Perform differential gene expression analysis on bulk RNA-seq count data.
npx skills add https://github.com/TianGzlab/OmicsClaw --skill bulkrna-de
Please help me install this Agent Skill. Skill: bulkrna-de Source: https://github.com/TianGzlab/OmicsClaw/tree/main/skills/bulkrna/bulkrna-de Command: npx skills add https://github.com/TianGzlab/OmicsClaw --skill bulkrna-de
This Skill automates the complex process of identifying genes that show significant changes in expression levels between different biological conditions in bulk RNA sequencing data.
Run differential expression analysis on my bulk RNA-seq counts.
High-intent search queries and answers about installing and using this skill.
To find differentially expressed genes from bulk RNA-seq data, this analysis runs PyDESeq2 or a Welch's t-test with Benjamini-Hochberg correction on count data, outputting publication-ready plots and significant gene tables.
Yes, you can use DESeq2 for RNA-seq differential expression analysis in Python via the PyDESeq2 implementation, which processes count data to identify significantly up- and down-regulated genes.
The best way to generate volcano plots and MA plots for RNA-seq is using matplotlib-based visualization tools that automatically process differential expression results and output publication-ready summary charts.
Yes, you need raw count data to run differential gene expression analysis, as the underlying PyDESeq2 and Welch's t-test statistical methods require integer count matrices to calculate significance.
You should use a t-test instead of DESeq2 for RNA-seq analysis when working with simpler two-group comparisons, applying Welch's t-test with Benjamini-Hochberg correction to identify significant biological markers.
Victory-HugoPerform differential expression analysis on bulk RNA-seq data with PyDESeq2.
omicverseAnalyze bulk RNA-seq count matrices for differential expression and pathway enrichment.
RamanEbrahimiPerform differential gene expression analysis on RNA-seq count data with DESeq2 in Python.
MubasherMohammedSummarize differential expression results from DESeq2, edgeR, or limma outputs.
