limma

Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq

A Snakemake workflow and MrBiomics module for performing and visualizing differential analyses of NGS data powered by the R package limma.

DEqMS is a tool for quantitative proteomic analysis

Tools for normalization, evaluation of outliers, technical biases and batch effects and differential expression analysis.

A quick recap of widely used differential analyses methods in R for RNA-seq experiments

Differential expression analysis: DESeq2, edgeR, limma. Realized in python based on rpy2

analyze_geo_microarrays.py : Differential expression analysis of published microarrays datasets from the NCBI Gene Expression Omnibus (GEO)

Timeseries analysis of -omics data can be carried out by fitting spline curves to the data and using limma for hypothesis testing. The obtained hits can be clustered based on the spline shape and then used for an over-representation (ORA) analysis.The R package SplineOmics streamlines this whole process and generates reports.

Simple workflows for the isobaric-labeling proteomic data from Proteome Discoverer with ANOVA, t-testing, DEqMS/limma and annotation via fgsea

Rosetta Stone between R and Python for bio

Python port of R limma for differential expression analysis

Bioinformatic analysis of gene expression microarray profiles and DGEs on R and R studio

EuroBioc2020 SPEAQeasy workshop https://eurobioc2020.bioconductor.org by Nick Eagles and Josh Stolz. For more information about SPEAQeasy check http://research.libd.org/SPEAQeasy/. For an example on how to use this RNA-seq processing pipeline and analyze the output files check http://research.libd.org/SPEAQeasy-example/.

Interactive Transcriptomics & DEG Visualization Dashboard

A selection of analytical approaches, tools, and utilities for the processing of microbiome data derived from either 16S rRNA amplicon sequencing or shotgun metagenomics.

Automated Bioconductor pipeline for programmatic retrieval, differential gene expression analysis, and GSEA pathway enrichment of public NCBI GEO transcriptomic datasets.

MetaboFlow: Untargeted LC-MS Metabolomics Quad-Workflow Pipeline | 非靶向代谢组学四工作流集成分析系统 | 4 pathway enrichment workflows (ORA+QEA) | Nature-quality figures | R-based | tidymass + MetaboAnalystR + limma

Reproducible R workflow that generates bulk RNA-seq from single-cell references, injects batch/biology effects, and compares correction methods (ComBat, limma, RUV, fastMNN, SVA) using quantitative metrics and plots. Outputs are bulk-level assays (bulk_counts).

Bulk RNA-seq analysis of colorectal cancer (GSE50760): QC, differential expression (limma), and GO/KEGG/GSEA enrichment in R