Literature DB >> 33373910

Novel Method for Accurately Assessing Pull-up Artifacts in STR Analysis.

Robert M Goor1, Douglas Hoffman2, George R Riley3.   

Abstract

OSIRIS is a mathematically-based software tool for Short Tandem Repeat (STR) and DNA fragment analysis (https://www.ncbi.nlm.nih.gov/osiris/). As part of its routine sample analyses, OSIRIS computes unique quality metrics that can be used for sample quality assessment. A common artifact of STR analysis is cross-channel pull-up or pull-down (negative pull-up). This occurs because of the spectral overlap between the dyes used with the marker set, and the failure of the color deconvolution matrix to isolate the colors in the dye set adequately. This paper describes a mathematical method for analyzing and quantifying the pull-up patterns across sample channels and effectively identifying and correcting the pull-up artifacts, as implemented in OSIRIS. Unlike approaches to pull-up that require a training set composed of previous samples, the algorithm described here uses a mathematical model of the underlying causes of pull-up. It is based solely on the information intrinsic to the sample it is analyzing and therefore incorporates the effects of the ambient conditions and the specific procedures used in creating the sample. These conditions are the physical determinants of the level of pull-up in the sample and are not likely to be represented in a training set consisting of past samples. Published by Elsevier B.V.

Entities:  

Keywords:  Artifact identification; Artifact removal; DNA analysis; OSIRIS; Quality control; STR analysis software

Mesh:

Year:  2020        PMID: 33373910      PMCID: PMC8279173          DOI: 10.1016/j.fsigen.2020.102410

Source DB:  PubMed          Journal:  Forensic Sci Int Genet        ISSN: 1872-4973            Impact factor:   4.882


  3 in total

1.  Automated detection and removal of capillary electrophoresis artifacts due to spectral overlap.

Authors:  Jonathan D Adelman; Angie Zhao; D Spencer Eberst; Michael A Marciano
Journal:  Electrophoresis       Date:  2019-05-28       Impact factor: 3.535

2.  Teaching artificial intelligence to read electropherograms.

Authors:  Duncan Taylor; David Powers
Journal:  Forensic Sci Int Genet       Date:  2016-07-28       Impact factor: 4.882

3.  A mathematical approach to the analysis of multiplex DNA profiles.

Authors:  Robert M Goor; Lisa Forman Neall; Douglas Hoffman; Stephen T Sherry
Journal:  Bull Math Biol       Date:  2010-11-20       Impact factor: 1.758

  3 in total

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