Quantifying genotyping errors in noninvasive population genetics

Abstract

The use of noninvasively collected samples greatly expands the range of ecological issues that may be investigated through population genetics. Furthermore, the difficulty of obtaining reliable genotypes with samples containing low quantities of amplifiable DNA may be overcome by designing optimal genotyping schemes. Such protocols are mainly determined by the rates of genotyping errors caused by false alleles and allelic dropouts. These errors may not be avoided through laboratory procedure and hence must be quantified. However, the definition of genotyping error rates remains elusive and various estimation methods have been reported in the literature. In this paper we proposed accurate codification for the frequencies of false alleles and allelic dropouts. We then reviewed other estimation methods employed in hair- or faeces-based population genetics studies and modelled the bias associated with erroneous methods. It is emphasized that error rates may be substantially underestimated when using an erroneous approach. Genotyping error rates may be important determinants of the outcome of noninvasive studies and hence should be carefully computed and reported.

Molecular epidemiology of Schistosoma mansoni: A robust, high-throughput method to assess multiple microsatellite markers from individual miracidia

“…Allelic dropout is common when template quantity is low and occurs when one allele (usually the shortest) is favored over the other allele so that the individual appears to be a homozygote when it is actually a heterozygote (Gerloff et al, 1995). False alleles are those that are called for an offspring, but do not exist in either parent and can be the result of a mutation between generations or a false peak due to "noise" in the data (Broquet and Petit, 2004). Sample sizes for offspring varied among loci and are given in Table 2.…”

Using a reference population yardstick to calibrate and compare genetic diversity reported in different studies: an example from the brown bear

“…The actual number of repeats was considerably higher as the entire multiplex was repeated if the genotype at any locus was unclear. We used the methods recommended by Broquet and Petit (2004) to estimate the frequency of allelic dropouts and false alleles, and program Micro-Checker (Van Oosterhout et al, 2004) to check the data for the presence of null alleles, and scoring errors due to stuttering and dropout of large alleles.…”

Maximum-Likelihood Estimation of Allelic Dropout and False Allele Error Rates From Microsatellite Genotypes in the Absence of Reference Data

“…Most studies quantify error rate as a single quantity, such as error rate per allele or per single-locus genotype. However, stochastic errors (as opposed to systematic errors, for example, null alleles) can be divided into two distinct classes: allelic dropout, where one allele of a heterozygote randomly fails to PCR amplify, and false alleles, where the true allele is misgenotyped because of factors such as PCR or electrophoresis artifacts or human errors in reading and recording data (Broquet and Petit 2004). These two classes of error can bias analyses in fundamentally different ways.…”

“…Consider a data set with a low false allele rate but a high allelic dropout rate, a common scenario for genotypes from noninvasive samples such as feces or hair (Broquet and Petit 2004). A candidate father with genotype AA could not be excluded with high confidence from paternity of an offspring with genotype CC because of the high probability of allelic dropout, but if the observed genotypes were AB and CD, respectively, the candidate father could be excluded with greater certainty.…”

“…Given that genotyping errors cannot be eliminated with certainty, a more pragmatic approach is to minimize (Piggott et al 2004), quantify (Bonin et al 2004;Broquet and Petit 2004;Hoffman and Amos 2005), and integrate them in statistical analysis (Marshall et al 1998;Sobel et al 2002;Wang 2004). Most studies quantify error rate as a single quantity, such as error rate per allele or per single-locus genotype.…”