ny-shao / miRNA_pipeline_for_miRanalyzer

A pipeline of miRNA by using miRanalyzer

miRNA_pipeline_for_miRanalyzer

A pipeline of miRNA by using miRanalyzer

Overview

Here is the pipeline I use to analyze miRNA-seq data by miRanalyzer.

Now it support:

• cut adapter
• run FastQC as step of quality control
• align sequences to annotation databases
• predict novel miRNAs
• summarize the results and generate the count table of the entries

Requirement

• ruffus
• cutadapt

• Bowtie
• FastQC

• The standalone version of miRanalyzer
• plyr An R package for data manipulation.

Install these softwares or packages and make sure the softwares are in $PATH.

Installation

Put all script in bin folders to a place in $PATH or add these folders to $PATH.

Usage

Firstly, you need to edit the config.yaml file to fit your need, then run:

nohup python pipline.py config.yaml &

For the organization of projects, I generally follow this paper: A Quick Guide to Organizing Computational Biology Projects. So project_dir/data_dir/fastq are the folder contains raw fastq files, while project_dir/output_dir folder are the results. The position of scripts in project_script doesn't matter at all. But I prefer to put them under project/script/miRanalyzer folder.

When the major part of the pipeline finishs, then run:

Rscript mergeStats.R config.yaml
Rscript mergeTables.R config.yaml

to summarize the final results. The items in stats_tags of config.yaml will be summarized.