Reference mapping for single-cell genomics

Reference-guided transcript discovery and quantification for long read RNA-Seq data

Analyze your RNA sequencing data without writing a single line of code

Visual self-service analytics platform for big omics data.

This repository contains R code, with which you can create 3D UMAP and tSNE plots of Seurat analyzed scRNAseq data

An open RNA-Seq data analysis pipeline tutorial with an example of reprocessing data from a recent Zika virus study

integrated RNA-seq Analysis Pipeline

Enjoy your transcriptomic data and analysis responsibly - like sipping a cocktail

Scalable RNA-seq analysis

Rails/Docker application for the Broad Institute's single cell RNA-seq data portal

pcaExplorer - Interactive exploration of Principal Components of Samples and Genes in RNA-seq data

GREIN : GEO RNA-seq Experiments Interactive Navigator

Tutorials, workflows, and convenience scripts for Single Cell Portal

Small non-coding RNA annotation Pipeline Optimized for rRNA- and tRNA-Derived Small RNAs

Clustering cells from single cell RNA seq assays

SNP-free RNA editing Identification Toolkit

Data-driven Network-based Bayesian Inference of Drivers

The pmartR R package provides functionality for quality control, normalization, exploratory data analysis, and statistical analysis of mass spectrometry (MS) omics data, in particular proteomic (either at the peptide or the protein level), lipidomic, and metabolomic data.

The Read Origin Protocol (ROP) is a computational protocol that aims to discover the source of all reads, including those originating from repeat sequences, recombinant B and T cell receptors, and microbial communities.

UNDER DEVELOPMENT--- Analysis of long non-coding RNAs from RNA-seq datasets