Use when performing differential expression analysis on RNA-seq count data using NOISeq or NOISeqBIO. Covers the full workflow: data object creation with readData, quality control with dat and explo.p
Use with AI
Install the MCP server or CLI to instantly fetch NOISeq documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/noiseq
deepTools — suite of Python tools for efficient analysis and visualization of high-throughput sequencing data including ChIP-seq, ATAC-seq, MNase-seq, and RNA-seq. BAM-to-bigWig conversion with normal
1 shared topic • 2 shared operations
PyDESeq2 — Python implementation of DESeq2 for differential gene expression analysis from bulk RNA-seq count data. Performs size factor normalization, genewise dispersion estimation, Wald tests with B
1 shared topic • 2 shared operations
scDblFinder — Bioconductor R package for detecting doublets in single-cell RNA-seq data using simulation-based classification with gradient boosting. Identifies neotypic and heterotypic doublets in dr
1 shared topic • 2 shared operations
Seurat — comprehensive R toolkit for single-cell genomics enabling QC, normalization (LogNormalize, SCTransform), feature selection, dimensionality reduction (PCA, UMAP, t-SNE), graph-based clustering
1 shared topic • 2 shared operations
WiggleTools — command-line toolkit for streaming arithmetic and set operations on genomic signal tracks stored in Wiggle, BigWig, BedGraph, and BAM/CRAM formats. Computes sums, means, products, log tr
1 shared topic • 2 shared operations