Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

https://github.com/runsheng/trackcluster

An analysis pipeline for Nanopore direct-RNA sequencing
https://github.com/runsheng/trackcluster

bioinformatics longread nanopore rna-seq

Last synced: about 2 months ago
JSON representation

An analysis pipeline for Nanopore direct-RNA sequencing

Lists

README 

        
# TrackCluster

![PyPI](https://img.shields.io/pypi/v/trackcluster?color=green)



Trackcluster is an isoform calling and quantification pipeline for long RNA/cDNA reads.



## Table of Contents



- [Overview](#overview)

- [Requirements](#requirements)

- [Scripts](#scripts)

- [Walkthrough](#walkthrough)



####

Hint: the ongoing development can be found in the ["dev"](https://github.com/Runsheng/trackcluster/tree/dev) branch.



## Overview

A pipeline for reference-based isoform identification and quantification using long reads. This pipeline was designed to use **only** long and nosisy reads to make a valid transcriptome. An indicator for the intact 5' could be very helpful to the pipeline, i.e, the splicing leader in the mRNA of nematodes. 



The major input/output for this pipeline is "bigg"--["bigGenePred"](https://github.com/Runsheng/trackcluster/blob/master/test/bigGenePred.as) format. 



## Requirements



1. developed on python 3.9, tested on python 3.6 and above (or 2.7.10+), should work with most of the py3 versions

2. samtools V2.0+ , bedtools V2.24+  and minimap2 V2.24+ in your $PATH

```bash

# install the external bins with conda

conda install -c bioconda samtools

conda install -c bioconda bedtools

conda install -c bioconda minimap2

```



## Installation

```bash

# use pip from pypi

pip install trackcluster

# or pip from source code for the latest version

git clone https://github.com/Runsheng/trackcluster.git

pip install ./trackcluster

```



## Recommendations

1. UCSC Kent source tree (for generating binary track), used only in bigg2b.py



## Scripts

All scripts can be run directly from shell after pip installation.

- **trackrun.py**: the main script for trackcluser run

- **bam2bigg.py**: convert the mapped read from the bam file, to bigg track format

- **gff2bigg.py**: convert the isoform annotation in gff3 to bigg format 

- bigg2b.py: convert the bigg track into binary format for better loading in IGV/UCSC

- biggmutant.py: change the value of one column in a bigglist



## Walkthrough

```bash

# test if all dependencies are installed

trackrun.py test --install



# prepare the reference annotation bed file from gff file

# tested on Ensembl, WormBase and Arapost gff

gff2bigg.py -i ensemblxxxx.gff3 -o ref.bed 

# WormBase full gff contains too many information, need to extract the lines from WormBase only

cat c_elegans.PRJNA13758.WS266.annotations.gff3 |grep WormBase > ws266.gff

gff2bigg.py -i ws266.gff -o ref.bed

# the ref.bed can be sorted to speed up the analysis

bedtools sort -i ref.bed > refs.bed # refs.bed contains the sorted, know transcripts from gff annotation



# generate the read track from minimap2 bam file

bam2bigg.py -b group1.bam -o group1.bed

bam2bigg.py -b group2.bam -o group2.bed



# merge the bed file and sort

cat group1.bed group2.bed > read.bed

bedtools sort -i read.bed > reads.bed



# Examples for running commands:

trackrun.py clusterj -s reads.bed -r refs.bed -t 40 # run in junction mode, will generate the isoform.bed

trackrun.py count -s reads.bed -r refs.bed -i isoform.bed # generate the csv file for isoform expression

# alternative for cluster

trackrun.py cluster -s reads.bed -r refs.bed -t 40 # run in exon/intron intersection mode， slower, will generate the isoform.bed



# the post analysis could include the classification of novel isoforms

trackrun.py desc --isoform isoform.bed --reference ref.bed # generate the description for each novel isoform

# this part can be run directly on reads, to count the frequency of splicing events in reads, like intron_retention

trackrun.py addgene -r ref.bed -s reads.bed # will generate reads_gene.bed

trackrun.py desc --isoform reads_gene.bed --reference ref.bed # will generated reads_desc.txt and reads_class12.txt 



```



## Citation

Please kindly cite our paper for using trackcluster in your work.



Li, R., Ren, X., Ding, Q., Bi, Y., Xie, D. and Zhao, Z., 2020. Direct full-length RNA sequencing reveals unexpected transcriptome complexity during *Caenorhabditis elegans* development. **Genome research**, 30(2), pp.287-298.