kahvecirem/next-generation-sequencing_ngs

Next Generation Sequencing (NGS) Analysis via Linux

Next Generation Sequencing (NGS) Analysis

This repository contains code for processing and analyzing Next Generation Sequencing (NGS) data. If you're working with NGS data on a Linux system and want to share your code on GitHub, follow the steps outlined below.

Linux Commands:

To work with NGS data on Linux, you'll need to familiarize yourself with essential Linux commands. Here are some sample commands and explanations:

1. Navigate to the Data Directory:

   cd /path/to/your/data

   Change the current directory to the location where your NGS data is stored.

2. List Files:

   ls

   View the list of files in the current directory.

3. View Data Files:

   cat your_file.fastq

   View the contents of a FASTQ data file.

4. Perform Data Analysis (e.g., Aligning with BWA):

   bwa mem reference.fasta sample.fastq > aligned.sam

   Use BWA for aligning NGS reads to a reference genome, generating an SAM file.

5. Convert SAM to BAM Format (Using SAMtools):

   samtools view -bS aligned.sam > aligned.bam

   Convert the SAM file to BAM format for easier manipulation and storage.

Markdown Documentation:

Documentation is crucial when sharing your NGS code on GitHub. Use Markdown to create a well-structured README file:

# NGS Analysis

This repository contains code for Next Generation Sequencing (NGS) data analysis on a Linux platform.

## Installation

To run this code, you'll need the following prerequisites:

- Linux operating system
- BWA (Burrows-Wheeler Aligner)
- SAMtools
- And more

You can install the requirements using the following commands:

```bash
sudo apt-get install bwa
sudo apt-get install samtools

Usage

To process and analyze your data, follow these steps:

1. Navigate to your data directory:

   cd /path/to/your/data

2. Align the data:

   bwa mem reference.fasta sample.fastq > aligned.sam

3. Convert the SAM file to BAM format:

   samtools view -bS aligned.sam > aligned.bam

---

Next Generation Sequencing (NGS) Analysis

In this guide, we'll walk you through the process of performing NGS analysis on a Linux system using ready-made data. This involves downloading NGS data, aligning it to a reference genome, and performing basic analysis.

Downloading Sample Data

To get started, we'll need some sample NGS data. For this example, we'll use publicly available data from the National Center for Biotechnology Information (NCBI) GenBank. You can download sample data like this:

# Example: Download sample E. coli data
wget -r ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/bacteria/Escherichia_coli/all_assembly_versions/

Installing NGS Analysis Tools

Before we begin the analysis, we need to install the necessary tools. For this example, we'll use the Burrows-Wheeler Aligner (BWA) for alignment and SAMtools for data manipulation. You can install these tools as follows:

# Install BWA
sudo apt-get install bwa

# Install SAMtools
sudo apt-get install samtools

Performing NGS Analysis

Now that we have the data and tools in place, let's proceed with the analysis.

Step 1: Index the Reference Genome

Before aligning the data, we need to index the reference genome. Replace reference.fasta with the actual reference genome file name.

bwa index reference.fasta

Step 2: Perform Sequence Alignment

Next, we'll align the NGS data to the reference genome using BWA. Replace sample.fastq with the actual NGS data file name.

bwa mem reference.fasta sample.fastq > aligned.sam

Step 3: Convert SAM to BAM

To make the data more manageable, we'll convert the SAM file to BAM format using SAMtools.

samtools view -bS aligned.sam > aligned.bam

Analyzing the Results

With the data aligned and in BAM format, you can proceed to analyze it further. You can use various NGS analysis tools to identify genetic variants, calculate coverage, and more.

Conclusion

This guide provides a basic overview of performing NGS analysis on a Linux system using ready-made data. Keep in mind that real NGS analyses can be more complex and tailored to specific research objectives. Always ensure compliance with legal and ethical considerations when working with NGS data.

For more advanced analyses, refer to the documentation of the specific tools and workflows relevant to your research project.

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Contributing

If you'd like to contribute to this project, please submit a pull request.

License

This code repository is licensed under the MIT License.

Save this Markdown file as `README.md` in the root directory of your GitHub repository. It will serve as the main documentation for your project.

Customize this template to suit your specific NGS analysis needs, and ensure that your code is well-documented, efficient, and ready for sharing with the NGS community on GitHub.