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10.1093/nar/gkw900 http://scihub22266oqcxt.onion/10.1093/nar/gkw900 C5388429!5388429 !28180325     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28180325 &cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       Nucleic+Acids+Res 2017 ; 45 (3 ): e14 Nephropedia Template TP {{tp|p=28180325 |t=2017. ROCker: accurate detection and quantification of target genes in short-read metagenomic data sets by modeling sliding-window bitscores |pdf=|usr=}}{{28180325 }} gab.com Text ROCker: accurate detection and quantification of target genes in short-read metagenomic data sets by modeling sliding-window bitscores JO: Nucleic Acids Res http://www.kidney.de/pget.php?&tw=1&pmid=28180325 #FOAvip 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 monooxygenase (amoA) and nitrous oxide reductase (nosZ) genes, mediating oxidation of ammonia and the reduction of the potent greenhouse gas, N2O, to inert N2, respectively. ROCker typically showed 60-fold lower FDR when compared to the common practice of using fixed e-values. Previously uncounted ?atypical? nosZ genes were found to be two times more abundant, on average, than their typical counterparts in most soil metagenomes and the abundance of bacterial amoA was quantified against the highly-related particulate methane monooxygenase (pmoA). Therefore, ROCker can reliably detect and quantify target genes in short-read metagenomes. Twit Text FOAVip ROCker: accurate detection and quantification of target genes in short-read metagenomic data sets by modeling sliding-window bitscores ????Nucleic Acids Res http://www.kidney.de/pget.php?&tw=1&pmid=28180325 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28180325 #FOAvip English Wikipedia <ref>{{Cite pmid|28180325 }}</ref> ROCker: accurate detection and quantification of target genes in short-read metagenomic data sets by modeling sliding-window bitscores #MMPMID28180325 Orellana LH ; Rodriguez-R LM ; Konstantinidis KT Nucleic Acids Res 2017[Feb]; 45 (3 ): e14 PMID28180325 show ga 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 monooxygenase (amoA) and nitrous oxide reductase (nosZ) genes, mediating oxidation of ammonia and the reduction of the potent greenhouse gas, N2O, to inert N2, respectively. ROCker typically showed 60-fold lower FDR when compared to the common practice of using fixed e-values. Previously uncounted ?atypical? nosZ genes were found to be two times more abundant, on average, than their typical counterparts in most soil metagenomes and the abundance of bacterial amoA was quantified against the highly-related particulate methane monooxygenase (pmoA). Therefore, ROCker can reliably detect and quantify target genes in short-read metagenomes. |Aquatic Organisms/genetics [MESH] |Computational Biology/methods [MESH] |Databases, Genetic/statistics & numerical data [MESH] |Ecosystem [MESH] |Metagenomics/*statistics & numerical data [MESH] |Microbial Consortia/genetics [MESH] |Phylogeny [MESH] |ROC Curve [MESH]ROCker: accurate detection and quantification of target genes in short(epmc).pdf DeepDyve Pubget Overpricing