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).
This pipeline resulted from the observation that potential artifacts derived from sequencing errors and/or data processing could result in an overestimation of abundance and diversity of miRNA isoforms. Paired end sequencing improves isomiR calling in small RNA sequencing data. Internal variation isomiR calls are frequent artifacts in single read sequencing data. Internal sequence variant isomiRs in single read sequencing mode may be false positives. See additional detail in the original publication here
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.
See additional details on the code here. The workflow of the pipeline is described in the following image. 
XICRA will require python v3.6 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 here.
We encourage you to install XICRA and all dependencies using the conda environment we created and following these instructions.
Unfortunately, a couple of executables are not available neither as a conda or pip packages. These packages are miraligner and sRNAbench. We have generated a shell script to retrieve and include within your conda environment.
To create a new conda environment, install third party software, install XICRA and missing dependencies, do as follows:
## clone repo
git clone https://github.com/HCGB-IGTP/XICRA.git
## move to folder
cd XICRA
## create conda environemt
conda env create -n XICRA -f XICRA_pip/devel/conda/environment.yml
## activate
conda activate XICRA
## install latest python code
pip install XICRA
## install missing software
sh XICRA_pip/XICRA/config/software/installer.shTo check everything is fine, try executing the config module:
XICRA configOn the other hand, if you might have already installed software and available within your path, you might only need to install it using the XICRA pip module. We encourage you to installed it within a python environment. See as an example the description here
We additionally provide a supplementary R package for parsing and plotting some XICRA results. See additional details here.
Install it in R using:
# Install XICRA.stats version from GitHub:
# install.packages("devtools")
devtools::install_github("HCGB-IGTP/XICRA.stats")XICRA is the name in Catalan for a small cup of coffee or chocoate. Also, it was used as a small measure of milk, oil or wine (125 ml). See additional details here: https://ca.wikipedia.org/wiki/Xicra
Una xicra és tassa petita, més aviat alta i estreta, emprada expressament per a prendre la xocolata desfeta o cafè. També és una unitat de mesura de volum per a líquids que es feia servir a Catalunya per a l'oli, vi, o llet.
In this repository we provide supplementary information for the original paper describing the method. See additional details in folder BMC_bioinformatics_paper or here
For a full documentation and details visit Read the Docs site here.
See a brief example on how to install and run XICRA here
MIT License
Copyright (c) 2020 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/
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