↓ Skip to main content

HLA Typing

Overview of attention for book
Cover of 'HLA Typing'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 The Past, Present, and Future of HLA Typing in Transplantation
  3. Altmetric Badge
    Chapter 2 Role of Human Leukocyte Antigens (HLA) in Autoimmune Diseases
  4. Altmetric Badge
    Chapter 3 The IPD Databases: Cataloguing and Understanding Allele Variants
  5. Altmetric Badge
    Chapter 4 Allele Frequency Net Database
  6. Altmetric Badge
    Chapter 5 High-Resolution HLA-Typing by Next-Generation Sequencing of Randomly Fragmented Target DNA
  7. Altmetric Badge
    Chapter 6 High-Throughput Contiguous Full-Length Next-Generation Sequencing of HLA Class I and II Genes from 96 Donors in a Single MiSeq Run
  8. Altmetric Badge
    Chapter 7 Application of High-Throughput Next-Generation Sequencing for HLA Typing on Buccal Extracted DNA
  9. Altmetric Badge
    Chapter 8 Super High Resolution for Single Molecule-Sequence-Based Typing of Classical HLA Loci Using Ion Torrent PGM
  10. Altmetric Badge
    Chapter 9 High-Resolution Full-Length HLA Typing Method Using Third Generation (Pac-Bio SMRT) Sequencing Technology
  11. Altmetric Badge
    Chapter 10 Full-Length HLA Class I Genotyping with the MinION Nanopore Sequencer
  12. Altmetric Badge
    Chapter 11 Imputation-Based HLA Typing with SNPs in GWAS Studies
  13. Altmetric Badge
    Chapter 12 In Silico Typing of Classical and Non-classical HLA Alleles from Standard RNA-Seq Reads
  14. Altmetric Badge
    Chapter 13 PHLAT: Inference of High-Resolution HLA Types from RNA and Whole Exome Sequencing
  15. Altmetric Badge
    Chapter 14 Using Exome and Amplicon-Based Sequencing Data for High-Resolution HLA Typing with ATHLATES
  16. Altmetric Badge
    Chapter 15 HLA Typing from Short-Read Sequencing Data with OptiType
  17. Altmetric Badge
    Chapter 16 Comprehensive HLA Typing from a Current Allele Database Using Next-Generation Sequencing Data
  18. Altmetric Badge
    Chapter 17 Accurate Assembly and Typing of HLA using a Graph-Guided Assembler Kourami
  19. Altmetric Badge
    Chapter 18 AmpliSAS and AmpliHLA: Web Server Tools for MHC Typing of Non-Model Species and Human Using NGS Data
  20. Altmetric Badge
    Chapter 19 HLA Haplotype Frequency Estimation from Real-Life Data with the Hapl-o-Mat Software
Attention for Chapter 19: HLA Haplotype Frequency Estimation from Real-Life Data with the Hapl-o-Mat Software
Altmetric Badge

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
6 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
HLA Haplotype Frequency Estimation from Real-Life Data with the Hapl-o-Mat Software
Chapter number 19
Book title
HLA Typing
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-8546-3_19
Pubmed ID
Book ISBNs
978-1-4939-8545-6, 978-1-4939-8546-3
Authors

Jürgen Sauter, Christian Schäfer, Alexander H. Schmidt, Sauter, Jürgen, Schäfer, Christian, Schmidt, Alexander H.

Abstract

HLA haplotype frequencies are of use in a variety of settings. Such data is typically derived either from family pedigree data by targeted typing or statistical analysis of large population-specific genotype samples. As established tools for the latter approach lacked ability to treat the amount, ambiguity, and inhomogeneity found in genotype data in hematopoietic stem cell donor registries, we developed Hapl-o-Mat to alleviate these specific shortcomings.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 33%
Other 1 17%
Student > Bachelor 1 17%
Unknown 2 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 1 17%
Social Sciences 1 17%
Medicine and Dentistry 1 17%
Unknown 3 50%