PMID- 25525323
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20141219
LR  - 20200930
IS  - 1176-9343 (Print)
IS  - 1176-9343 (Electronic)
IS  - 1176-9343 (Linking)
VI  - 10
DP  - 2014
TI  - SWAMP: Sliding Window Alignment Masker for PAML.
PG  - 197-204
LID - 10.4137/EBO.S18193 [doi]
AB  - With the greater availability of genetic data, large genome-wide scans for 
      positive selection increasingly incorporate data from a range of sources. These 
      data sets may be derived from different sequencing methods, each of which has 
      potential sources of error. Sequencing errors, compounded by alignment errors, 
      greatly increase the number of false positives in tests for adaptive evolution. 
      Genome-wide analyses often fail to fully address these issues or to provide 
      sufficient detail on postalignment masking/filtering. Here, we introduce a 
      Sliding Window Alignment Masker for Phylogenetic Analysis by Maximum Likelihood 
      (SWAMP) that scans multiple-sequence alignments for short regions enriched with 
      unreasonably high rates of nonsynonymous substitutions caused, for example, by 
      sequence or alignment errors. SWAMP prevents their inclusion in downstream 
      evolutionary analyses and therefore increases the reliability of downstream 
      analyses. It is able to effectively mask short stretches of erroneous sequence, 
      particularly prevalent in low-coverage genomes, which may not be detected by 
      existing methods based on filtering by sitewise conservation or alignment 
      confidence. SWAMP offers a flexible masking approach, and the user can apply 
      different masking regimens to specific branches or sequences in the phylogeny 
      allowing the stringency of masking to vary according to branch length, expected 
      divergence levels, or assembly quality. We exemplify SWAMPs effectiveness on a 
      dataset of 6,379 protein-coding genes from primate species, including data of 
      variable quality. Full reporting of the software parameters will further improve 
      the reproducibility of genome-wide analyses, as well as reduce false-positive 
      rates.
FAU - Harrison, Peter W
AU  - Harrison PW
AD  - Department of Genetics, Evolution and Environment, University College London, 
      London, United Kingdom.
FAU - Jordan, Gregory E
AU  - Jordan GE
AD  - European Molecular Biology Laboratory, European Bioinformatics Institute, 
      Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom.
FAU - Montgomery, Stephen H
AU  - Montgomery SH
AD  - Department of Genetics, Evolution and Environment, University College London, 
      London, United Kingdom.
LA  - eng
PT  - Journal Article
DEP - 20141201
PL  - United States
TA  - Evol Bioinform Online
JT  - Evolutionary bioinformatics online
JID - 101256319
PMC - PMC4251194
OTO - NOTNLM
OT  - PAML
OT  - adaptive evolution
OT  - genome evolution
OT  - molecular evolution
OT  - phylogenetics
OT  - sequence analysis
EDAT- 2014/12/20 06:00
MHDA- 2014/12/20 06:01
PMCR- 2014/12/01
CRDT- 2014/12/20 06:00
PHST- 2014/06/26 00:00 [received]
PHST- 2014/08/21 00:00 [revised]
PHST- 2014/09/01 00:00 [accepted]
PHST- 2014/12/20 06:00 [entrez]
PHST- 2014/12/20 06:00 [pubmed]
PHST- 2014/12/20 06:01 [medline]
PHST- 2014/12/01 00:00 [pmc-release]
AID - ebo-10-2014-197 [pii]
AID - 10.4137/EBO.S18193 [doi]
PST - epublish
SO  - Evol Bioinform Online. 2014 Dec 1;10:197-204. doi: 10.4137/EBO.S18193. 
      eCollection 2014.