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SUMMARY:Quikr: Rapid Bacterial Community Reconstruction Via Compressive Se
 nsing - Koslicki\, D (Oregon State University)
DTSTART:20140327T134500Z
DTEND:20140327T141500Z
UID:TALK51657@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Co-authors: Simon Foucart (University of Georgia)\, Gail Rosen
  (Drexel University) \n\nMany metagenomic studies compare hundreds to thou
 sands of environmental and health-related samples by extracting and sequen
 cing their DNA. However\, one of the first steps - to determine what bacte
 ria are actually in the sample - can be a computationally time-consuming t
 ask since most methods rely on computing the classification of each indivi
 dual read out of tens to hundreds of thousands of reads. We introduce Quik
 r: a QUadratic\, K-mer based\, Iterative\, Reconstruction method which com
 putes a vector of taxonomic assignments and their proportions in the sampl
 e using an optimization technique motivated from the mathematical theory o
 f compressive sensing. On both simulated and actual biological data\, we d
 emonstrate that Quikr is typically more accurate as well as typically orde
 rs of magnitude faster than the most commonly utilized taxonomic assignmen
 t techniques for both whole genome techniques (Metaphyler\, Metaphlan) and
  16S rRNA techniques (the Ribosomal Database Project's Naive Bayesian Clas
 sifier). We also show that in general nonnegative L1 minimization can be r
 educed to a simple nonnegative least squares problem.\n\nRelated Links: \n
 http://www.math.uga.edu/~foucart/WGSQuikr_final.pdf - WGSQuikr preprint \n
 \nhttp://www.math.uga.edu/~foucart/QuikrRevisionPrePrint.pdf - Quikr prepr
 int \n\nhttp://www.math.uga.edu/~foucart/SRasNNLS_final.pdf - Sparse recov
 ery by means of nonnegative least squares \n
LOCATION:Seminar Room 1\, Newton Institute
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