Showing 5 open source projects for "error"

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  • 1
    ChIP-RNA-seqPRO

    ChIP-RNA-seqPRO

    ChIP-RNA-sequencing-processing (ChIP-RNA-seqPRO)

    ChIP-RNA-seqPRO: A strategy for identifying regions of epigenetic deregulation associated with aberrant transcript splicing and RNA-editing sites. Runnable python scripts packaged together with customized annotation libraries, demo data input and README guide. 9/26 : v1.1 Updated MAIN_IV to debug error thrown by python pandas no longer supporting 'subset'. This code will no longer be actively maintained/updated here. A cloud-based resource for comparative analysis of epigenetic, sequence variation, and expression datasets is now available. Please visit the Cloudomics, project for cloud-based resources: https://sourceforge.net/projects/cloudomics-for-aws/
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  • 2

    Virus QSP Modeling

    C++ and Python code for simulating RNA virus replication

    Stochastic simulation model of poliovirus Sabin-to-Mahoney genetic state transition (C++ code). Models genotypes, virus populations, and quasispecies cloud. Simulates replication error and copy-choice recombination. Various parameters guiding the model are user-specified. Python code post-processes simulation output to produce report files.
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  • 3

    hrefinder

    Detection of homologous recombination events from SNP data

    ...We use information from the nearby SNPs, so that if 1-2 alleles in a series of SNPs differs from the ancestral allele, it may be better explained as a mutation or sequencing error. But if a series of SNP alleles differ from the ancestral pattern, then it may be more likely that an HRE has occurred, particularly if the allele pattern matches that from another part of the tree better than that of the ancestral node.
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  • 4

    ARDEN

    Specificity Control for Read Alignments Using an Artificial Reference

    We introduce ARDEN (Artificial Reference Driven Estimation of false positives in NGS data), a novel benchmark that estimates error rates based on real experimental reads and an additionally generated artificial reference genome. It allows the computation of error rates specifically for a dataset and the construction of a ROC-curve. Thereby, it can be used to optimize parameters for read mappers, to select read mappers for a specific problem or also to filter alignments based on quality estimation.
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  • 5
    GemSIM is a software package for generating realistic simulated next-generation sequencing reads with quality score values. Both Illumina and Roche/454 reads (single or paired end) can be simulated using appropriate empirical error models.
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