2004
DOI: 10.1186/1471-2105-5-1
|View full text |Cite
|
Sign up to set email alerts
|

PyEvolve: a toolkit for statistical modelling of molecular evolution

Abstract: Background: Examining the distribution of variation has proven an extremely profitable technique in the effort to identify sequences of biological significance. Most approaches in the field, however, evaluate only the conserved portions of sequences -ignoring the biological significance of sequence differences. A suite of sophisticated likelihood based statistical models from the field of molecular evolution provides the basis for extracting the information from the full distribution of sequence variation. The… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

1
196
0

Year Published

2007
2007
2022
2022

Publication Types

Select...
10

Relationship

0
10

Authors

Journals

citations
Cited by 426 publications
(197 citation statements)
references
References 18 publications
1
196
0
Order By: Relevance
“…The sequences within each clade were then aligned with muscle (Edgar, 2004), trimmed to equal length, and only sequences with a length ≥ 90% of all reads were retained. Remaining sequences were clustered at 0.03 cut‐off following the pipeline detailed in Arif et al .…”
Section: Methodsmentioning
confidence: 99%
“…The sequences within each clade were then aligned with muscle (Edgar, 2004), trimmed to equal length, and only sequences with a length ≥ 90% of all reads were retained. Remaining sequences were clustered at 0.03 cut‐off following the pipeline detailed in Arif et al .…”
Section: Methodsmentioning
confidence: 99%
“…A reciprocal allversus-all BLASTp search was performed (threshold E value of Յ1eϪ10) (45), and orthologous groups were determined by orthAgogue and MCL (ignoring E values, percent match lengths of Ն80%, and inflation values of 5 [46,47]). The groups of orthologues (GOs) were then aligned by using MUSCLE and back-translated to the nucleotide sequence by using Translatorx Perl script (48)(49)(50). Maximum likelihood phylogenetic reconstruction of each GO was performed in MEGA6.06 (51), using the Kimura two-parameter model as the nucleotide substitution model and a discrete gamma distribution (4 categories) to model evolutionary rate differences among sites.…”
Section: Methodsmentioning
confidence: 99%
“…The B204 amino acid sequence was queried against the metagenome database using tblastn to identify contigs that shared 30% or higher identity to STIV B204. The sequences were aligned using MUSCLE (34).…”
Section: Methodsmentioning
confidence: 99%