>
 <li>Perform batch jobs easy(using for loops).</li>
 <li>Easy to use in bash shell or your  data analysis workflow, e.g. snakemake.</li>
 </ul>
@@ -249,7 +249,7 @@ <h2>Why GSEAPY<a class="headerlink" href="#why-gseapy" title="Permalink to this
 </ul>
 </li>
 <li class="toctree-l2"><a class="reference internal" href="gseapy_tutorial.html#use-prerank-command-or-prerank">Use <code class="docutils literal"><span class="pre">prerank</span></code> Command, or <code class="docutils literal"><span class="pre">prerank()</span></code></a></li>
-<li class="toctree-l2"><a class="reference internal" href="gseapy_tutorial.html#use-single-command-or-ssgsea">Use <code class="docutils literal"><span class="pre">single</span></code> command, or <code class="docutils literal"><span class="pre">ssgsea()</span></code></a></li>
+<li class="toctree-l2"><a class="reference internal" href="gseapy_tutorial.html#use-ssgsea-command-or-ssgsea">Use <code class="docutils literal"><span class="pre">ssgsea</span></code> command, or <code class="docutils literal"><span class="pre">ssgsea()</span></code></a></li>
 <li class="toctree-l2"><a class="reference internal" href="gseapy_tutorial.html#use-enrichr-command-or-enrichr">Use <code class="docutils literal"><span class="pre">enrichr</span></code> command, or <code class="docutils literal"><span class="pre">enrichr()</span></code></a></li>
 <li class="toctree-l2"><a class="reference internal" href="gseapy_tutorial.html#use-replot-command-or-replot">Use <code class="docutils literal"><span class="pre">replot</span></code> Command, or <code class="docutils literal"><span class="pre">replot()</span></code></a></li>
 </ul>