scran -- Single-Cell RNA-Seq Normalization and Analysis

Use when working with CATALYST for mass-cytometry or flow-cytometry analysis in R/Bioconductor, including preprocessing with prepData, normCytof, assignPrelim, estCutoffs, applyCutoffs, computeSpillma

2 shared topics • 2 shared operations

Use this skill for SCTransform normalization of single-cell RNA-seq count matrices. Route here when users ask about variance stabilizing transformation (VST), regularized negative binomial regression

2 shared topics • 2 shared operations

ZINB-WaVE (Zero-Inflated Negative Binomial Wave) for dimensionality reduction and normalization of single-cell RNA-seq data. Fits a zero-inflated negative binomial (ZINB) model to scRNA-seq count matr

2 shared topics • 2 shared operations

estimate-compute-requirements — predict CPU, memory, wall time, and storage for bioinformatics pipelines given input data size and tool selection. Generates per-step resource tables, platform-specific

2 shared topics • 1 shared operation

Seurat — comprehensive R toolkit for single-cell genomics enabling QC, normalization (LogNormalize, SCTransform), feature selection, dimensionality reduction (PCA, UMAP, t-SNE), graph-based clustering

2 shared topics • 1 shared operation