🐟 🍣 🍱 Highly-accurate & wicked fast transcript-level quantification from RNA-seq reads using selective alignment

Nanopore sequence read simulator

Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data

Technology agnostic long read analysis pipeline for transcriptomes

GET_HOMOLOGUES: a versatile software package for pan-genome analysis

Building classifiers using cancer transcriptomes across 33 different cancer-types

The START App: R Shiny Transcriptome Analysis Resource Tool

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

Merging, Annotation, Validation, and Illustration of Structural variants

De novo clustering of long transcript reads into genes

A Python library to visualize and analyze long-read transcriptomes

Reference-free reconstruction and error correction of transcriptomes from Nanopore long-read sequencing

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

Evolutionary Transcriptomics with R

Genome Annotation Without Nightmares

de novo assembly of RNA-seq data using ABySS

A genome annotation pipeline that use short and long sequencing reads alignments from animal genomes

Demultiplexing and debarcoding tool designed for LR-Split-seq data.

A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq

Annotated Genome Optimization Using Transcriptome Information

Merge transcriptome read-to-genome alignments into non-redundant transcript models

Software for measuring poly(A) tail length and 3′-end modifications using a high-throughput sequencer

Derives consensus sequences from a set of long noisy reads by clustering and error correction.

TrendCatcher is an open source R-package that allows users to systematically analyze and visualize time course data. Please cite "Temporal transcriptomic analysis using TrendCatcher identifies early and persistent neutrophil activation in severe COVID-19" by Xinge Wang et al published in JCI Insight (2022) - https://insight.jci.org/articles/view/157255

TreeExp 2.0: Toolbox for analyzing expression evolution based on RNA-seq count data

Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chromatin accessibility and cis-regulatory chromatin contacts.

Emending Alignment of Spliced Transcript Reads

AnceTran2.0: R package for transcriptome evolution analysis based on RNA-seq expression data or ChIP-seq TF-binding data

Multilayer modelling of the human transcriptome and biological mechanisms of complex diseases and traits

A highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.