Published December 31, 2003
Abstract
The pedigree and genotype data from the Framingham Heart Study were reviewed for errors. Errors in 21 of 329 pedigrees were detected with the program PREST, and the mistakes of those pedigrees and 16 were resolved. Genotyping errors were detected with SIMWALK2. Mend lienne five errors were found following the pedigree corrections. Double-recombinant mistakes have been more frequent, with 142 being detected at mistyping probabilities of 0.25 or more. Background Because
linkage analysis observes co-segregation of alleles markers and phenotype, it is feared that the mistakes in pedigrees or genotypes may result in false negative or false positive results. L & 39; Using Genetic Analysis Workshop (GAW) data to examine the presence and nature of the errors & 39; n pedigree is not new [1-3]. In this exercise, we identify and describe the pedigree and genotyping errors in the GAW13 Framingham Heart Study data.
Outline Methods
Summary Background Method Results Discussion References Thanks
Pedigree d & 39; error detection and correction PREST Program [4] Pedigree has been used to detect errors. PREST estimates of probabilities, p0, p1 and p2 two people sharing 0, 1 and 2 alleles identical by descent (IBD), respectively. We calculated this on & 39; range of relations between couples known to PREST (parent-offspring, full-brothers, half-brothers, avuncular, first cousins, grandparents, grandchildren, half-avuncular, half - first cousin, half-sib, the first - Cousin, monozygotic twins, and unrelated) to & 39; within and among pedigrees. Pedigree d & 39; mistakes have first been screened with PREST analytical tests: Conditional estimated identity by descent (EIBD), adjusted identity of the State & 39; (AIBS), and IBS, in order & 39;, and where appropriate, = 0.0001, to focus on the most important problems. This index pair and their relatives were then examined in greater detail using PREST ALTERTEST program & 39; support that can make the test & 39; two individuals for each of the 11 classes of relationship. PREST R comes with a screenplay written by Dan Weeks track DCI & 39; estimate of a single pair compared to a triangular relationship [5]. We changed the program to provide a scattergram of IBDs on the triangle. The result is an informative summary chart of the family tree & 39; errors in the sample & 39;. Pedigrees were drawn with PEDIGREE / DRAW [6]. Genotyping of & 39; detection and error correction of errors are detected using genotyping SIMWALK [7.8]. SIMWALK2 applied a Markov chain, Monte Carlo method of pedigree data, the population allele frequencies, and & 39; a genetic map to assign probabilities for each genotype mistyping. Because it & 39; s & 39; talking & 39; an exercise in intensive computing, we examined the mistakes of genotyping only on chromosome 7. We ran SIMWALK2 in two phases. In the first phase, Mendelian errors were detected and corrected independently for each marker. Marker genotypes were blanked (postponed to a missing value) for all probabilities mistyping d above a given threshold & 39;. The threshold was chosen cautiously, c & 39; is to say, no more genotypes in white marker for a longer necessary to calculate the probability that marker. Mistyping The probability was 1.0 decremented & 39; up to a calculable probability has been reached. In the second phase, which offer genotypes improbable double recombination events were sealed. Mistyping probabilities were assigned using the genetic maps supplied with the data GAW13. In this phase, the proportion of potentially genotypes & 39; cancelled during a series of thresholds is set to provide a visual guide for the selection of a threshold & 39;. Following the correction of race and genotype data, we recalculated for comparison, the genetic map of chromosome 7 using MULTIMAP / CRIMAP [9.10].
Outline Results
Summary Background Method Results Discussion References Thanks
Figures
Figure 1Scatter diagrams & 39; From the estimated relationship IBDs triangles for six categories relationship
Figure 2Pedigree error example 1
Figure 3Pedigree error example 2
Figure 4Distribution double recombinant genotyping errors
Pedigree errors Scatter diagram of the PCI & 39; estimate of probabilities p0, p1, and P2 on the relationship triangles are shown in Figure 1. These reveal virtually no full-sibling errors. Some avuncular and first cousin relationships are liable & 39; be independent, and a large number of unrelated individuals & 39; are indeed likely to be linked & 39;, some parent-offspring pairs. Faithful among the observations of the parents were required before changes were made to the pedigrees. For example, four pairs that are unrelated parent-offspring undoubtedly show the necessary parent-offspring relationship with a woman in a pedigree disconnected, as determined by ALTERTEST and illustrated in Figure 2. All four were unrelated to the original name of the mother, mother-in-law now. None of the other alternative tests suggested that any other arrangement. In another example shown in Figure 3, two pedigrees were joined by two half-brothers ungenotyped detected through consistent half-avuncular and half-cousin relationship. These simple examples belie the difficulties pedigree to correct errors. In the Framingham data we have been able to resolve errors in 16 of 21 pedigrees, the pedigrees of 329 in total. The five models displayed outstanding pedigrees d & 39; errors, contradicting all testable hypotheses alternatives, and were left unchanged. Five errors genotyping Mendelian following errors have been revealed the pedigree changes. The probability distribution mistyping for the detection of recombinant double is shown in Figure 4. We opted for a threshold of 0.25 probability of erroneous to define genotypes, so empty without too great a loss of data. With this threshold, 142 genotypes were sealed. Following the cut, a new card for 21 genetic markers on chromosome 7 was estimated using MULTIMAP / CRIMAP [9.10]. The new map was 167 cM in length, or 24 cM shorter than the map provided with the data. By comparison, the length of the corresponding map is 175 Marshfield cM [11].
Outline Discussion
Summary Background Method Results Discussion References Thanks
Framingham Data were relatively free of pedigree errors, in particular those involving close relatives. The most frequent type of error & 39; of the individuals involved in the upper generations, detected through their descendants because of a lack of data for the genotype ancestors. These errors are often corrected through the accession of & 39; pedigrees disconnected. It is difficult to generalize these results to other populations of & 39; including the types and distribution of pedigree mistakes can be quite different. Presumably in Framingham, kinship terms are usually given a biological interpretation. So & 39; other population groups where it & 39; n is not strictly the case, serious errors seem possible. The small number of Mendelian genotyping errors in the data from Framingham, which & 39; had not been detected earlier & 39; became clear that as a result of pedigree corrections. Genotype errors involving improbable double recombination events were more common, the exact number depending on a definition of probable mistyping.
Acknowledgements We are grateful to Linda Freeman-Shade (SFBR) to provide PEDSYS [12] Versions PREST (PREPREST) and SIMWALK2 (PRESWALK), making these programs very easy to use, and Thomas Dyer (SFBR) to support programs for use with SIMWALK2. This research was partially funded by NIH grant MH59490.
Outline References
Summary Background Method Results Discussion References
1 Acknowledgements. Broman KW: Cleaning genotype data.Genet Epidemiol 1999, 17 (suppl 1): S79-S83.
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2. Sun L, M Abney, McPeek MS: Detection of error & 39; relations specified in inbred and outbred pedigrees.Genet Epidemiol 2001, 21 (suppl 1): S36-S41.
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3. Cherny SS, Abecasis GR, Cookson WOC, Sham PC, Cardon LR: L & 39; effect of genotype and pedigree error on link analysis: l & 39; genome analysis of three asthma scans.Genet Epidemiol 2001, 21 ( suppl 1): S117-S122.
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4. Sun L, K Wilder, McPeek MS: Enhanced pedigree error detection.Hum Hered 2002, 54:99-110.
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5. Ihaka R, Gentleman R: A language for data analysis & 39; and Graph graphics.J Comp Stat 1996, 5:299-314.
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6. Mamalka PM, B Dyke, MacCluer JW: Pedigree / Draw & 39; for the Apple Macintosh, Technical Report No. 1.San Antonio, TX, Population Genetics Laboratory, Southwest Foundation for Biomedical Research 1989.
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7. Sobel E, Lange K: Descent graphics pedigree analysis: applications haplotyping, & 39; location of the partition, and marker-sharing statistics.Am J Hum Genet 1996, 58:1323-1337.
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8. Sobel E, Papp JC, Lange K: Detection & 39; and the integration of statistical errors genotyping genetics.Am J Hum Genet 2002, 70:496-508.
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9. Matise TC, Perlin M, Chakravarti A: construction automated genetic linkage maps using an expert system (MultiMap): Linking human genome map.Nat Genet 1994, 6:384-390.
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10. Green P, K Falls, Crooks S: CRI-MAP Documentation.St. Louis, MO, Department of Genetics, Washington University in St. Louis 1990.
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11. KW Broman, JC Murray, Sheffield VC, White RL, Weber JL: Comprehensive human genetic maps: individual and specific gender variation recombination.Am J Hum Genet 1998, 63:861-689.
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12. Dyke B: PEDSYS a Pedigree Data Management System & 39; s User Manual, Technical Report No. 2.San Antonio, TX, Population Genetics Laboratory, Southwest Foundation for Biomedical Research 1994.
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