Title
Lambda: the local aligner for massive biological data.
Abstract
Motivation: Next-generation sequencing technologies produce unprecedented amounts of data, leading to completely new research fields. One of these is metagenomics, the study of large-size DNA samples containing a multitude of diverse organisms. A key problem in metagenomics is to functionally and taxonomically classify the sequenced DNA, to which end the well-known BLAST program is usually used. But BLAST has dramatic resource requirements at metagenomic scales of data, imposing a high financial or technical burden on the researcher. Multiple attempts have been made to overcome these limitations and present a viable alternative to BLAST. Results: In this work we present Lambda, our own alternative for BLAST in the context of sequence classification. In our tests, Lambda often outperforms the best tools at reproducing BLAST's results and is the fastest compared with the current state of the art at comparable levels of sensitivity.
Year
DOI
Venue
2014
10.1093/bioinformatics/btu439
BIOINFORMATICS
Keywords
Field
DocType
algorithms,metagenomics,sequence alignment
Sequence alignment,Biological data,Data mining,Computer science,Metagenomics,Software,Bioinformatics,Lambda
Journal
Volume
Issue
ISSN
30
17
1367-4803
Citations 
PageRank 
References 
8
0.53
16
Authors
3
Name
Order
Citations
PageRank
Hannes Hauswedell180.53
Jochen Singer2182.92
Knut Reinert31020105.87