The Experts below are selected from a list of 303 Experts worldwide ranked by ideXlab platform
Martin Maiers - One of the best experts on this subject based on the ideXlab platform.
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Charting improvements in US registry HLA Typing ambiguity using a Typing resolution score.
Human Immunology, 2016Co-Authors: Vanja Paunic, Loren Gragert, Joel Schneider, Carlheinz Müller, Martin MaiersAbstract:Abstract Unrelated stem cell registries have been collecting HLA Typing of volunteer bone marrow donors for over 25 years. Donor selection for hematopoietic stem cell transplantation is based primarily on matching the alleles of donors and patients at five polymorphic HLA loci. As HLA Typing technologies have continually advanced since the beginnings of stem cell transplantation, registries have accrued Typings of varied HLA Typing ambiguity. We present a new Typing resolution score (TRS), based on the likelihood of self-match, that allows the systematic comparison of HLA Typings across different methods, data sets and populations. We apply the TRS to chart improvement in HLA Typing within the Be The Match Registry of the United States from the initiation of DNA-based HLA Typing to the current state of high-resolution Typing using next-generation sequencing technologies. In addition, we present a publicly available online tool for evaluation of any given HLA Typing. This TRS objectively evaluates HLA Typing methods and can help define standards for acceptable recruitment HLA Typing.
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Charting Improvements in US Registry HLA Typing Ambiguity Using a Typing Resolution Score
bioRxiv, 2016Co-Authors: Vanja Paunic, Loren Gragert, Joel Schneider, Carlheinz Mueller, Martin MaiersAbstract:Unrelated stem cell registries have been collecting HLA Typing of volunteer bone marrow donors for over 25 years. Donor selection for hematopoietic stem cell transplantation is based primarily on matching the alleles of donors and patients at five polymorphic HLA loci. As HLA Typing technologies have continually advanced since the beginnings of stem cell transplantation, registries have accrued Typings of varied HLA Typing ambiguity. We present a new Typing resolution score, based on the likelihood of self-match, that allows the systematic comparison of HLA Typings across different methods, data sets and populations. We apply the Typing resolution score to chart improvement in HLA Typing within the Be The Match Registry of the United States from the initiation of DNA-based HLA Typing to the current state of high-resolution Typing using next-generation sequencing technologies. In addition, we present a publicly available online tool for evaluation of any given HLA Typing. This Typing resolution score objectively evaluates HLA Typing methods and can help define standards for acceptable recruitment HLA Typing.
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Measuring Ambiguity in HLA Typing Methods
PLoS ONE, 2012Co-Authors: Vanja Paunic, John Freeman, Abeer Madbouly, Loren Gragert, Martin MaiersAbstract:In hematopoietic stem cell transplantation, donor selection is based primarily on matching donor and patient HLA genes. These genes are highly polymorphic and their Typing can result in exact allele assignment at each gene (the resolution at which patients and donors are matched), but it can also result in a set of ambiguous assignments, depending on the Typing methodology used. To facilitate rapid identification of matched donors, registries employ statistical algorithms to infer HLA alleles from ambiguous genotypes. Linkage disequilibrium information encapsulated in haplotype frequencies is used to facilitate prediction of the most likely haplotype assignment. An HLA Typing with less ambiguity produces fewer high-probability haplotypes and a more reliable prediction. We estimated ambiguity for several HLA Typing methods across four continental populations using an information theory-based measure, Shannon's entropy. We used allele and haplotype frequencies to calculate entropy for different sets of 1,000 subjects with simulated HLA Typing. Using allele frequencies we calculated an average entropy in Caucasians of 1.65 for serology, 1.06 for allele family level, 0.49 for a 2002-era SSO kit, and 0.076 for single-pass SBT. When using haplotype frequencies in entropy calculations, we found average entropies of 0.72 for serology, 0.73 for allele family level, 0.05 for SSO, and 0.002 for single-pass SBT. Application of haplotype frequencies further reduces HLA Typing ambiguity. We also estimated expected confirmatory Typing mismatch rates for simulated subjects. In a hypothetical registry with all donors typed using the same method, the entropy values based on haplotype frequencies correspond to confirmatory Typing mismatch rates of 1.31% for SSO versus only 0.08% for SBT. Intermediate-resolution single-pass SBT contains the least ambiguity of the methods we evaluated and therefore the most certainty in allele prediction. The presented measure objectively evaluates HLA Typing methods and can help define acceptable HLA Typing for donor recruitment.
Vanja Paunic - One of the best experts on this subject based on the ideXlab platform.
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Charting improvements in US registry HLA Typing ambiguity using a Typing resolution score.
Human Immunology, 2016Co-Authors: Vanja Paunic, Loren Gragert, Joel Schneider, Carlheinz Müller, Martin MaiersAbstract:Abstract Unrelated stem cell registries have been collecting HLA Typing of volunteer bone marrow donors for over 25 years. Donor selection for hematopoietic stem cell transplantation is based primarily on matching the alleles of donors and patients at five polymorphic HLA loci. As HLA Typing technologies have continually advanced since the beginnings of stem cell transplantation, registries have accrued Typings of varied HLA Typing ambiguity. We present a new Typing resolution score (TRS), based on the likelihood of self-match, that allows the systematic comparison of HLA Typings across different methods, data sets and populations. We apply the TRS to chart improvement in HLA Typing within the Be The Match Registry of the United States from the initiation of DNA-based HLA Typing to the current state of high-resolution Typing using next-generation sequencing technologies. In addition, we present a publicly available online tool for evaluation of any given HLA Typing. This TRS objectively evaluates HLA Typing methods and can help define standards for acceptable recruitment HLA Typing.
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Charting Improvements in US Registry HLA Typing Ambiguity Using a Typing Resolution Score
bioRxiv, 2016Co-Authors: Vanja Paunic, Loren Gragert, Joel Schneider, Carlheinz Mueller, Martin MaiersAbstract:Unrelated stem cell registries have been collecting HLA Typing of volunteer bone marrow donors for over 25 years. Donor selection for hematopoietic stem cell transplantation is based primarily on matching the alleles of donors and patients at five polymorphic HLA loci. As HLA Typing technologies have continually advanced since the beginnings of stem cell transplantation, registries have accrued Typings of varied HLA Typing ambiguity. We present a new Typing resolution score, based on the likelihood of self-match, that allows the systematic comparison of HLA Typings across different methods, data sets and populations. We apply the Typing resolution score to chart improvement in HLA Typing within the Be The Match Registry of the United States from the initiation of DNA-based HLA Typing to the current state of high-resolution Typing using next-generation sequencing technologies. In addition, we present a publicly available online tool for evaluation of any given HLA Typing. This Typing resolution score objectively evaluates HLA Typing methods and can help define standards for acceptable recruitment HLA Typing.
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Measuring Ambiguity in HLA Typing Methods
PLoS ONE, 2012Co-Authors: Vanja Paunic, John Freeman, Abeer Madbouly, Loren Gragert, Martin MaiersAbstract:In hematopoietic stem cell transplantation, donor selection is based primarily on matching donor and patient HLA genes. These genes are highly polymorphic and their Typing can result in exact allele assignment at each gene (the resolution at which patients and donors are matched), but it can also result in a set of ambiguous assignments, depending on the Typing methodology used. To facilitate rapid identification of matched donors, registries employ statistical algorithms to infer HLA alleles from ambiguous genotypes. Linkage disequilibrium information encapsulated in haplotype frequencies is used to facilitate prediction of the most likely haplotype assignment. An HLA Typing with less ambiguity produces fewer high-probability haplotypes and a more reliable prediction. We estimated ambiguity for several HLA Typing methods across four continental populations using an information theory-based measure, Shannon's entropy. We used allele and haplotype frequencies to calculate entropy for different sets of 1,000 subjects with simulated HLA Typing. Using allele frequencies we calculated an average entropy in Caucasians of 1.65 for serology, 1.06 for allele family level, 0.49 for a 2002-era SSO kit, and 0.076 for single-pass SBT. When using haplotype frequencies in entropy calculations, we found average entropies of 0.72 for serology, 0.73 for allele family level, 0.05 for SSO, and 0.002 for single-pass SBT. Application of haplotype frequencies further reduces HLA Typing ambiguity. We also estimated expected confirmatory Typing mismatch rates for simulated subjects. In a hypothetical registry with all donors typed using the same method, the entropy values based on haplotype frequencies correspond to confirmatory Typing mismatch rates of 1.31% for SSO versus only 0.08% for SBT. Intermediate-resolution single-pass SBT contains the least ambiguity of the methods we evaluated and therefore the most certainty in allele prediction. The presented measure objectively evaluates HLA Typing methods and can help define acceptable HLA Typing for donor recruitment.
David Heckerman - One of the best experts on this subject based on the ideXlab platform.
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Statistical resolution of ambiguous HLA Typing data
PLoS Computational Biology, 2008Co-Authors: Jennifer Listgarten, Carl Kadie, Gao Xiaojiang, Philip Goulder, Mary Carrington, Bruce N. Walker, Zabrina L Brumme, David HeckermanAbstract:High-resolution HLA Typing plays a central role in many areas of immunology, such as in identifying immunogenetic risk factors for disease, in studying how the genomes of pathogens evolve in response to immune selection pressures, and also in vaccine design, where identification of HLA-restricted epitopes may be used to guide the selection of vaccine immunogens. Perhaps one of the most immediate applications is in direct medical decisions concerning the matching of stem cell transplant donors to unrelated recipients. However, high-resolution HLA Typing is frequently unavailable due to its high cost or the inability to re-type historical data. In this paper, we introduce and evaluate a method for statistical, in silico refinement of ambiguous and/or low-resolution HLA data. Our method, which requires an independent, high-resolution training data set drawn from the same population as the data to be refined, uses linkage disequilibrium in HLA haplotypes as well as four-digit allele frequency data to probabilistically refine HLA Typings. Central to our approach is the use of haplotype inference. We introduce new methodology to this area, improving upon the Expectation-Maximization (EM)-based approaches currently used within the HLA community. Our improvements are achieved by using a parsimonious parameterization for haplotype distributions and by smoothing the maximum likelihood (ML) solution. These improvements make it possible to scale the refinement to a larger number of alleles and loci in a more computationally efficient and stable manner. We also show how to augment our method in order to incorporate ethnicity information (as HLA allele distributions vary widely according to race/ethnicity as well as geographic area), and demonstrate the potential utility of this experimentally. A tool based on our approach is freely available for research purposes at http://microsoft.com/science.
Ethan Kentzel - One of the best experts on this subject based on the ideXlab platform.
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assessing the utilization of high resolution 2 field HLA Typing in solid organ transplantation
American Journal of Transplantation, 2019Co-Authors: Yanping Huang, Anh Dinh, S Heron, Allison Gasiewski, Carolina Kneib, Hilary Mehler, Michael T Mignogno, Ryan Morlen, Larissa Slavich, Ethan KentzelAbstract:: HLA Typing in solid organ transplantation (SOT) is necessary for determining HLA-matching status between donor-recipient pairs and assessing patients' anti-HLA antibody profiles. Histocompatibility has traditionally been evaluated based on serologically defined HLA antigens. The evolution of HLA Typing and antibody identification technologies, however, has revealed many limitations with using serologic equivalents for assessing compatibility in SOT. The significant improvements to HLA Typing introduced by next-generation sequencing (NGS) require an assessment of the impact of this technology on SOT. We have assessed the role of high-resolution 2-field HLA Typing (HR-2F) in SOT by retrospectively evaluating NGS-typed pre- and post-SOT cases. HR-2F Typing was highly instructive or necessary in 41% (156/385) of the cases. Several pre- and posttransplant scenarios were identified as being better served by HR-2F Typing. Five different categories are presented with specific case examples. The experience of another center (Temple University Hospital) is also included, whereby 21% of the cases required HR-2F Typing by Sanger sequencing, as supported by other legacy methods, to properly address posttransplant anti-HLA antibody issues.
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Assessing the utilization of high‐resolution 2‐field HLA Typing in solid organ transplantation
American Journal of Transplantation, 2019Co-Authors: Yanping Huang, Anh Dinh, S Heron, Allison Gasiewski, Carolina Kneib, Hilary Mehler, Michael T Mignogno, Ryan Morlen, Larissa Slavich, Ethan KentzelAbstract:: HLA Typing in solid organ transplantation (SOT) is necessary for determining HLA-matching status between donor-recipient pairs and assessing patients' anti-HLA antibody profiles. Histocompatibility has traditionally been evaluated based on serologically defined HLA antigens. The evolution of HLA Typing and antibody identification technologies, however, has revealed many limitations with using serologic equivalents for assessing compatibility in SOT. The significant improvements to HLA Typing introduced by next-generation sequencing (NGS) require an assessment of the impact of this technology on SOT. We have assessed the role of high-resolution 2-field HLA Typing (HR-2F) in SOT by retrospectively evaluating NGS-typed pre- and post-SOT cases. HR-2F Typing was highly instructive or necessary in 41% (156/385) of the cases. Several pre- and posttransplant scenarios were identified as being better served by HR-2F Typing. Five different categories are presented with specific case examples. The experience of another center (Temple University Hospital) is also included, whereby 21% of the cases required HR-2F Typing by Sanger sequencing, as supported by other legacy methods, to properly address posttransplant anti-HLA antibody issues.
Loren Gragert - One of the best experts on this subject based on the ideXlab platform.
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Charting improvements in US registry HLA Typing ambiguity using a Typing resolution score.
Human Immunology, 2016Co-Authors: Vanja Paunic, Loren Gragert, Joel Schneider, Carlheinz Müller, Martin MaiersAbstract:Abstract Unrelated stem cell registries have been collecting HLA Typing of volunteer bone marrow donors for over 25 years. Donor selection for hematopoietic stem cell transplantation is based primarily on matching the alleles of donors and patients at five polymorphic HLA loci. As HLA Typing technologies have continually advanced since the beginnings of stem cell transplantation, registries have accrued Typings of varied HLA Typing ambiguity. We present a new Typing resolution score (TRS), based on the likelihood of self-match, that allows the systematic comparison of HLA Typings across different methods, data sets and populations. We apply the TRS to chart improvement in HLA Typing within the Be The Match Registry of the United States from the initiation of DNA-based HLA Typing to the current state of high-resolution Typing using next-generation sequencing technologies. In addition, we present a publicly available online tool for evaluation of any given HLA Typing. This TRS objectively evaluates HLA Typing methods and can help define standards for acceptable recruitment HLA Typing.
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Charting Improvements in US Registry HLA Typing Ambiguity Using a Typing Resolution Score
bioRxiv, 2016Co-Authors: Vanja Paunic, Loren Gragert, Joel Schneider, Carlheinz Mueller, Martin MaiersAbstract:Unrelated stem cell registries have been collecting HLA Typing of volunteer bone marrow donors for over 25 years. Donor selection for hematopoietic stem cell transplantation is based primarily on matching the alleles of donors and patients at five polymorphic HLA loci. As HLA Typing technologies have continually advanced since the beginnings of stem cell transplantation, registries have accrued Typings of varied HLA Typing ambiguity. We present a new Typing resolution score, based on the likelihood of self-match, that allows the systematic comparison of HLA Typings across different methods, data sets and populations. We apply the Typing resolution score to chart improvement in HLA Typing within the Be The Match Registry of the United States from the initiation of DNA-based HLA Typing to the current state of high-resolution Typing using next-generation sequencing technologies. In addition, we present a publicly available online tool for evaluation of any given HLA Typing. This Typing resolution score objectively evaluates HLA Typing methods and can help define standards for acceptable recruitment HLA Typing.
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8-OR: TOOLS FOR IMPLEMENTATION OF SILVER STANDARD PRINCIPLES FOR HLA Typing
Human Immunology, 2012Co-Authors: Bob Milius, Abeer Madbouly, Loren Gragert, Joel Schneider, Michael Heuer, Pradeep Bashyal, Mike George, Doug Schneyman, Jane Pollack, Jill A. HollenbachAbstract:Aim A ‘Silver Standard’ for HLA data collection and reporting has been described at ImmPort (immport.niaid.nih.gov, “Proposal for HLA Data Validation”) to address ambiguity resolution in the recording and reporting of HLA Typing results. While standards are critical for HLA data interoperability, they are not meaningful until useful tools are developed and made available for community use. We are developing distributable tools that implement this silver standard. Here we describe the development a web service to create, update, and retrieve HLA Typing data in standardized formats without the need for NMDP allele codes and the corresponding inherent introduction of new ambiguities. Methods ReST web services with HTTP negotiation are being developed employing a Java library that manages HLA Typing data using standardized formats. These formats include the XML based Histoimmunogenetics Markup Language (HML) and a simple character-delimited string format (GL String) able to encode ambiguity within HLA Typing. Resources are identified with a simple Uniform Resource Identifier (URI). Results The services build on a foundation of an open access database schema for IMGT/HLA reference sequence data (updated quarterly), and objects such as alleles, lists of alleles, haplotypes, genotypes, lists of genotypes and multi-locus unphased genotypes. Public services include creating, updating, and retrieving these objects. Content negotiation allows data retrieval in a variety of formats including GL String, HML, HTML, JSON, and QR Code. Conclusions The tools being developed here provide the HLA researcher, clinician and lab technician a common resource for managing HLA data in a standardized way. We envision these tools to augment workflows through creating new instances of HLA Typing objects when needed, and retrieval of those objects and their associated metadata when called upon.
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Measuring Ambiguity in HLA Typing Methods
PLoS ONE, 2012Co-Authors: Vanja Paunic, John Freeman, Abeer Madbouly, Loren Gragert, Martin MaiersAbstract:In hematopoietic stem cell transplantation, donor selection is based primarily on matching donor and patient HLA genes. These genes are highly polymorphic and their Typing can result in exact allele assignment at each gene (the resolution at which patients and donors are matched), but it can also result in a set of ambiguous assignments, depending on the Typing methodology used. To facilitate rapid identification of matched donors, registries employ statistical algorithms to infer HLA alleles from ambiguous genotypes. Linkage disequilibrium information encapsulated in haplotype frequencies is used to facilitate prediction of the most likely haplotype assignment. An HLA Typing with less ambiguity produces fewer high-probability haplotypes and a more reliable prediction. We estimated ambiguity for several HLA Typing methods across four continental populations using an information theory-based measure, Shannon's entropy. We used allele and haplotype frequencies to calculate entropy for different sets of 1,000 subjects with simulated HLA Typing. Using allele frequencies we calculated an average entropy in Caucasians of 1.65 for serology, 1.06 for allele family level, 0.49 for a 2002-era SSO kit, and 0.076 for single-pass SBT. When using haplotype frequencies in entropy calculations, we found average entropies of 0.72 for serology, 0.73 for allele family level, 0.05 for SSO, and 0.002 for single-pass SBT. Application of haplotype frequencies further reduces HLA Typing ambiguity. We also estimated expected confirmatory Typing mismatch rates for simulated subjects. In a hypothetical registry with all donors typed using the same method, the entropy values based on haplotype frequencies correspond to confirmatory Typing mismatch rates of 1.31% for SSO versus only 0.08% for SBT. Intermediate-resolution single-pass SBT contains the least ambiguity of the methods we evaluated and therefore the most certainty in allele prediction. The presented measure objectively evaluates HLA Typing methods and can help define acceptable HLA Typing for donor recruitment.
