Data & Analytics · By TianGzlab

Load when the user needs Deterministic fixed-period 24-hour single-component cosinor OLS rhythm analysis for a bulk RNA time-course CSV.

TianGzlab/OmicsClaw

Load when correcting batch effects in bulk expression using R sva ComBat or the legacy Python parametric approximation.

TianGzlab/OmicsClaw

Load when discovering bulk gene co-expression modules and hub genes with R WGCNA.

TianGzlab/OmicsClaw

Load when converting Ensembl, Entrez or symbol IDs in a bulk RNA count matrix using an explicit mapping or a small human demo reference.

TianGzlab/OmicsClaw

Load when querying STRING for the protein-protein interaction neighborhood of 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 comparing bulk expression strata against clinical time-to-event data with Kaplan-Meier and log-rank tests.

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 matching LC-MS m/z features to an explicit local metabolite reference within a ppm tolerance; bundled HMDB entries are for explicit demonstrations only.

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 metabolite-name ORA against an explicit local pathway reference with BH-FDR; bundled pathway sets are for explicit demonstrations only.

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 exercising the CLI and replay pipeline with a synthetic LC-MS peak table.

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 for Fisher over-representation analysis of protein identifiers against caller-supplied pathways.

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

TianGzlab/OmicsClaw

Load when testing whether cell-type / cluster proportions or neighbourhood densities differ between conditions in a multi-sample scRNA AnnData via Milo, scCODA, simple proportion screen, or R…

TianGzlab/OmicsClaw

Load when running bulk-style pathway enrichment (ORA / GSEA / GSEA-R / GSVA-R) on a per-group ranked DE / marker list against a gene-set library.

TianGzlab/OmicsClaw

Load when extracting gene programs (NMF / cNMF factorisation) and per-cell program usage scores from a non-negative scRNA AnnData.

TianGzlab/OmicsClaw

Load when inferring TF → target gene regulatory networks on a normalised scRNA AnnData via pySCENIC (GRNBoost2 + cisTarget + AUCell) or correlation-based GRN fallback (when arboreto is unavailable…

TianGzlab/OmicsClaw

Load when ordering cells along a developmental trajectory in a normalised scRNA AnnData via DPT, Palantir, VIA, CellRank, Slingshot (R), or Monocle3 (R).

TianGzlab/OmicsClaw

Load when computing RNA velocity vectors on a scRNA AnnData with spliced / unspliced layers via scVelo (stochastic / dynamical / steady-state); dynamical mode additionally exports latent time.

TianGzlab/OmicsClaw

Load when inferring copy-number variation per spot on a preprocessed spatial AnnData with chromosome-annotated genes via infercnvpy (default — log-ratio sliding-window) or Numbat (R, allele-aware…

TianGzlab/OmicsClaw

Load when ranking spatially variable genes with Moran's I, SpatialDE, SPARK-X, or FlashS.

TianGzlab/OmicsClaw

Load when running the foundational spatial transcriptomics QC + filtering + normalisation + HVG + PCA + neighbour-graph + Leiden pipeline on a Visium / Xenium / generic spatial AnnData.

TianGzlab/OmicsClaw

Load when aligning multiple spatial slices into a common coordinate frame with PASTE or STalign.

TianGzlab/OmicsClaw

Load when running spatial autocorrelation / hotspot / co-occurrence / neighbourhood-enrichment / Ripley K stats on a clustered spatial AnnData via squidpy.

TianGzlab/OmicsClaw

Load when inferring pseudotime / lineage trajectories on a preprocessed spatial AnnData via DPT (default — diffusion pseudotime), CellRank (terminal-state + fate-probability), or Palantir (waypoint…

TianGzlab/OmicsClaw

Load when estimating RNA velocity on a spatial AnnData with layers["spliced"] + layers["unspliced"] via scVelo (stochastic / deterministic / dynamical) or veloVI (deep generative).

TianGzlab/OmicsClaw