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zqfang committed Oct 24, 2023
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Expand Up @@ -57,7 +57,7 @@ GSEApy has 7 sub-commands available: ``gsea``, ``prerank``, ``ssgsea``, ``gsva``
:gsea: The ``gsea`` module produces `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 produces **Prerank tool** results. The input expects a pre-ranked gene list dataset with correlation values, provided in .rnk format, and gene_sets file in gmt format. ``prerank`` module is an API to `GSEA` pre-rank tools.
:ssgsea: The ``ssgsea`` module performs **single sample GSEA(ssGSEA)** analysis. The input expects a pd.Series (indexed by gene name), or a pd.DataFrame (include ``GCT`` file) with expression values and a ``GMT`` file. For multiple sample input, ssGSEA reconigzes gct format, too. ssGSEA enrichment score for the gene set is described by `D. Barbie et al 2009 <http://www.nature.com/nature/journal/v462/n7269/abs/nature08460.html>`_.
:gsva: The ``gsva`` module performs `GSVA <https://github.com/rcastelo/GSVA>`_ method. The input is same to ssgsea.
:gsva: The ``gsva`` module performs `GSVA <https://github.com/rcastelo/GSVA>`_ method by `Hänzelmann et al <https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-14-7>`_. The input is same to ssgsea.
:replot: The ``replot`` module reproduce GSEA desktop version results. The only input for GSEApy is the location to ``GSEA`` Desktop output results.
:enrichr: The ``enrichr`` module enable you perform gene set enrichment analysis using ``Enrichr`` API. Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr . It runs very fast.
:biomart: The ``biomart`` module helps you convert gene ids using BioMart API.
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Mandatory
~~~~~~~~~

build

* Rust: For gseapy > 0.11.0, Rust compiler is needed
* setuptools-rust

run

* Numpy >= 1.13.0
* Scipy
* Pandas
* Matplotlib
* Requests


* build
* Rust: For gseapy > 0.11.0, Rust compiler is needed
* setuptools-rust
* run
* Numpy >= 1.13.0
* Scipy
* Pandas
* Matplotlib
* Requests

Run GSEApy
-----------------
Expand All @@ -167,7 +162,7 @@ For command line usage:
# An example to run ssGSEA using gseapy ssgsea module
$ gseapy ssgsea -d expression.txt -g gene_sets.gmt -o test
# An example to run ssGSEA using gseapy ssgsea module
# An example to run GSVA using gseapy ssgsea module
$ gseapy gsva -d expression.txt -g gene_sets.gmt -o test
# An example to use enrichr api
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# assign gene_sets parameter with enrichr library name or gmt file on your local computer.
gseapy.gsea(data=expression_dataframe, gene_sets='KEGG_2016', cls= sample_names, outdir='test')
# using prerank tool
# prerank tool
gene_ranked_dataframe = pd.DataFrame()
gseapy.prerank(rnk=gene_ranked_dataframe, gene_sets='KEGG_2016', outdir='test')
# using ssGSEA
# ssGSEA
gseapy.ssgsea(data=expression_dataframe, gene_sets='KEGG_2016', outdir='test')
# using ssGSEA
# gsva
gseapy.gsva(data=expression_dataframe, gene_sets='KEGG_2016', outdir='test')
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