Tag: Parallel

CUDA-EC 1.02 – Fast Parallel Error Correction tool for Short Reads

CUDA-EC 1.02

:: DESCRIPTION

CUDA-EC is a scalable parallel algorithm for correcting sequencing errors in high-throughput short-read data so that error-free reads can be available before DNA fragment assembly.

::DEVELOPER

Haixiang Shi

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ compiler
  • NVIDIA CUDA SDK

:: DOWNLOAD

 CUDA-EC

:: MORE INFORMATION

Citation

J Comput Biol. 2010 Apr;17(4):603-15. doi: 10.1089/cmb.2009.0062.
A parallel algorithm for error correction in high-throughput short-read data on CUDA-enabled graphics hardware.
Shi H, Schmidt B, Liu W, Müller-Wittig W.

ALEXA-Seq 1.17 – Alternative Expression Analysis by massively parallel RNA Sequencing

ALEXA-Seq 1.17

:: DESCRIPTION

ALEXA-Seq is a method for using massively parallel paired-end transcriptome sequencing for ‘alternative expression analysis’.

::DEVELOPER

ALEXA-Seq Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • Virtual Machines

:: DOWNLOAD

 ALEXA-Seq

:: MORE INFORMATION

Citation:

Malachi Griffith, et al.
Alternative expression analysis by RNA sequencing.
Nature Methods. 2010 Oct;7(10):843-847.

shellfish – Parallel PCA and data processing for Genome-wide SNP data

shellfish

:: DESCRIPTION

shellfish carries out a variety of tasks related to principal component analysis of genome-wide SNP data. Unlike other available software, PCA computations can be carried out in parallel (both on a computing cluster running the Sun Grid Engine, and also in the simple case of a machine with multiple processors). In addition to the PCA calculations, it automates the process of data subsetting and allele-matching, using plink and gtool for file format interconversion where necessary. The aim is that tasks that would otherwise require a complex series of shell commands and/or work in R, can be carried out with a single, straightforward, command.

::DEVELOPER

Dan Davison

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • MacOsX / Linux
  • Python

:: DOWNLOAD

 shellfish

:: MORE INFORMATION

JESAM 0.8.1 – Parallel Processing DNA Sequence Comparison and Clustering

JESAM 0.8.1

:: DESCRIPTION

JESAM is a software components to create and publish EST alignments and clusters.

::DEVELOPER

Jeremy Parsons

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Java

:: DOWNLOAD

  JESAM

:: MORE INFORMATION

Citation

Bioinformatics. 2000 Apr;16(4):313-25.
JESAM: CORBA software components to create and publish EST alignments and clusters.
Parsons JD, Rodriguez-Tomé P.

Pasqual 1.0 – Parallel de Novo Genome Sequence Assembler

Pasqual 1.0

:: DESCRIPTION

PASQUAL (PArallel SeQUence AssembLer) is designed for shared memory parallelism, using OpenMP due to its good tradeoff between performance and programmer productivity. Shared memory parallelism has become mainstream with the widespread production of multicore commodity processors. For PASQUAL we follow the OLC approach and use a careful combination of tailored algorithms and data structures to obtain high-quality solutions.

::DEVELOPER

Bader HPC Lab @ GeorgiaTech

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 Pasqual

:: MORE INFORMATION

Citation

Xing Liu, Pushkar R. Pande, Henning Meyerhenke, and David A. Bader.
PASQUAL: A Parallel de novo Assembler for Next Generation Genome Sequencing.
Submitted for journal publication, 2011.

PTS 1.0.2 – Parallel Tagged Sequencing

PTS 1.0.2

:: DESCRIPTION

PTS (Parallel Tagged Sequencing) is a small collection of programs concerned with parallel sequencing of multiple samples on the 454 platform. untag supports Parallel Tagged Sequencing by sorting sequences according to their tags and by removing those tags when producing output files (in FASTA or SFF format) for downstream processing with standard 454 or other assembly software.

::DEVELOPER

Department of Genetics/Bioinformatics – Max Planck Institut

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 PTS

:: MORE INFORMATION

ParaSAM – Parallel Version of the SAM Algorithm

ParaSAM

:: DESCRIPTION

ParaSAM is a high performance parallel processing implementation of the SAM (Significance Analysis of Microarrays) algorithm. The permutations are divided across the multiple nodes. The computational workload is divided among multiple CPUs and the main memory of all participating computers is utilized to avoid caching operations to the disk, which significantly decrease algorithm execution time.

::DEVELOPER

Ashok Sharma & Richard A. McIndoe, Ph.D.

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

ParaSAM

:: MORE INFORMATION

If you don’t want to install ParaSAM locally, you can use a Web version here.

If you make use of the program presented here, please cite the following article:

Sharma A, Zhao J, Podolsky R, McIndoe RA: ParaSAM: A parallelized version of the significance analysis of microarrays algorithm. Bioinformatics 2010.