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DATE | 2017-04-19 |
FROM | Ruben Safir
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SUBJECT | Subject: [Learn] Computational Mathematics in Biology - R Programming -
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From learn-bounces-at-nylxs.com Wed Apr 19 02:28:45 2017 Return-Path: X-Original-To: archive-at-mrbrklyn.com Delivered-To: archive-at-mrbrklyn.com Received: from www.mrbrklyn.com (www.mrbrklyn.com [96.57.23.82]) by mrbrklyn.com (Postfix) with ESMTP id 9853216132F; Wed, 19 Apr 2017 02:28:45 -0400 (EDT) X-Original-To: learn-at-nylxs.com Delivered-To: learn-at-nylxs.com Received: from [10.0.0.62] (flatbush.mrbrklyn.com [10.0.0.62]) by mrbrklyn.com (Postfix) with ESMTP id 7DDE3161327; Wed, 19 Apr 2017 02:28:43 -0400 (EDT) To: Hangout , "learn-at-nylxs.com" From: Ruben Safir Message-ID: <5d2b1c75-d211-35ed-d90d-f8b16bf6b190-at-mrbrklyn.com> Date: Wed, 19 Apr 2017 02:28:43 -0400 User-Agent: Mozilla/5.0 (X11; Linux x86_64; rv:45.0) Gecko/20100101 Thunderbird/45.8.0 MIME-Version: 1.0 Subject: [Learn] Computational Mathematics in Biology - R Programming - mothur.org X-BeenThere: learn-at-nylxs.com X-Mailman-Version: 2.1.17 Precedence: list List-Id: List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit Errors-To: learn-bounces-at-nylxs.com Sender: "Learn"
http://www.microbeworld.org/podcasts/this-week-in-microbiology
You have to check out this podcast, especially about 50 minutes it.
http://traffic.libsyn.com/twimshow/TWiM149.mp3
It is about microbiology and it is entitled: TWiM #149: You're going to learn R
The guess is a remarkable gentleman named Pat Schloss who is a biologist who chose to be a gnu/linux hacker as well and is spreading the word in his area of study.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ http://www.schlosslab.org/ Join Us! I am always looking for exceptional and dedicated scientists and try to maintain a balance between training graduate students and postdoctoral researchers. It is important to me that we maintain a diverse team so that we do the best job of synergizing our experiences and interests. If you are interested in working towards a PhD at Michigan, I participate in the Program in Biomedical Sciences (PIBS), which is an umbrella program within the Medical School. You should apply to the Department of Microbiology & Immunology through PIBS and once you get here, ask me about doing a rotation. If you are finishing your PhD and are looking for a potential postdoctoral position, let's start a conversation.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ http://msphere.asm.org/content/2/2/e00073-17
OptiClust, an Improved Method for Assigning Amplicon-Based Sequence Data to Operational Taxonomic Units Sarah L. Westcott, Patrick D. Schloss Katherine McMahon, Editor DOI: 10.1128/mSphereDirect.00073-17
ArticleFigures & DataInfo & Metrics PDF
ABSTRACT
Assignment of 16S rRNA gene sequences to operational taxonomic units (OTUs) is a computational bottleneck in the process of analyzing microbial communities. Although this has been an active area of research, it has been difficult to overcome the time and memory demands while improving the quality of the OTU assignments. Here, we developed a new OTU assignment algorithm that iteratively reassigns sequences to new OTUs to optimize the Matthews correlation coefficient (MCC), a measure of the quality of OTU assignments. To assess the new algorithm, OptiClust, we compared it to 10 other algorithms using 16S rRNA gene sequences from two simulated and four natural communities. Using the OptiClust algorithm, the MCC values averaged 15.2 and 16.5% higher than the OTUs generated when we used the average neighbor and distance-based greedy clustering with VSEARCH, respectively. Furthermore, on average, OptiClust was 94.6 times faster than the average neighbor algorithm and just as fast as distance-based greedy clustering with VSEARCH. An empirical analysis of the efficiency of the algorithms showed that the time and memory required to perform the algorithm scaled quadratically with the number of unique sequences in the data set. The significant improvement in the quality of the OTU assignments over previously existing methods will significantly enhance downstream analysis by limiting the splitting of similar sequences into separate OTUs and merging of dissimilar sequences into the same OTU. The development of the OptiClust algorithm represents a significant advance that is likely to have numerous other applications.
IMPORTANCE The analysis of microbial communities from diverse environments using 16S rRNA gene sequencing has expanded our knowledge of the biogeography of microorganisms. An important step in this analysis is the assignment of sequences into taxonomic groups based on their similarity to sequences in a database or based on their similarity to each other, irrespective of a database. In this study, we present a new algorithm for the latter approach. The algorithm, OptiClust, seeks to optimize a metric of assignment quality by shuffling sequences between taxonomic groups. We found that OptiClust produces more robust assignments and does so in a rapid and memory-efficient manner. This advance will allow for a more robust analysis of microbial communities and the factors that shape them.
Podcast: A podcast concerning this article is available.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ https://www.asm.org/index.php/asm-governance/2-uncategorised/94824-2017-ballot
http://www.schlosslab.org/labbies/westcott.html https://www.mothur.org/ <=========================== Check this out
-- So many immigrant groups have swept through our town that Brooklyn, like Atlantis, reaches mythological proportions in the mind of the world - RI Safir 1998 http://www.mrbrklyn.com
DRM is THEFT - We are the STAKEHOLDERS - RI Safir 2002 http://www.nylxs.com - Leadership Development in Free Software http://www2.mrbrklyn.com/resources - Unpublished Archive http://www.coinhangout.com - coins! http://www.brooklyn-living.com
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