codex

Life Sciences NGS Analysis

Guided NGS intake, local execution, and public-pipeline routing for BCL, FASTQ, DNA variant, RNA-seq, single-cell, epigenomics, amplicon, and metagenomics analyses, with deeper decision skills for high-risk assay branches.

30 on GitHubby OpenAIv1.0.3MITupdated 4 months agoEducation & Research

Plugin ngs-analysis in zhongjingyun/codex-plugins. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (18)

  • ngs-amplicon-microbiome

    Kick off public 16S, 18S, ITS, COI, or other marker-gene amplicon microbiome workflows using nf-core/ampliseq, QIIME2, DADA2, and Cutadapt.

  • ngs-analysis-router

    Route BCL, FASTQ, BAM/CRAM, count-matrix, or VCF sequencing requests to the right public NGS analysis skill and ask only the missing assay-specific setup questions.

  • ngs-atacseq-peaks-qc

    Run or plan ATAC-seq QC, alignment, TSS enrichment, fragment-size, blacklist, peak-calling, consensus peak, and differential accessibility workflows.

  • ngs-bcl-to-fastq

    Validate Illumina BCL run folders and sample sheets, plan demultiplexing, review index/UMI/lane choices, run BCL-to-FASTQ conversion, and interpret demux metrics while surfacing license/download boundaries.

  • ngs-bulk-rnaseq-counts-qc

    Run or plan bulk RNA-seq FASTQ-to-count processing with sample-sheet, strandedness, genome annotation, alignment or pseudoalignment, MultiQC, and count-matrix QC checks.

  • ngs-bulk-rnaseq-differential-expression

    Run or plan bulk RNA-seq differential-expression analysis from count matrices with replicate, design formula, contrast, batch, normalization, QC plot, and result-table checks.

  • ngs-bulk-rnaseq

    Dispatch bulk RNA-seq requests to FASTQ-to-count QC or count-matrix differential-expression skills using nf-core/rnaseq, STAR, Salmon, featureCounts, MultiQC, and R/Bioconductor workflows.

  • ngs-chip-cutrun-peaks-qc

    Run or plan ChIP-seq, CUT&RUN, or CUT&Tag QC, control handling, spike-in, peak calling, broad-vs-narrow target selection, replicate, bigWig, and differential binding workflows.

  • ngs-dna-germline-variants

    Run or plan deep germline WGS, WES, targeted-panel, cohort, or trio variant-calling workflows with reference-build, known-sites, QC, joint-calling, and annotation checks.

  • ngs-dna-somatic-variants

    Run or plan tumor-normal, tumor-only, WGS, WES, or cancer-panel somatic variant workflows with pairing, contamination, panel-of-normals, purity, QC, and annotation checks.

  • ngs-dna-umi-panel-variants

    Run or plan targeted DNA panel variant workflows that use UMIs, duplex consensus reads, molecular barcodes, low-frequency calling, target coverage, and panel-specific QC.

  • ngs-dna-variant-calling

    Dispatch WGS, WES, or targeted DNA variant requests to germline, somatic, or UMI-panel skills, then plan public nf-core/sarek, GATK4, DeepVariant, samtools, or bcftools workflows.

  • ngs-epigenomics-peaks

    Dispatch ATAC-seq, ChIP-seq, CUT&RUN, or CUT&Tag requests to assay-specific QC, alignment, signal-track, peak-calling, consensus, and differential peak workflows.

  • ngs-fastq-qc

    Validate FASTQ inputs, run local FastQC/MultiQC QC, interpret QC signals, and optionally execute fastp or Cutadapt trimming branches without overwriting raw reads.

  • ngs-runtime-env

    Check whether public NGS tools and packages already exist before downloading, installing, or running a sequencing pipeline.

  • ngs-scrna-seq

    Route single-cell or single-nucleus RNA-seq FASTQs to public count-generation workflows and defer post-count matrix QC, annotation, clustering, and UMAP analysis to the embedded scrna-seq-qc skill.

  • ngs-shotgun-metagenomics

    Kick off public shotgun metagenomics QC, host-depletion, taxonomic profiling, and functional profiling workflows using nf-core/taxprofiler, Kraken2, Bracken, MetaPhlAn, and HUMAnN.

  • scrna-seq-qc

    Process, quality-control, annotate, and visualize single-cell or single-nucleus RNA-seq datasets across tissues and species. Use when Codex needs to build, adapt, or review a general scRNA-seq QC pipeline; choose dataset-appropriate cell-level filters from QC distributions; run required scDblFinder-

View source on GitHub openai.com

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