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Agent skills

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Agent skill

MeRIP-seq End-to-End Pipeline

Orchestrates an end-to-end MeRIP-seq / m6A-seq analysis from raw FASTQ to differential m6A peak calls and metagene plots, chaining fastp adapter trimming, STAR splice-aware genome alignment (NO deduplication for non-UMI MeRIP), deepTools replicate-concordance + IP-enrichment QC, PreSeq saturation...

ClaudeCodexOpenClawData & Analytics
GPTomics1,232
Agent skill

Differential Accessibility

Identify differentially accessible chromatin regions across conditions using DiffBind, csaw, DESeq2, or edgeR. Use when comparing ATAC-seq accessibility between treatment groups, choosing between consensus-peak vs sliding-window approaches, picking the correct normalization (full library vs reads...

ClaudeCodexOpenClawData & Analytics
GPTomics1,232
Agent skill

counts_df: rows = sgRNAs, columns = samples

Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or Chronos. Covers screen-specific batch sources (passage cohort, library lot, infection day, sequenci...

ClaudeCodexOpenClawData & Analytics
GPTomics1,232
Agent skill

DE Visualization

Creates DE-specific diagnostic and result visualizations using DESeq2/edgeR built-in functions and lightweight ggplot2 wrappers. Covers MA plot (with the shrunken-LFC compression effect), volcano (with the apeglm caveat that p-values are unchanged), PCA on VST/rlog (never raw counts), sample dist...

ClaudeCodexOpenClawData & Analytics
GPTomics1,232
Agent skill

Sample Size for Genomics Experiments

Estimates the minimum biological replicates (or cells/events) for a target power at a target FDR in genomics experiments using ssizeRNA, PROPER, powsimR for scRNA-seq, and pilot-data dispersion estimation from DESeq2/edgeR. Covers the biological-versus-technical replication distinction (technical...

ClaudeCodexOpenClawData & Analytics
GPTomics1,232
Agent skill

Expression Matrix Normalization

Normalizes and transforms RNA-seq count matrices for DE, visualization, clustering, and ML. Covers between-sample (TMM, TMMwsp, RLE/median-of-ratios, upper quartile), within-sample (TPM, FPKM/RPKM), variance-stabilizing (VST, rlog, log-CPM), GC-content correction (cqn, EDASeq), and single-cell (s...

ClaudeCodexOpenClawData & Analytics
GPTomics1,232
Agent skill

Expression to Pathways Workflow

Orchestrates the full path from differential expression results to redundancy-collapsed functional enrichment: choose ORA vs GSEA, convert gene IDs per method, run enrichGO/enrichKEGG/enrichPathway/enrichWP or gseGO/gseKEGG (clusterProfiler, ReactomePA, rWikiPathways), and visualize. Routes the O...

ClaudeCodexOpenClawData & Analytics
GPTomics1,232
Agent skill

Time-Course Analysis Pipeline

End-to-end time-course analysis from expression matrix to temporal patterns and enrichment. Covers temporal DE, Mfuzz soft clustering, optional rhythm detection, GAM trajectory fitting, and per-cluster pathway enrichment. Use when analyzing bulk time-series expression experiments from any omics p...

ClaudeCodexOpenClawData & Analytics
GPTomics1,232
Agent skill

DE Results

Extracts, filters, annotates, and exports differential expression results from DESeq2 or edgeR with proper handling of padj=NA (independent filtering, Cook's outliers, all-zero), multiple-testing correction choice (BH vs Storey q-value vs IHW vs lfsr), TREAT vs post-hoc fold-change filtering, p-v...

ClaudeCodexOpenClawData & Analytics
GPTomics1,232
Agent skill

DESeq2 Basics

Performs differential expression on bulk RNA-seq count data with DESeq2's negative-binomial GLM, Wald and LRT testing, apeglm/ashr/normal LFC shrinkage, independent filtering, Cook's outlier handling, VST/rlog transforms, and design formulas including paired, batch, and interaction terms. Use whe...

ClaudeCodexOpenClawData & Analytics
GPTomics1,232
Agent skill

Count Matrix QC

Quality control and exploration of RNA-seq count matrices before differential expression. Check for outliers, batch effects, and sample relationships. Use when assessing count matrix quality before DE analysis.

ClaudeCodexOpenClawData & Analytics
GPTomics1,232
Agent skill

differential-abundance

Differential abundance testing for microbiome data using compositionally-aware methods like ALDEx2, ANCOM-BC2, and MaAsLin2. Use when identifying taxa that differ between experimental groups while accounting for the compositional nature of microbiome data.

ClaudeCodexOpenClawData & Analytics
GPTomics1,232

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