Showing 10 open source projects for "parallel computing"

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  • 1

    MarDRe

    MapReduce-based tool to remove duplicate DNA reads

    ...Instead, MarDRe takes advantage of the MapReduce programming model to significantly improve ParDRe performance on distributed systems, especially on cloud-based infrastructures. Written in pure Java to maximize cross-platform compatibility, MarDRe is built upon the open-source Apache Hadoop project, the most popular distributed computing framework for Big Data processing.
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  • 2

    HSRA

    Hadoop spliced read aligner for RNA-seq data

    HSRA is a MapReduce-based parallel tool for mapping reads from RNA sequencing (RNA-seq) experiments. RNA-seq analyses typically begin by mapping reads to a reference genome in order to determine the location from which the reads were originated, which is a very time-consuming step. This tool allows bioinformatics researchers to efficiently distribute their mapping tasks over the nodes of a cluster by combining a fast multithreaded spliced aligner (HISAT2) with Apache Hadoop, which is a distributed computing framework for scalable Big Data processing. ...
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  • 3

    SAT-Assembler

    Scalable and accurate targeted gene assembly for large-scale NGS data

    ...It recovers genes from gene families of particular interest to biologists with high coverage, low chimera rate, and extremely low memory usage compared with exiting gene assembly tools. Moreover, it is naturally compatible with parallel computing platforms.
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  • 4

    parSRA

    Portable Framework for the Parallel Execution of Short Read Aligners

    ...It uses the following techniques in order to improve scalability: 1) a fast splitting of the input reads using the FUSE kernel module available in most of current Linux distributions; 2) a balanced on-demand distribution of the reads based on the shared locks of UPC++, an extension of C++ for parallel computing that follows the Partitioned Global Address Space (PGAS) paradigm. parSRA is portable as its configuration file allows the users to parallelize the execution of existing SRA tools without the need to modify the source code of parSRA or the aligner.
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  • 5

    Ezys

    Ezys 3D medical image registration program

    Ezys is a non-linear 3D medical image registration program. Ezys fully exploits the parallel computing power of inexpensive commercial graphics processing units (GPU), resulting in a very fast and accurate program capable of running on desktop PCs and even some laptops. On these systems, non-linear image registrations take less than a minute to complete. Ezys implements a diffeomorphic inverse consistent image registration algorithm with a demons-style regularization based on a non-parametric free form deformation model. ...
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  • 6

    PPSeq: Parallel NGS Analysis

    Parallel Processing for Next-Generation Sequencing (NGS) Analysis

    High-throughput next generation sequencing (NGS) technology has quickly emerged as a powerful tool in many aspects of biomedical research. However, along with its rapid development, the data magnitude and analysis complexity for NGS far exceed the capacity and capability of traditional small-scale computing facilities, such as multithreading algorithms on standalone workstations. To address this issue, here we present a solution using the ever-increasing supply of processing power by massive parallel processing (MPP) systems.
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  • 7

    GENIE (GEne-geNe IntEraction)

    GPU based Parallel Gene-Gene Interaction Analysis

    Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic...
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  • 8

    PASHA: Parallelized Short Read Assembly

    One of the fastest parallel short read assemblers for large genomes.

    PASHA is a parallel short read assembler for large genomes using de Bruijn graphs. Taking advantage of both shared-memory multi-core CPUs and distributed-memory compute clusters, PASHA has demonstrated its potential to perform high-quality de-novo assembly of large genomes in reasonable time with modest computing resources. Our evaluation using three small real paired-end datasets shows that PASHA is able to produce better assemblies with comparable genome coverage and mis-assembly rates compared to three leading assemblers: Velvet, ABySS and SOAPdenovo. ...
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  • 9
    Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
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  • 10
    ProteinFinder - a C language parallel computing engine for tandem protein mass spectrometry database search. ProteinFinder is interfaced with MySQL relational database MassSpec that hosts the experimental data, predicted databases, and search results.
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