Small RNAseq pipeline for paired-end reads
Project description
XICRA: Small RNAseq pipeline for paired-end reads
Description
XICRA is a python pipeline developed in multiple separated modules that it is designed to take paired end fastq reads, trim adapters and low-quality base pairs positions, and merge reads (R1 & R2) that overlap. Using joined reads it describes all major RNA biotypes present in the samples including miRNA and isomiRs, tRNA fragments (tRFs) and piwi associated RNAs (piRNAs).
So far, XICRA produces a miRNA analysis at the isomiR level using joined reads, multiple software at the user selection and following a standardization procedure. Results are generated for each sample analyzed and summarized for all samples in a single expression matrix. This information can be processed at the miRNA or isomiR level (single sequence) but also summarizing for each isomiR variant type. This information can be easily accessed using the accompanied R package XICRA.stats. Although the pipeline is designed to take paired-end reads, it also accepts single-end reads.
Installation
XICRA will require python v3.7 and java (we tested in openjdk 14 2020-03-17).
The XICRA python pipeline is available in pip
and also available using conda
.
XICRA depends on multiple third party software that we have listed below.
Dependencies
Python XICRA module will install itself along some python modules dependencies (pandas, multiqc, pybedtools, biopython etc.).
But additionally, XICRA depends on third party software that we listed in the following table.
Conda environment
We encourage you to install XICRA and all dependencies using the conda
environment we created and following these instructions.
To create a new conda environment, install third party software, install XICRA and missing dependencies, do as follows:
- Get requirements file from XICRA git repo
wget https://raw.githubusercontent.com/HCGB-IGTP/XICRA/master/XICRA_pip/devel/conda/environment.yml
- Create environment named XICRA and install required packages using conda:
conda env create -f environment.yml
- Activate environment and install XICRA
## activate
conda activate XICRA
## install latest python code
pip install XICRA
- Install missing software: Unfortunately, a couple of executables are not available neither as a
conda
orpip
packages. These packages aremiraligner
,sRNAbench
and 'MINTmap'. We have generated abash
script to retrieve and include within yourconda environment
.
## install missing software
wget https://raw.githubusercontent.com/HCGB-IGTP/XICRA/master/XICRA_pip/XICRA/config/software/installer.sh
sh installer.sh
To check everything is fine, try executing the config
module:
XICRA config
Documentation
See a full documentation, user guide and manual in here
Example
Here we include a brief example on how to use XICRA.
First, we create a python environment and will install XICRA and dependencies. See example details shown before. Then, we can test XICRA by using an example of 100 miRNA simulated and provideded within the repository as an example of simulation.
## run XICRA example
ln -s ~/BMC_bioinformatics_paper/simulation/example/reads/
## prepare reads
XICRA prep --input reads/ --output_folder test_XICRA
## join reads
XICRA join --input test_XICRA --noTrim
## create miRNA analysis
XICRA miRNA --input test_XICRA --software miraligner sRNAbench
## explore results
ls test_XICRA/report/
Documentation
For a full documentation and details visit Read the Docs site here.
See a brief example on how to install and run XICRA here
License
MIT License
Copyright (c) 2020-2022 HCGB-IGTP
See additional details here
Developed and maintained by Jose F. Sanchez-Herrero and Lauro Sumoy at HCGB-IGTP
http://www.germanstrias.org/technology-services/genomica-bioinformatica/
Citation
Sanchez Herrero, J.F., Pluvinet, R., Luna de Haro, A. et al. Paired-end small RNA sequencing reveals a possible overestimation in the isomiR sequence repertoire previously reported from conventional single read data analysis. BMC Bioinformatics 22, 215 (2021). https://doi.org/10.1186/s12859-021-04128-1
Authors
Antonio Luna de Haro (v0.1) Jose F Sanchez-Herrero (v1.0)
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