Visualising Errors in Animal Pedigree Genotype Data

نویسندگان

  • Martin Graham
  • Jessie B. Kennedy
  • Trevor Paterson
  • Andy Law
چکیده

Genetic analysis of a breeding animal population involves determining the inheritance pattern of genotypes for multiple genetic markers across the individuals in the population pedigree structure. However, experimental pedigree genotype data invariably contains errors in both the pedigree structure and in the associated individual genotypes, which introduce inconsistencies into the dataset, rendering them useless for further analysis. The resolution of these errors requires consideration of the genotype inheritance patterns in the context of the pedigree structure. Existing visualisations of pedigree structures are typically more suited to human pedigrees and are less suitable for large complex animal pedigrees which may exhibit cross generational inbreeding. Similarly, current table-based viewers of genotype marker information can highlight where errors become apparent but lack the functionality and interactive visual feedback to enable users to locate the underlying source of errors within the pedigree. In this paper, we detail a design study steered by biologists who work with pedigree data, and describe successive iterations through approaches and prototypes for viewing genotyping errors in the context of a displayed pedigree. We describe how each approach performs with real pedigree genotype data and why eventually we deemed them unsuitable. Finally, a novel prototype visualisation for pedigrees, which we term the ‘sandwich view’, is detailed and we demonstrate how the approach effectively communicates errors in the pedigree context, supporting the biologist in the error identification task.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Microsatillate based Parentage Verification in Crossbred Sheep Herds

Parentage testing is an important tool in farm animals for genetically determining the accuracy of pedigree information. The objective of the current study was to implication of multiplexing 14 microsatellite markers for routine parentage testings. The twenty-four lambs were crossbred of Ghazel × Baluchi, Ghazel × Baluchi × Merinos, and Baluchi × Moghani × Merinos breeds. The genomic DNA was ex...

متن کامل

SNP Data Quality Control in a National Beef and Dairy Cattle System and Highly Accurate SNP Based Parentage Verification and Identification

A major use of genetic data is parentage verification and identification as inaccurate pedigrees negatively affect genetic gain. Since 2012 the international standard for single nucleotide polymorphism (SNP) verification in Bos taurus cattle has been the ISAG SNP panels. While these ISAG panels provide an increased level of parentage accuracy over microsatellite markers (MS), they can validate ...

متن کامل

Error detection for genetic data, using likelihood methods.

As genetic maps become denser, the effect of laboratory typing errors becomes more serious. We review a general method for detecting errors in pedigree genotyping data that is a variant of the likelihood-ratio test statistic. It pinpoints individuals and loci with relatively unlikely genotypes. Power and significance studies using Monte Carlo methods are shown by using simulated data with pedig...

متن کامل

Cleaning genotype data.

The identification of genes contributing to variation in complex phenotypes requires genetic data of high fidelity. Thus, the identification of pedigree and genotyping errors is a crucial prerequisite to the analysis of data from a genome scan for disease genes. The problem has been given little attention in most gene hunting papers; the focus has often been on eliminating mendelian inconsisten...

متن کامل

Inferring Haplotypes from genotypes on a Pedigree with mutations, genotyping Errors and Missing Alleles

Inferring the haplotypes of the members of a pedigree from their genotypes has been extensively studied. However, most studies do not consider genotyping errors and de novo mutations. In this paper, we study how to infer haplotypes from genotype data that may contain genotyping errors, de novo mutations, and missing alleles. We assume that there are no recombinants in the genotype data, which i...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Comput. Graph. Forum

دوره 30  شماره 

صفحات  -

تاریخ انتشار 2011