From 94be6c562dfde2c14dc64b0cbf516c590cc05f85 Mon Sep 17 00:00:00 2001 From: zqfang Date: Tue, 24 Oct 2023 15:03:02 -0700 Subject: [PATCH] docs --- docs/faq.rst | 11 +++++++++++ docs/index.rst | 10 ++++++---- 2 files changed, 17 insertions(+), 4 deletions(-) diff --git a/docs/faq.rst b/docs/faq.rst index 1187892..6af13c5 100644 --- a/docs/faq.rst +++ b/docs/faq.rst @@ -30,6 +30,17 @@ When observed ES is not within the null ESs, you'll get 0s. if you don't want 0, - set the smallest pvalue to 1 / ( number of permutations) - increase the permutation number (but more running time needed) +**Q:** What are ``gene %``, and ``tag %`` mean in the output? +----------------------------------------------------------------------- + +.. math:: + + \text{gene \\%} = \text{(the position of the gene coresponding to enrichment score peak)} \div \text{(number of all genes in ranking list)} + + +.. math:: + + \text{tag \\%} = \text{( number of leading genes)} \div \text{(number of genes in certain pathway that overalpped with the input ranking list)} diff --git a/docs/index.rst b/docs/index.rst index 490fbc5..7710941 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -62,7 +62,7 @@ Installation GSEApy is a Python/Rust implementation of **GSEA** and wrapper for **Enrichr**. -------------------------------------------------------------------------------------------- -GSEApy has six subcommands: ``gsea``, ``prerank``, ``ssgsea``, ``replot`` ``enrichr``, ``biomart``. +GSEApy has multiple subcommands: ``gsea``, ``prerank``, ``ssgsea``, ``gsva``, ``replot`` ``enrichr``, ``biomart``. 1. The ``gsea`` module produces **GSEA** results. The input requries a txt file(FPKM, Expected Counts, TPM, et.al), a cls file, and gene_sets file in gmt format. @@ -73,13 +73,15 @@ The input expects a pre-ranked gene list dataset with correlation values, which 3. The ``ssgsea`` module performs **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 `_. -4. The ``replot`` module reproduces GSEA desktop version results. +4. The ``gsva`` module performs **GSVA** analysis, which described by `Hänzelmann et al `_. + +5. The ``replot`` module reproduces GSEA desktop version results. The only input for GSEAPY is the location to GSEA Desktop output results. -5. The ``enrichr`` module enables you to perform gene set enrichment analysis using ``Enrichr`` API. +6. The ``enrichr`` module enables you to 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 and generates results in txt format. -6. The ``biomart`` module helps you convert gene ids using BioMart API. +7. The ``biomart`` module helps you convert gene ids using BioMart API. 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.