Pico Computing Demonstrates Bioinformatics Acceleration at SC 2011

Pico's SC5 FPGA cluster reduces short read sequencing from 6 1/2 hours to just one minute

Seattle, WA (PRWEB) November 09, 2011

Pico Computing will be demonstrating an FPGA implementation of BFAST resulting in a 350X acceleration over a software-only implementation running on two quad core Intel Xeon processors. The 350X acceleration was achieved using 8 Pico M-503 FPGA modules in their SC5 SuperCluster chassis. The BFAST algorithm is primarily used in short read genome mapping.

Read more: http://www.sfgate.com/cgi-bin/article.cgi?f=/g/a/2011/11/09/prweb8945226.DTL#ixzz1dyI5LQs

CloVR

"Background

Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software.

Results

We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms.

Conclusion

The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing."

http://clovr.org/

NGS: videos and tutorials, papers et al.

http://mged12-deep-sequencing-analysis.wikispaces.com/file/view/BrooksAN_Intro_DeepSequencing.pdf

ppt tutorial

http://www.slideshare.net/thomaskeane/eccb-2010-nextgen-sequencing-tutorial

Comparative analysis of algorithms for next-generation sequencing read alignment

Abstract

Motivation: The advent of next-generation sequencing (NGS) techniques presents many novel opportunities for many applications in life sciences. The vast number of short reads produced by these techniques, however, pose significant computational challenges. The first step in many types of genomic analysis is the mapping of short reads to a reference genome, and several groups have developed dedicated algorithms and software packages to perform this function. As the developers of these packages optimize their algorithms with respect to various considerations, the relative merits of different software packages remain unclear. However, for scientists who generate and use NGS data for their specific research projects, an important consideration is choosing the software that is most suitable for their application.

Results: With a view to comparing existing short read alignment software, we develop a simulation and evaluation suite, SEAL, which simulates NGS runs for different configurations of various factors, including sequencing error, indels, and coverage. We also develop criteria to compare the performances of software with disparate output structure (e.g., some packages return a single alignment while some return multiple possible alignments). Using these criteria, we comprehensively evaluate the performances of Bowtie, BWA, mr- and mrsFAST, Novoalign, SHRiMP and SOAPv2, with regard to accuracy and runtime.

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