mirror of
https://github.com/Ponce/slackbuilds
synced 2024-11-18 22:06:04 +01:00
26 lines
1.3 KiB
Text
26 lines
1.3 KiB
Text
WEVOTE (WEighted VOting Taxonomic idEntification)
|
|
|
|
WEVOTE is a method that classifies metagenome shotgun sequencing DNA
|
|
reads based on an ensemble of existing methods using k-mer based,
|
|
marker-based, and naive-similarity based approaches. The performance
|
|
evaluation based on fourteen simulated microbiome datasets
|
|
consistently demonstrates that WEVOTE achieves a high level of
|
|
sensitivity and precision compared to the individual methods across
|
|
different taxonomic levels. The major advantage of the WEVOTE pipeline
|
|
is that the user can make the choice of which tools to use in order to
|
|
explore the trade-off between sensitivity, precision, time and memory.
|
|
|
|
The WEVOTE architecture is flexible so that additional taxonomic tools
|
|
can be easily added, or the current tools can be replaced by improved
|
|
ones. Moreover, the score assigned to the taxon for each read
|
|
indicates the confidence level of the assignment. This information is
|
|
especially useful for the assessment of false positive annotations at
|
|
a particular taxonomic level. The classification score given by WEVOTE
|
|
can be used for any downstream analysis that requires the high
|
|
confidence of the annotated sequences.
|
|
|
|
Publication:
|
|
Ahmed A. Metwally, Yang Dai, Patricia W. Finn, and David L. Perkins.
|
|
WEVOTE: Weighted Voting Taxonomic Identification Method of Microbial
|
|
Sequences.
|
|
PloS ONE, 2016.
|