ROCker: accurate detection and quantification of target genes in short-read metagenomic data sets by modeling sliding-window bitscores.

ABSTRACT: Functional annotation of metagenomic and metatranscriptomic data sets relies on similarity searches based on e-value thresholds resulting in an unknown number of false positive and negative matches. To overcome these limitations, we introduce ROCker, aimed at identifying position-specific, most-discriminant thresholds in sliding windows along the sequence of a target protein, accounting for non-discriminative domains shared by unrelated proteins. ROCker employs the receiver operating characteristic (ROC) curve to minimize false discovery rate (FDR) and calculate the best thresholds based on how simulated shotgun metagenomic reads of known composition map onto well-curated reference protein sequences and thus, differs from HMM profiles and related methods. We showcase ROCker using ammonia m

SUBMITTER: Orellana LH 

PROVIDER: S-EPMC5388429 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature