Agent skills by TianGzlab

Load when removing batch effects from a multi-cohort bulk RNA-seq dataset using ComBat (R or Python implementation).

TianGzlab/OmicsClaw

Load when discovering gene co-expression modules and hub genes in a bulk RNA-seq cohort via WGCNA-style soft-thresholded networks.

TianGzlab/OmicsClaw

Load when comparing gene expression between two conditions in bulk RNA-seq count data.

TianGzlab/OmicsClaw

Load when estimating cell-type proportions in bulk RNA-seq samples from a single-cell or signature-matrix reference.

TianGzlab/OmicsClaw

Load when running pathway / GO term enrichment on a bulk RNA-seq DE result list.

TianGzlab/OmicsClaw

Load when converting gene identifiers between Ensembl, Entrez, and HGNC symbol in a bulk RNA-seq count matrix.

TianGzlab/OmicsClaw

Load when querying STRING for the protein-protein interaction subgraph induced by a bulk RNA-seq DEG list and finding hub genes.

TianGzlab/OmicsClaw

Load when checking a bulk RNA-seq count matrix for library-size outliers, gene detection rates, and sample-sample correlation before DE.

TianGzlab/OmicsClaw

Load when summarising STAR / HISAT2 / Salmon alignment-rate logs in bulk RNA-seq.

TianGzlab/OmicsClaw

Load when checking raw FASTQ quality (Phred / GC / adapter / Q20-Q30) before alignment in bulk RNA-seq.

TianGzlab/OmicsClaw

Load when summarising rMATS / SUPPA2 alternative-splicing output and identifying significant differential splicing events.

TianGzlab/OmicsClaw

Load when stratifying patients by gene expression and testing for survival differences (Kaplan-Meier + Cox) in bulk RNA-seq.

TianGzlab/OmicsClaw

Load when placing bulk RNA-seq samples on a single-cell reference's pseudotime axis (NNLS deconvolution + nearest-neighbour mapping).

TianGzlab/OmicsClaw

Load when you want a verified multi-method consensus over spatial tissue domains on a preprocessed spatial AnnData — fanning out N domain methods, ranking base clusterings, and emitting a typed…

TianGzlab/OmicsClaw

Load when biologically interpreting a finished verified consensus run (consensus-domains / sc-consensus-clustering) — inline DE, marker-DB lookup, and LLM cell-type naming with mandatory marker…

TianGzlab/OmicsClaw

Load when computing alignment QC metrics (mapping rate, MAPQ distribution, insert size, duplicate rate, proper-pair rate) from a SAM or BAM file produced by any short-/long-read aligner (BWA /…

TianGzlab/OmicsClaw

Load when computing genome-assembly QC metrics — N50/N90, L50/L90, total length, contig count, GC content, longest-contig — from a FASTA produced by any assembler (SPAdes / Megahit / Flye / Canu).

TianGzlab/OmicsClaw

Load when calling CNV segments via CBS-style segmentation on a bin-level log2-ratio CSV from exome / WGS coverage — emits per-segment 5-class CN state (amplification / gain / neutral / loss /…

TianGzlab/OmicsClaw

Load when summarising a peak file (BED / narrowPeak) from ATAC-seq / ChIP-seq / CUT&Tag — peak count, width distribution, per-chromosome counts, score statistics.

TianGzlab/OmicsClaw

Load when summarising a phased VCF (output of WhatsHap / SHAPEIT5 / Eagle2) — phased fraction of het variants, phase-block N50, PS-field parsing, pipe-delimited genotype detection.

TianGzlab/OmicsClaw

Load when running pre-alignment FASTQ quality control — Phred quality scores, Q20/Q30 rates, GC / N content, read-length distribution, adapter-contamination detection.

TianGzlab/OmicsClaw

Load when summarising structural variants from an SV VCF (DEL / DUP / INV / TRA) — BND-notation parsing, size classification, per-type counts.

TianGzlab/OmicsClaw

Load when summarising functional impact of an annotated variant CSV — per-IMPACT counts (HIGH / MODERATE / LOW / MODIFIER), top consequences, gene-affected count.

TianGzlab/OmicsClaw

Load when summarising small variants (SNVs / indels) from a VCF or computing demo-pattern variant statistics (Ti/Tv ratio, per-chromosome distribution, SNP / indel split).

TianGzlab/OmicsClaw

Load when summarising / filtering a VCF — variant classification (SNP / MNP / INS / DEL / COMPLEX), Ti/Tv ratio, QUAL / DP threshold filtering, INFO-field parsing.

TianGzlab/OmicsClaw

Load when extracting GEO accessions, dataset metadata, and downloadable references from a scientific paper (PDF / URL / DOI / PubMed ID / raw text) for downstream omics analysis.

TianGzlab/OmicsClaw

Load when annotating LC-MS features against a built-in 15-metabolite HMDB demo dictionary by m/z within a --ppm tolerance — emits a per-feature annotation table.

TianGzlab/OmicsClaw

Load when running two-group metabolomics DE (t-test + log2FC + BH-FDR + PCA) on a feature × sample CSV using --group-a-prefix / --group-b-prefix (default ctrl / treat).

TianGzlab/OmicsClaw

Load when normalising a feature × sample metabolomics CSV via median, quantile, total (sum), PQN (probabilistic quotient), or log methods — emits a normalised wide-form table.

TianGzlab/OmicsClaw

Load when running over-representation analysis (ORA) on a metabolite list via Fisher's exact test against a built-in 9-pathway DEMO dictionary, BH-FDR adjusted.

TianGzlab/OmicsClaw

Load when running per-sample peak picking on a feature × intensity table via scipy.signal.findpeaks — emits per-(sample, feature) detected peaks with prominence and width.

TianGzlab/OmicsClaw

Load when imputing missing values (min / median / KNN) and normalising (TIC / median / log) a feature × sample metabolomics CSV.

TianGzlab/OmicsClaw

Load when running univariate two-group testing (t-test / Wilcoxon / ANOVA / Kruskal-Wallis) on a feature × sample metabolomics CSV with --group1-prefix / --group2-prefix column matching, BH-FDR…

TianGzlab/OmicsClaw

Load when running an XCMS-style preprocessing summary on LC-MS metabolomics raw / vendor-converted files — emits a peak table with m/z, retention time, and per-sample intensities.

TianGzlab/OmicsClaw

Load when scaffolding a NEW OmicsClaw skill from a natural-language request — generates the skill directory layout (skill.yaml, SKILL.md, references/, tests/) under the chosen domain.

TianGzlab/OmicsClaw

Load when routing a natural-language omics query to the correct domain skill across spatial / singlecell / genomics / proteomics / metabolomics / bulkrna domains via keyword / LLM / hybrid matching.

TianGzlab/OmicsClaw

Load when ingesting a MaxQuant proteinGroups.txt, FragPipe combinedprotein.tsv, DIA-NN report, or generic CSV / TSV protein-quantification table — normalises columns to a standard schema, emits…

TianGzlab/OmicsClaw

Load when computing two-group differential protein abundance (group2 vs group1, log2FC + p-value + BH-adjusted FDR) via Welch t-test, equal-variance t-test, or Mann-Whitney on a wide protein ×…

TianGzlab/OmicsClaw

Load when running over-representation analysis (ORA) on a list of proteins via Fisher's exact test against a built-in 8-pathway DEMO dictionary, with BH-FDR correction.

TianGzlab/OmicsClaw

Load when summarising peptide identifications (PSM count, unique peptide count, distinct protein count, score / charge distributions) from a peptide-level CSV produced by MaxQuant / FragPipe / DIA-NN.

TianGzlab/OmicsClaw

Load when computing protein-table QC — proteins × samples count, missing-value rate, intensity CV (median + mean) — from a MaxQuant / FragPipe / DIA-NN protein-quantification CSV.

TianGzlab/OmicsClaw

Load when summarising PTM sites (phosphorylation, acetylation, ubiquitination, etc.) from a per-site CSV — site-class assignment (Olsen et al.

TianGzlab/OmicsClaw

Load when computing per-protein abundance from a peptide / PSM table via LFQ (intensity summation), iBAQ (intensity / tryptic peptide count), or spectral counting (PSMs per protein).

TianGzlab/OmicsClaw

Load when summarising cross-linking MS (XL-MS) results — intra/inter-protein link split, optional FDR filtering, distance-constraint validation against a per-crosslinker (DSS / BS3 / EDC / DSSO /…

TianGzlab/OmicsClaw

Load when removing ambient RNA contamination from droplet-based scRNA-seq using a simple subtraction path, CellBender, or SoupX.

TianGzlab/OmicsClaw

Load when integrating multi-sample scRNA-seq with Harmony, scVI, scANVI, BBKNN, Scanorama, SIMBA, or supported R-backed methods to remove batch effects.

TianGzlab/OmicsClaw

Load when assigning cell-type labels to a clustered scRNA AnnData via marker dictionaries, CellTypist, PopV, KNNPredict, SingleR, scmap, SCSA, or a manual cluster-to-label map.

TianGzlab/OmicsClaw

Load when computing cell-cell ligand-receptor communication on an annotated scRNA AnnData via builtin scorer, LIANA, CellPhoneDB, CellChat (R), or NicheNet (R).

TianGzlab/OmicsClaw