kartzz/ngs-bioimage repository overview

This Docker image provides a comprehensive bioinformatics pipeline for processing next-generation sequencing (NGS) data, using the popular tools bwa, samtools, bcftools, fastqc, and others. The pipeline performs a series of steps including downloading sequencing data, performing quality control, aligning reads to a reference genome, processing the alignment data into BAM format, and finally calling variants. All the tools and necessary files are pre-installed, making this image ideal for bioinformaticians working with NGS data

Key Features:

Base Image: Ubuntu 22.04

Pre-installed Tools:

bwa (for alignment)

samtools (for BAM processing)

bcftools (for variant calling)

fastqc (for quality control)

sra-toolkit (for downloading sequencing data)

default-jre (Java Runtime Environment for certain bioinformatics tools)

openssl (for secure file handling) Genome Reference: GRCh38 (Human reference genome)

Custom Pipeline:

Data Download: FastQ files from NCBI SRA using fasterq-dump.

Quality Control: fastqc for assessing the quality of raw sequencing data.

Alignment: Aligns paired-end reads to the GRCh38 reference genome using bwa.

BAM Processing: Converts SAM files to BAM, sorts, and indexes using samtools.

Variant Calling: Uses bcftools for calling variants from aligned BAM files.

Default Workflow:

Downloads paired-end FastQ files for specified SRR accessions.

Performs a quality check with fastqc on both FastQ files.

Aligns the reads to the human genome (GRCh38) using bwa mem.

Converts the resulting SAM files to sorted BAM files, and indexes them with samtools.

Performs variant calling using bcftools and generates VCF files. Default Workflow:

Downloads paired-end FastQ files for specified SRR accessions.

Performs a quality check with fastqc on both FastQ files.

Aligns the reads to the human genome (GRCh38) using bwa mem.

Converts the resulting SAM files to sorted BAM files, and indexes them with samtools.

Performs variant calling using bcftools and generates VCF files.

Customizable:

Thread Configuration: The number of threads used for multi-threaded tools is configurable via the THREADS environment variable (default is 4 threads).

Input: Users can modify the SRR accessions in the script to specify different sequencing datasets.

Command: The default command runs the pipeline, but users can customize it by editing pipeline.sh. To run the pipeline:

docker run -v /path/to/data:/data <image_name>

This Docker image provides an easy-to-use solution for automating the processing and analysis of NGS data, simplifying the workflow for researchers and bioinformaticians.