Showing 4 open source projects for "ace-step"

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  • 1

    HSRA

    Hadoop spliced read aligner for RNA-seq data

    ...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. HSRA currently supports single-end and paired-end read alignments from FASTQ/FASTA datasets. ...
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  • 2

    Cell Culture

    Rediscover the Simplicity http://www.atgclabs.com/

    ...Cell Culture manages activities related to the growth and maintenance of cell lines, provides stable cell lines development and incorporates laboratory methods facilitating faster and more accurate inventory lifecycle management: from the procurement of cell lines and request processing to tracking of tubes and other items in the laboratories. Cell Culture provides easy to follow, step-by-step protocols, with tips and notes and is of interest to researchers, technicians and process engineers using cell culture within the biotechnology, biomedicine and pharmaceutical industries.
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  • 3

    SuRankCo

    Supervised Ranking of Contigs in de novo Assemblies

    ...Renard (http://www.biomedcentral.com/1471-2105/16/240/abstract) PLEASE NOTE, it is recommended to read the paper and the readme.txt file before using SuRankCo. Update Jun2015: * Minor changes to enable BAM support. Update Feb2014: * Added support for FASTA/SAM assemblies in addition to ACE/FASTQ(QUAL). NOTE: features of FASTA/SAM assemblies do not include BaseCount, BaseSeqmentCount and ContigQualities yet.
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  • 4

    iMir

    Integrated pipeline for HT miRNA-Seq data analysis

    Processing of smallRNA-Seq data to gather biologically relevant information requires application of multiple statistical and bioinformatics tools from different sources, each focusing on a specific step of the analysis pipeline. The analytical workflow can be challenging for the continuous interventions by the operator, a critical factor when large numbers of datasets need to be analyzed at once. To allow a flexible and comprehensive analysis of smallRNA-Seq data we designed a novel modular pipeline, called iMir, integrating multiple open source modules and resource in an automated workflow, devising different statistical approaches to analyze data rigorously. iMir comprises also a Graphical User Interface (GUI), so that the pipeline is particularly suited for biologist and early stage bioinformaticians and produces both graphics and text outputs.
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