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Next-generation Sequencing

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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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RNA-seq

RNA-seq

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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...

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Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

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Published on: May 9, 2017

CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing.

Samuel V Angiuoli¹, Malcolm Matalka, Aaron Gussman

¹Institute for Genome Sciences (IGS), University of Maryland School of Medicine, Baltimore, Maryland, USA. angiuoli@umiacs.umd.edu

BMC Bioinformatics

|September 1, 2011

Summary

This summary is machine-generated.

Cloud Virtual Resource (CloVR) is a desktop application simplifying automated sequence analysis for microbial genomics. This portable virtual machine (VM) enables push-button analysis on local or cloud resources, making complex bioinformatics accessible.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Next-generation sequencing (NGS) necessitates user-friendly, portable, and scalable bioinformatics tools.
Cloud computing offers on-demand infrastructure for high-throughput data analysis.

Purpose of the Study:

To introduce Cloud Virtual Resource (CloVR), a desktop application for automated sequence analysis.
To enable efficient utilization of local and cloud computing resources for bioinformatics workflows.

Main Methods:

CloVR is a portable virtual machine (VM) providing automated analysis pipelines for microbial genomics (16S, whole genome, metagenome).
The VM runs on personal computers with minimal installation, leveraging local resources.
CloVR supports remote cloud computing for enhanced performance in large-scale processing.

Main Results:

CloVR facilitates automated, push-button sequence analysis.
Demonstrated successful automatic processing of NGS data on multiple cloud platforms.
The VM integrates local and cloud resources for scalable bioinformatics.

Conclusions:

CloVR reduces the complexity of implementing advanced bioinformatics protocols.
The architecture supports both local and cloud-based high-throughput data processing.
Lowers the barrier to entry for complex genomic data analysis.