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An Improved Method ...
An Improved Method for Estimating Chromosomal Line Origin in QTL Analysis of Crosses Between Outbred Lines
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- Crooks, Lucy (författare)
- Uppsala universitet,Beräknings- och systembiologi
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- Carlborg, Örjan (författare)
- Uppsala universitet,Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för husdjursgenetik (HGEN),Department of Animal Breeding and Genetics,Uppsala University,Beräknings- och systembiologi
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- Nettelblad, Carl (författare)
- Uppsala universitet,Avdelningen för teknisk databehandling,Tillämpad beräkningsvetenskap
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(creator_code:org_t)
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- 2011-06-01
- 2011
- Engelska.
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Ingår i: G3. - : Oxford University Press (OUP). - 2160-1836. ; 1, s. 57-64
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Abstract
Ämnesord
Stäng
- Estimating the line origin of chromosomal sections from marker genotypes is a vital step in quantitative trait loci analyses of outbred line crosses. The original, and most commonly used, algorithm can only handle moderate numbers of partially informative markers. The advent of high-density genotyping with SNP chips motivates a new method because the generic sets of markers on SNP chips typically result in long stretches of partially informative markers. We validated a new method for inferring line origin, triM (tracing inheritance with Markov models), with simulated data. A realistic pattern of marker information was achieved by replicating the linkage disequilibrium from an existing chicken intercross. There were approximately 1500 SNP markers and 800 F-2 individuals. The performance of triM was compared to GridQTL, which uses a variant of the original algorithm but modified for larger datasets. triM estimated the line origin with an average error of 2%, was 10% more accurate than GridQTL, considerably faster, and better at inferring positions of recombination. GridQTL could not analyze all simulated replicates and did not estimate line origin for around a third of individuals at many positions. The study shows that triM has computational benefits and improved estimation over available algorithms and is valuable for analyzing the large datasets that will be standard in future.
Ämnesord
- LANTBRUKSVETENSKAPER -- Veterinärmedicin (hsv//swe)
- AGRICULTURAL SCIENCES -- Veterinary Science (hsv//eng)
- LANTBRUKSVETENSKAPER -- Husdjursvetenskap (hsv//swe)
- AGRICULTURAL SCIENCES -- Animal and Dairy Sience (hsv//eng)
- NATURVETENSKAP -- Matematik -- Beräkningsmatematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Computational Mathematics (hsv//eng)
- NATURVETENSKAP -- Biologi -- Genetik (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Genetics (hsv//eng)
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