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Quality Control, Mapping and Reads Count for RNA-Seq Analysis

Shell 14.16% R 85.84%
trimmomatic star quality-control rna-seq-analysis rna-seq-pipeline mapping rnaseqpipeline rna-seq-mapping rna-seq-qc bioinformatics bioinformatics-pipeline rna-seq-aligner multiqc fastqc hisat2 htseq-count featurecounts

baqcom's Introduction

BAQCOM - Bioinformatics Analysis for Quality Control and Mapping

Quality Control (Trimmomatic), Mapping (STAR | HISAT2) and Counting Reads (HTSeq | featuresCount)



BAQCOM is an user-friendly pipeline which implements five automated pipelines for RNA-Seq analysis using Trimmomatic for QC, STAR or HISAT2 for mapping and, HTSeq or featuresCount for counting reads.


baqcom-steps-white

STEP.1 - Download this repository to a preference path:

Git is required

 git clone https://github.com/hanielcedraz/BAQCOM.git
 cd BAQCOM
 chmod +x install.sh
 ./install.sh


STEP.2 - Install R

To install R Access CRAN website

STEP.3 - Install MultiQC and HTSeq-count:

MultiQC: If you would like to use multiqc analysis, please install it.
Installation: If pip is not installed, please install as follow:

	wget https://bootstrap.pypa.io/get-pip.py -O get-pip.py
	python get-pip.py

You can install MultiQC from PyPI using pip as follow:

	pip install multiqc

More information, please access MultiQC website

HTSeq-count:

HTSeq is available from the Python Package Index (PyPI):
	To use HTSeq, you need Python 2.7 or 3.4 or above (3.0-3.3 are not supported), together with:
		NumPy, a commonly used Python package for numerical calculations
		Pysam, a Python interface to samtools. 
	To make plots you will need matplotlib, a plotting library. 

You can install HTSeq-count using pip:

	pip install HTSeq
	
If HTSeq is already installed you need to upgrade it
	pip install HTSeq --upgrade

In addition you need to upgrade numpy
	pip install numpy --upgrade

or following the source documentation



STEP.4 - Install PigZ:

To speed up your analysis results, install the pigz.

Centos

sudo yum install pigz

Ubuntu

sudo apt install pigz



Examples

You can find some command line examples here


Differential Expression Gene

You will find some script to analyze differential expression genes here

baqcom's People

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