Displaying 1 to 6 from 6 results

rna-seq-snakemake - Snakemake based pipeline for RNA-Seq analysis

  •    R

Inputs to all snakefiles are specified using a config.py, and generally is as simple as specifiying the directory containing all *.fq/*.fq.gz/*.fastq.gz/*.sra files.

needlestack - Multi-sample somatic variant caller

  •    R

Warning: development in progress, unreliable results warranted. Please wait upcoming publication before using it in production.

dropSeqPipe - A SingleCell RNASeq pre-processing pipeline built on snakemake

  •    R

This pipeline is based on snakemake and the dropseq tools provided by the McCarroll Lab. It allows to go from raw data of your Single Cell RNA seq experiment until the final count matrix with QC plots along the way. This is the tool we use in our lab to improve our wetlab protocol as well as provide an easy framework to reproduce and compare different experiments with different parameters.

irap - integrated RNA-seq Analysis Pipeline

  •    R

iRAP is a flexible RNA-seq analysis pipeline that allows the user to select and apply their preferred combination of existing tools for mapping reads, quantifying expression and testing for differential expression. Depending upon the application, iRAP can be used to quantify expression at the gene, exon or transcript level. Please consult the wiki (https://github.com/nunofonseca/irap/wiki) for further information.




drake-manual - The user manual for the drake R package

  •    R

This is the development repository of the drake R package user manual, hosted here. Please feel free to discuss on the issue tracker and submit pull requests to add new examples and update old ones. The environment for collaboration should be friendly, inclusive, respectful, and safe for everyone, so all participants must obey this repository's code of conduct.

zUMIs - zUMIs: A fast and flexible pipeline to process RNA sequencing data with UMIs

  •    R

zUMIs is a fast and flexible pipeline to process RNA-seq data with (or without) UMIs. The input to this pipeline is simply fastq files. In the most common cases, you will have a read containing the cDNA sequence and other read(s) containing UMI and Cell Barcode information. Furthermore, you will need a STAR index for your genome and GTF annotation file.