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Differential gene expression analysis for bulk RNA-seq count matrices using a DESeq2-like workflow in Python; use when you need Wald tests, FDR correction, and optional LFC shrinkage for condition/batch/covariate designs.
Bulk RNA-seq DE with PyDESeq2: load counts, normalize, fit negative binomial models, Wald test (BH-FDR), LFC shrinkage, volcano/MA plots. Use for two-group comparisons, multi-factor designs with batch correction, multiple contrasts.
End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, featureCounts), assembles a gene-level counts matrix, then hands off to differential expression (pydeseq2), pathway/GSEA enrichment (pathwa...
Agent skill for Data Scientist, Business Intelligence Analyst, Researcher, published by FridrichMethod. Project details and file access are provided by the publisher.
Agent skill for Researcher, Data Scientist, published by FridrichMethod. Project details and file access are provided by the publisher.
Agent skill for Researcher, Data Scientist, Business Intelligence Analyst, published by BioTender-max. Project details and file access are provided by the publisher.
Agent skill for Data Scientist, Business Intelligence Analyst, Researcher, published by BioTender-max. Project details and file access are provided by the publisher.
Agent skill for Data Scientist, Researcher, Business Intelligence Analyst, published by BioTender-max. Project details and file access are provided by the publisher.
Agent skill for Researcher, Data Scientist, Clinical Research, published by KunanonJ. Project details and file access are provided by the publisher.
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