Brings bulk and pseudobulk transcriptomics to the tidyverse

Statistical Analysis of RNA-Seq Tools

This RNAseq data analysis tutorial is created for educational purpose

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

Generate HTML report for a set of genomic regions or DESeq2/edgeR results

Various tutorials on how to analyse transcriptomic data.

Probabilistic outlier identification for bulk RNA sequencing data

Some of the analytical processes and tools we use to provide rigorous and actionable results to our clients.

Some of the analytical processes and tools we use to provide rigorous and actionable results to our clients.

Sea lion urine comparison with spectral counting.

Galaxy wrappers for SARTools (Statistical Analysis of RNA-Seq Tools)

Analyses combining ATAC-seq, RRBS, and RNA-seq data for purple urchins

Enhanced volcano plot using edgeR data

some scripts to process transcriptomics and Chip-seq data

Methods overview with scripts looking at mtDNA and haplogroup association with CPTAC LUAD study.

RNA-Seq Data Analysis in R: From Raw Counts to Differential Expression Analysis

Personalized, annotated code for anyone working with RNA-seq data.

RNA sequencing processing and analysis to find differential expression