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      Pedimap: Software for the Visualization of Genetic and Phenotypic Data in Pedigrees

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          Abstract

          Pedimap is a user-friendly software tool for visualizing phenotypic and genotypic data for related individuals linked in pedigrees. Genetic data can include marker scores, Identity-by-Descent probabilities, and marker linkage map positions, allowing the visualization of haplotypes through lineages. The pedigrees can accommodate all types of inheritance, including selfing, cloning, and repeated backcrossing, and all ploidy levels are supported. Visual association of the genetic data with phenotypic data simplifies the exploration of large data sets, thereby improving breeding decision making. Data are imported from text files; in addition data exchange with other software packages (FlexQTL TM and GenomeStudio TM) is possible. Instructions for use and an executable version compatible with the Windows platform are available for free from http://www.plantbreeding.wur.nl/UK/software_pedimap.html.

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          Software for constructing and verifying pedigrees within large genealogies and an application to the Old Order Amish of Lancaster County.

          Sanjay R Agarwala, Leslie G Biesecker, C Francomano … (1998)
          This paper describes PedHunter, a software package that facilitates creation and verification of pedigrees within large genealogies. A frequent problem in medical genetics is to connect distant relatives with a pedigree. PedHunter uses methods from graph theory to solve two versions of the pedigree connection problem for genealogies as well as other pedigree analysis problems. The pedigrees are produced by PedHunter as files in LINKAGE format ready for linkage analysis. PedHunter uses a relational database of genealogy data, with tables in specified format, for all calculations. The functionality and utility of PedHunter are illustrated by examples using the Amish Genealogy Database (AGDB), which was created for the Old Order Amish community of Lancaster County, Pennsylvania.
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            Microsatellite allele dose and configuration establishment (MADCE): an integrated approach for genetic studies in allopolyploids

            Thijs van Dijk, Yolanda Noordijk, Tiphaine Dubos … (2012)
            Background Genetic studies in allopolyploid plants are challenging because of the presence of similar sub-genomes, which leads to multiple alleles and complex segregation ratios. In this study, we describe a novel method for establishing the exact dose and configuration of microsatellite alleles for any accession of an allopolyploid plant species. The method, named Microsatellite Allele Dose and Configuration Establishment (MADCE), can be applied to mapping populations and pedigreed (breeding) germplasm in allopolyploids. Results Two case studies are presented to demonstrate the power and robustness of the MADCE method. In the mapping case, five microsatellites were analysed. These microsatellites amplified 35 different alleles based on size. Using MADCE, we uncovered 30 highly informative segregating alleles. A conventional approach would have yielded only 19 fully informative and six partially informative alleles. Of the ten alleles that were present in all progeny (and thereby ignored or considered homozygous when using conventional approaches), six were found to segregate by dosage when analysed with MADCE. Moreover, the full allelic configuration of the mapping parents could be established, including null alleles, homozygous loci, and alleles that were present on multiple homoeologues. In the second case, 21 pedigreed cultivars were analysed using MADCE, resulting in the establishment of the full allelic configuration for all 21 cultivars and a tracing of allele flow over multiple generations. Conclusions The procedure described in this study (MADCE) enhances the efficiency and information content of mapping studies in allopolyploids. More importantly, it is the first technique to allow the determination of the full allelic configuration in pedigreed breeding germplasm from allopolyploid plants. This enables pedigree-based marker-trait association studies the use of algorithms developed for diploid crops, and it may increase the effectiveness of LD-based association studies. The MADCE method therefore enables researchers to tackle many of the genotyping problems that arise when performing mapping, pedigree, and association studies in allopolyploids. We discuss the merits of MADCE in comparison to other marker systems in polyploids, including SNPs, and how MADCE could aid in the development of SNP markers in allopolyploids.
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              Madeline 2.0 PDE: a new program for local and web-based pedigree drawing.

              James A. Marrs, Kari Branham, John Richards … (2007)
              The Madeline 2.0 Pedigree Drawing Engine (PDE) is a pedigree drawing program for use in linkage and family-based association studies. The program is designed to handle large and complex pedigrees with an emphasis on readability and aesthetics. For complex pedigrees, we use a hybrid algorithm in which consanguinous loops are drawn as cyclic graphs whenever possible, but we resort to acyclic graphs when matings can no longer be connected without line crossings. A similar hybrid approach is used to avoid line crossings for matings between distant descendants of different founding groups. Written in object-oriented C++ and released under the GNU General Public License (GPL), Madeline 2.0 PDE reads input files specified on the command line and generates pedigree drawings without user interaction. Pedigree output in scalable vector graphics (SVG) format can be viewed in browsers with native SVG rendering support or in vector graphics editors. We provide an easy-to-use public web service, which is experimental and still under development. http://kellogg.umich.edu/madeline.
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                Author and article information

                Journal
                Journal ID (nlm-ta): J Hered
                Journal ID (iso-abbrev): J. Hered
                Journal ID (hwp): jhered
                Journal ID (publisher-id): jhered
                Title: Journal of Heredity
                Publisher: Oxford University Press (US )
                ISSN (Print): 0022-1503
                ISSN (Electronic): 1465-7333
                Publication date (Print): Nov-Dec 2012
                Publication date (Electronic): 19 October 2012
                Publication date PMC-release: 19 October 2012
                Volume: 103
                Issue: 6
                Pages: 903-907
                Affiliations
                From the Wageningen University & Research Centre, Plant Breeding, PO Box 16, 6700 AA Wageningen, The Netherlands (Voorrips and van de Weg); and the Wageningen University & Research Centre, Biometris, PO Box 100, 6700 AC Wageningen, The Netherlands (Bink).
                Author notes
                Address correspondence to Roeland E. Voorrips at the address above, or e-mail: roeland.voorrips@ 123456wur.nl .

                Corresponding Editor: John Stommel

                Article
                DOI: 10.1093/jhered/ess060
                PMC ID: 3510005
                PubMed ID: 23087384
                SO-VID: 33d83d0a-ce72-470b-b6b9-f5b2a31044d7
                Copyright © © The American Genetic Association. 2012.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses?by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 9 January 2012
                Date revision received : 14 June 2012
                Date accepted : 8 July 2012
                Page count
                Pages: 5
                Categories
                Subject: Computer Note

                ScienceOpen disciplines: Genetics
                Keywords: genetic data,phenotypic data,pedigree software,plant breeding
                Data availability:
                ScienceOpen disciplines: Genetics
                Keywords: genetic data, phenotypic data, pedigree software, plant breeding

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