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10.1038/srep26447 http://scihub22266oqcxt.onion/10.1038/srep26447 C4876386!4876386 !27211518     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=27211518 &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 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 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\27211518 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Sci+Rep 2016 ; 6 (ä): 26447 Nephropedia Template TP {{tp|p=27211518 |t=2016. MetaTrans: an open-source pipeline for metatranscriptomics |pdf=|usr=}}{{27211518 }} gab.com Text MetaTrans: an open-source pipeline for metatranscriptomics JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=27211518 #FOAvip To date, meta-omic approaches use high-throughput sequencing technologies, which produce a huge amount of data, thus challenging modern computers. Here we present MetaTrans, an efficient open-source pipeline to analyze the structure and functions of active microbial communities using the power of multi-threading computers. The pipeline is designed to perform two types of RNA-Seq analyses: taxonomic and gene expression. It performs quality-control assessment, rRNA removal, maps reads against functional databases and also handles differential gene expression analysis. Its efficacy was validated by analyzing data from synthetic mock communities, data from a previous study and data generated from twelve human fecal samples. Compared to an existing web application server, MetaTrans shows more efficiency in terms of runtime (around 2?hours per million of transcripts) and presents adapted tools to compare gene expression levels. It has been tested with a human gut microbiome database but also proposes an option to use a general database in order to analyze other ecosystems. For the installation and use of the pipeline, we provide a detailed guide at the following website (www.metatrans.org). Twit Text FOAVip MetaTrans: an open-source pipeline for metatranscriptomics ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=27211518 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27211518 #FOAvip English Wikipedia <ref>{{Cite pmid|27211518 }}</ref> MetaTrans: an open-source pipeline for metatranscriptomics #MMPMID27211518 Martinez X ; Pozuelo M ; Pascal V ; Campos D ; Gut I ; Gut M ; Azpiroz F ; Guarner F ; Manichanh C Sci Rep 2016[May]; 6 (ä): 26447 PMID27211518 show ga To date, meta-omic approaches use high-throughput sequencing technologies, which produce a huge amount of data, thus challenging modern computers. Here we present MetaTrans, an efficient open-source pipeline to analyze the structure and functions of active microbial communities using the power of multi-threading computers. The pipeline is designed to perform two types of RNA-Seq analyses: taxonomic and gene expression. It performs quality-control assessment, rRNA removal, maps reads against functional databases and also handles differential gene expression analysis. Its efficacy was validated by analyzing data from synthetic mock communities, data from a previous study and data generated from twelve human fecal samples. Compared to an existing web application server, MetaTrans shows more efficiency in terms of runtime (around 2?hours per million of transcripts) and presents adapted tools to compare gene expression levels. It has been tested with a human gut microbiome database but also proposes an option to use a general database in order to analyze other ecosystems. For the installation and use of the pipeline, we provide a detailed guide at the following website (www.metatrans.org). |*Microbiota [MESH] |Bacteria/classification/*genetics [MESH] |Computational Biology/*methods [MESH] |Feces/microbiology [MESH] |High-Throughput Nucleotide Sequencing [MESH] |Humans [MESH] |Internet [MESH] |Metagenomics [MESH] |Sequence Analysis, RNA [MESH]MetaTrans: an open-source pipeline for metatranscriptomics (epmc).pdf DeepDyve Pubget Overpricing