Research & Science · Python · By TianGzlab

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

TianGzlab/OmicsClaw

Load when turning scRNA FASTQ (or existing CellRanger/STARsolo/SimpleAF/kb-python output) into a downstream-ready AnnData.

TianGzlab/OmicsClaw

Load when annotating putative doublets in single-cell RNA-seq using Scrublet, DoubletDetection, DoubletFinder, scDblFinder, or scds.

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 checking raw single-cell FASTQ read quality (Phred / GC / adapter / length) before counting.

TianGzlab/OmicsClaw

Load when predicting in-silico gene knockout effects on a normalised scRNA AnnData via GRN-based propagation (Python) or scTenifoldKnk (R).

TianGzlab/OmicsClaw

Load when computing per-cell pathway / gene-set scores on a normalised scRNA AnnData via AUCell (R or Python) or Scanpy scoregenes.

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