Dropout_program_note

Dropout_program_note - Molecular Ecology Notes (2005) 5,...

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Molecular Ecology Notes (2005) 5 , 716–718 doi: 10.1111/j.1471-8286.2005.01038.x © 2005 Blackwell Publishing Ltd Blackwel Publishing, Ltd. PROGRAM NOTE DROPOUT : a program to identify problem loci and samples for noninvasive genetic samples in a capture-mark-recapture framework K. S. M c KELVEY and M. K. SCHWARTZ USDA Forest Service, Rocky Mountain Research Station, 800 E. Beckwith, Missoula, MT 59801, USA Abstract Genotyping error, often associated with low-quantity/quality DNA samples, is an important issue when using genetic tags to estimate abundance using capture-mark-recapture (CMR). DROPOUT , an MS-Windows program, identifies both loci and samples that likely contain errors affecting CMR estimates. DROPOUT uses a ‘bimodal test’, that enumerates the number of loci different between each pair of samples, and a ‘difference in capture history test’ (DCH) to determine those loci producing the most errors. Importantly, the DCH test allows one to determine that a data set is error-free. DROPOUT (2004) and is now available online. Keywords : allelic dropout, dropout , genotyping error, mark recapture, molecular tagging, noninvasive Received 09 March 2005; revision accepted 14 April 2005 The fields of ecology, wildlife management and conservation biology have embraced identification of species and individuals using noninvasively collected genetic samples. Projects using noninvasive genetic samples can provide a wealth of data on rare and elusive species once thought impossible to accurately count. Unfortunately, using DNA from noninvasive samples can also lead to genotyping errors which can bias estimates unless carefully controlled (Waits & Leberg 2000; Creel et al Schwartz 2004). Genotyping errors often occur when DNA is collected from low quality samples (hair, feathers, faeces, etc.; Taberlet et al . 1996; Morin et al . 2001). The most common genotyp- ing errors are allelic dropout, the preferential amplification of one of two alleles, false alleles, amplification products that mimic true alleles, and various laboratory errors such as misreading bands or transcription errors. Molecular ecologists have recognized the importance of genotyping error and arrived at multiple solutions. Programs gimlet (Valiere 2002) and reliotype (Miller et al . 2002) are useful for evaluating errors when samples have been multitubed (Taberlet et al . 1996). Program pedmanager (Ewen et al . 2000) is useful when pedigree information is available. Additionally, micro - checker (Van Oosterhout et al . 2004) compares randomly constructed genotypes to observed genotypes, locating errors due to stutter and short allele dominance. Other approaches include quantifying the amount of extracted DNA and avoiding analysis of samples with low yield (Morin et al . 2001). Here we provide details on a program,
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Dropout_program_note - Molecular Ecology Notes (2005) 5,...

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