Zoological Institute, University of Basel, 4051 Basel, Switzerland.
Bioinformatics. 2009 Aug 1;25(15):1982-3. doi: 10.1093/bioinformatics/btp303. Epub 2009 May 6.
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.
www.evolution.unibas.ch/salzburger/software.htm.
Supplementary data are available at Bioinformatics online.
用于统计分析微卫星数据的计算机程序利用等位基因长度的变化来推断群体遗传参数,检测数量性状位点或选择清除等。然而,观察到的等位基因长度通常不准确,可能偏离重复的预期周期性。将观察到的等位基因长度四舍五入到最接近的整数的常见做法通常会导致误报和等位基因丰富度的低估。将等位基因长度手动分类到离散类别(称为“binning”)的过程既繁琐又容易出错。在这里,我们提出了一种新的程序,用于自动对微卫星等位基因长度进行 binning,以克服这些问题并促进高通量等位基因 binning。
www.evolution.unibas.ch/salzburger/software.htm。
补充数据可在 Bioinformatics 在线获取。