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SUMMARY:Webserver-supported storage of metagenomic datasets using MEGANv5 
 - Ruscheweyh\, H-J (University of Tuebingen)
DTSTART:20140327T144500Z
DTEND:20140327T151500Z
UID:TALK51659@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Co-author: Daniel Huson (University of Tuebingen\, Algorithms 
 in Bioinformatics\, Tuebingen\, Germany) \n\nBackground: Metagenomics is a
  rapidly growing field of research that aims at studying assemblages of un
 cultured organisms with the help of sequencing\, with the hope of understa
 nding the true diversity of microbes\, their functions\, cooperation and e
 volution. While early papers studied isolated or small numbers of samples\
 , there is now an increasing number of projects that involve systematicall
 y collecting multiple samples of\, due to sinking sequencing costs\, growi
 ng size. Moreover\, more attention is being paid to the problem of recordi
 ng relevant environmental parameters (so-called metadata). There is a need
  for tools that allow one to store and analyze multiple metagenomic datase
 ts in the context of their metadata. \n\nResults: We announce an extension
  to our metagenome analysis tool MEGAN\, called MeganServer\, that allows 
 one to store metagenomic datasets on a secure server in order to reduce re
 dundancy and enhancing the ease of sharing large datasets between project 
 members or making the publicly available. The software allows one\, additi
 onally\, to capture the metadata associated with datasets and then use it 
 to form new composite datasets by combining primary datasets based on the 
 values of their environmental parameters. While the user can analyze any s
 uch combined dataset exactly like a primary dataset using MEGAN\, internal
 ly\, a combined dataset refers back to the primary datasets and thus does 
 not duplicate any reads or matches. \n\nConclusions: With sinking sequenci
 ng costs\, metagenomic datasets are growing to sizes too large to be store
 d locally. Installing MeganServer on an computer cluster or using a public
 ly available instance allows one to store datasets on a server without los
 ing the benefits of using MEGAN locally. Also\, combining datasets based o
 n environmental features is an important step in the comparative analysis 
 of metagenome datasets.\n
LOCATION:Seminar Room 1\, Newton Institute
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