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Next-generation Sequencing

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....

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Related Experiment Video

Updated: Nov 22, 2025

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Published on: April 11, 2016

PM4NGS, a project management framework for next-generation sequencing data analysis.

Roberto Vera Alvarez¹, Lorinc Pongor², Leonardo Mariño-Ramírez³

¹Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, 8900 Rockville Pike, NIH, Bethesda, MD 20894, USA.

|January 7, 2021

Summary

This summary is machine-generated.

PM4NGS is an open-source framework simplifying next-generation sequencing (NGS) data analysis. It standardizes project structures and integrates bioinformatics tools, making complex workflows accessible for researchers without extensive computational biology experience.

Keywords:

ChIP-Seq ChIP-exo FAIR, RNA-Seq NGS pipelines NGS sequence analysis open source frameworks

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

Published on: October 5, 2018

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Last Updated: Nov 22, 2025

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Published on: April 11, 2016

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

Published on: October 5, 2018

Area of Science:

Computational Biology
Bioinformatics
Genomics

Background:

Next-generation sequencing (NGS) data analysis requires complex computational workflows for reproducibility and scalability.
Workflow languages, managers, and container technologies aid in cross-platform data analysis pipeline execution.

Purpose of the Study:

To introduce PM4NGS, a project management framework for NGS data analysis.
To simplify NGS data analysis for researchers lacking bioinformatics expertise.

Main Methods:

PM4NGS provides automatic directory/file structure creation.
Integrates bioinformatics tools via Docker or Bioconda.
Utilizes CWL for data analysis pipelines and Jupyter notebooks for reporting.

Main Results:

Demonstrated 3 pipelines for RNA-Seq, ChIP-Seq, and ChIP-exo data analysis.
Framework is installable and configurable on personal computers, including Windows 10 with WSL.
Facilitates use by non-bioinformaticians.

Conclusions:

PM4NGS reduces the gap between experimental researchers and data analysis workflows.
The framework enhances accessibility and usability of NGS data analysis.
Open-source documentation is available at https://pm4ngs.readthedocs.io/.