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lingxling/scientific-agent-skills

v2.72.0MIT

Ready-to-use scientific and research Agent Skills for biology, chemistry, medicine, and related workflows.

bulk-rnaseq

Prepares bulk RNA-seq FASTQ, Salmon, STAR or featureCounts output for gene-level differential expression. Covers nf-core/rnaseq and standalone quantification, biological replication, strandedness, reference provenance, validated count assembly and a PyDESeq2 handoff. Use for FASTQ-to-counts analysis, nf-core/rnaseq configuration, STAR/Salmon quantification, or building a counts matrix for DESeq2. For single-cell data use scanpy; for statistical fitting alone use pydeseq2.

Version
2.0
License
MIT
Compatibility
Requires Python 3.11+ with pandas and numpy; Salmon import also needs pytximport. Read processing needs Nextflow with containers or standalone bioinformatics tools. Network access is needed for installation and reference downloads.
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