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Parikesit, Arli
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Medicine & Pharmacology

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Computational Software for Assessing Allelic Droput Ivan, Jeremias; Parikesit, Arli
Indonesian Journal of Life Sciences 2019: IJLS Vol 01 No .01
Publisher : Indonesia International Institute for Life Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54250/ijls.v1i1.11

Abstract

Allelic dropout is a failed amplification of an allele which usually happens when the concentration of the DNA sample is low. As there is a missing genotype, the result of the DNA profiling will significantly be affected. One way to overcome this problem is by using computational software that considers thedropout event within its algorithm. This review is aimed to discuss several software that have been created to serve this purpose. All of the listed software turn to implement Maximum Likelihood (LR) algorithm within their calculation; however, they use different parameters and variables. This reviewshowed that allelic dropout should not be evaluated alone; it correlates with other events in creating a low quality of DNA. Therefore, a comprehensive algorithm that consider all of the factors should be built to best estimates the allelic dropout rate within a data.
Co-Authors Ivan, Jeremias