A probabilistic method for small RNA flowgram matching.
The 454 pyrosequencing technology is gaining popularity as an alternative to traditional Sanger sequencing. While each method has comparative advantages over the other, certain properties of the 454 method make it particularly well suited for small RNA discovery. We here describe some of the details of the 454 sequencing technique, with an emphasis on the nature of the intrinsic sequencing errors and methods for mitigating their effect. We propose a probabilistic framework for small RNA discovery, based on matching 454 flowgrams against the target genome. We formulate flowgram matching as an analog of profile matching, and adapt several profile matching techniques for the task of matching flowgrams. As a result, we are able to recover some of the hits missed by existing methods and assign probability-based scores to them.
Vacic
Vladimir
V
Computer Science and Engineering Department, University of California, Riverside, USA.
Jin
Hailing
H
Zhu
Jian-Kang
JK
Lonardi
Stefano
S
D017360:Arabidopsis / Q000235:genetics; D019295:Computational Biology; D030561:Databases, Nucleic Acid; D015723:Gene Library; D035683:MicroRNAs / Q000235:genetics; D015233:Models, Statistical; D016133:Polymerase Chain Reaction / Q000379:methods; D012313:RNA / Q000235:genetics*; D018749:RNA, Plant / Q000235:genetics; D034741:RNA, Small Interfering / Q000235:genetics; D022661:RNA, Untranslated / Q000235:genetics; D016415:Sequence Alignment / Q000706:statistics & numerical data; D017423:Sequence Analysis, RNA / Q000379:methods / Q000706:statistics & numerical data*; D012984:Software
D035683:MicroRNAs; D018749:RNA, Plant; D034741:RNA, Small Interfering; D022661:RNA, Untranslated; D012313:RNA