TANDEM: integrating automated allele binning into genetics and genomics workflows.
CONCLUSIONS
Computer programs for the statistical analysis of microsatellite data use allele length variation to infer, e.g. population genetic parameters, to detect quantitative trait loci or selective sweeps. However, observed allele lengths are usually inaccurate and may deviate from the expected periodicity of repeats. The common practice of rounding to the nearest whole number frequently results in miscalls and underestimations of allelic richness. Manual sorting of allele lengths into discrete classes, a process called binning, is tedious and error-prone. Here, we present a new program for the automated binning of microsatellite allele lengths to overcome these problems and to facilitate high-throughput allele binning.


BACKGROUND
www.evolution.unibas.ch/salzburger/software.htm.


BACKGROUND
Supplementary data are available at Bioinformatics online.
Matschiner
Michael
M
Zoological Institute, University of Basel, 4051 Basel, Switzerland. michael.matschiner@unibas.ch
Salzburger
Walter
W
D000483:Alleles; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D023281:Genomics / Q000379:methods*; D012984:Software; D014584:User-Computer Interface