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Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

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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.
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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

STORMSeq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.

Konrad J Karczewski¹, Guy Haskin Fernald¹, Alicia R Martin¹

¹Biomedical Informatics Training Program, Stanford University School of Medicine, Stanford, California, United States of America ; Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.

|January 24, 2014

Summary

This summary is machine-generated.

STORMSeq offers a user-friendly, cloud-based solution for personal genome analysis. This open-source tool democratizes genomics by enabling customizable read mapping and variant calling without extensive technical expertise.

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Personal genome sequencing data is increasingly accessible, leading to democratized genomics.
Existing read mapping and variant calling software require technical expertise and may not meet user customization needs.

Purpose of the Study:

To introduce STORMSeq, a scalable, open-source tool for read mapping, cleaning, variant calling, and annotation.
To provide a user-friendly, graphical interface for cloud-based personal genome analysis.

Main Methods:

STORMSeq utilizes a modular system for read mapping, cleaning, and variant calling/annotation.
The platform is cloud-based, accessible via Amazon EC2, and does not require a parallel computing environment.

Main Results:

STORMSeq provides a customizable and modular solution for personal genomic data analysis.
Processing a full exome sequence costs approximately $2 and takes 5-10 hours.
Processing a whole genome sequence costs approximately $30 and takes 3-8 days.

Conclusions:

STORMSeq democratizes genomics by offering an accessible, cost-effective, and user-friendly platform for personal genome analysis.
The open-source and open-access nature of STORMSeq promotes wider adoption and customization in personal genomics.