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Polyidus — identifying chimeric sequencing reads with a tale of Python programming language

Authors: Karimzadeh, Mehran; Hoffman, Michael M.;

Polyidus — identifying chimeric sequencing reads with a tale of Python programming language

Abstract

The free Polyidus software identifies the exact genomic regions for integration of a known virus. We developed Polyidus to identify viral integration sites with chimeric sequencing reads from any paired-end sequencing data. First, Polyidus aligns reads to a viral genome. It allows for partial mapping using local alignment, and removes any sequencing fragment where neither read maps to the virus. Second, Polyidus aligns the selected reads to the host genome, permitting partial mapping. Third, Polyidus identifies chimeric reads: those reads mapped partially to the host genome and partially to the virus genome. Fourth, for each chimeric read, Polyidus reports the start and strand of integration in both the host and viral genomes. Polyidus also reports the number of chimeric reads supporting each integration site. In the previous version, we called our software Bellerophon. After noticing that the name was previously used for another software, we changed the name to Polyidus. Update on version 1.1.0: The host BAM file for paired-end analysis was expected to be sorted by reads, but was in fact sorted by position. The bug is fixed in v1.1.0

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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