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MrBait: universal identification and design of targeted-enrichment capture probes
Author(s) -
Tyler K. Chafin,
Marlis R. Douglas,
Michael E. Douglas
Publication year - 2018
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bty548
Subject(s) - computer science , codebase , python (programming language) , source code , pipeline (software) , documentation , identification (biology) , context (archaeology) , parsing , software , cluster analysis , os x , data mining , programming language , artificial intelligence , paleontology , botany , biology
It is a non-trivial task to identify and design capture probes ('baits') for the diverse array of targeted-enrichment methods now available (e.g. ultra-conserved elements, anchored hybrid enrichment, RAD-capture). This often involves parsing large genomic alignments, followed by multiple steps of curating candidate genomic regions to optimize targeted information content (e.g. genetic variation) and to minimize potential probe dimerization and non-target enrichment.

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