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10.1186/s12859-017-1552-9 http://scihub22266oqcxt.onion/10.1186/s12859-017-1552-9 C5333416!5333416 !28249565     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\28249565 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       BMC+Bioinformatics 2017 ; 18 (1 ): 139 Nephropedia Template TP {{tp|p=28249565 |t=2017. Statistical method to compare massive parallel sequencing pipelines |pdf=|usr=}}{{28249565 }} gab.com Text Statistical method to compare massive parallel sequencing pipelines JO: BMC Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=28249565 #FOAvip BACKGROUND: Today, sequencing is frequently carried out by Massive Parallel Sequencing (MPS) that cuts drastically sequencing time and expenses. Nevertheless, Sanger sequencing remains the main validation method to confirm the presence of variants. The analysis of MPS data involves the development of several bioinformatic tools, academic or commercial. We present here a statistical method to compare MPS pipelines and test it in a comparison between an academic (BWA-GATK) and a commercial pipeline (TMAP-NextGENe®), with and without reference to a gold standard (here, Sanger sequencing), on a panel of 41 genes in 43 epileptic patients. This method used the number of variants to fit log-linear models for pairwise agreements between pipelines. To assess the heterogeneity of the margins and the odds ratios of agreement, four log-linear models were used: a full model, a homogeneous-margin model, a model with single odds ratio for all patients, and a model with single intercept. Then a log-linear mixed model was fitted considering the biological variability as a random effect. RESULTS: Among the 390,339 base-pairs sequenced, TMAP-NextGENe® and BWA-GATK found, on average, 2253.49 and 1857.14 variants (single nucleotide variants and indels), respectively. Against the gold standard, the pipelines had similar sensitivities (63.47% vs. 63.42%) and close but significantly different specificities (99.57% vs. 99.65%; p?<?0.001). Same-trend results were obtained when only single nucleotide variants were considered (99.98% specificity and 76.81% sensitivity for both pipelines). CONCLUSIONS: The method allows thus pipeline comparison and selection. It is generalizable to all types of MPS data and all pipelines. Twit Text FOAVip Statistical method to compare massive parallel sequencing pipelines ????BMC Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=28249565 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28249565 #FOAvip English Wikipedia <ref>{{Cite pmid|28249565 }}</ref> Statistical method to compare massive parallel sequencing pipelines #MMPMID28249565 Elsensohn MH ; Leblay N ; Dimassi S ; Campan-Fournier A ; Labalme A ; Roucher-Boulez F ; Sanlaville D ; Lesca G ; Bardel C ; Roy P BMC Bioinformatics 2017[Mar]; 18 (1 ): 139 PMID28249565 show ga BACKGROUND: Today, sequencing is frequently carried out by Massive Parallel Sequencing (MPS) that cuts drastically sequencing time and expenses. Nevertheless, Sanger sequencing remains the main validation method to confirm the presence of variants. The analysis of MPS data involves the development of several bioinformatic tools, academic or commercial. We present here a statistical method to compare MPS pipelines and test it in a comparison between an academic (BWA-GATK) and a commercial pipeline (TMAP-NextGENe®), with and without reference to a gold standard (here, Sanger sequencing), on a panel of 41 genes in 43 epileptic patients. This method used the number of variants to fit log-linear models for pairwise agreements between pipelines. To assess the heterogeneity of the margins and the odds ratios of agreement, four log-linear models were used: a full model, a homogeneous-margin model, a model with single odds ratio for all patients, and a model with single intercept. Then a log-linear mixed model was fitted considering the biological variability as a random effect. RESULTS: Among the 390,339 base-pairs sequenced, TMAP-NextGENe® and BWA-GATK found, on average, 2253.49 and 1857.14 variants (single nucleotide variants and indels), respectively. Against the gold standard, the pipelines had similar sensitivities (63.47% vs. 63.42%) and close but significantly different specificities (99.57% vs. 99.65%; p? |*Models, Statistical [MESH] |Computational Biology/*methods [MESH] |Epilepsy/genetics/pathology [MESH] |High-Throughput Nucleotide Sequencing [MESH] |Humans [MESH] |INDEL Mutation [MESH] |Polymorphism, Single Nucleotide [MESH]Statistical method to compare massive parallel sequencing pipelines (epmc).pdf DeepDyve Pubget Overpricing