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HLApers: HLA Typing and Quantification of Expression with Personalized Index

  • Vitor R. C. AguiarEmail author
  • Cibele Masotti
  • Anamaria A. Camargo
  • Diogo Meyer
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Part of the Methods in Molecular Biology book series (MIMB, volume 2120)

Abstract

The plethora of RNA-seq data which have been generated in the recent years constitutes an attractive resource to investigate HLA variation and its relationship with normal and disease phenotypes, such as cancer. However, next generation sequencing (NGS) brings new challenges to HLA analysis because of the mapping bias introduced by aligning short reads originated from polymorphic genes to a single reference genome. Here we describe HLApers, a pipeline which adapts widely used tools for analysis of standard RNA-seq data to infer HLA genotypes and estimate expression. By generating reliable expression estimates for each HLA allele that an individual carries, HLApers allows a better understanding of the relationship between HLA alleles and phenotypes manifested by an individual.

Key words

HLA HLA typing HLA expression RNA-seq Immunogenetics 

Notes

Acknowledgements

Funding was provided by the National Institutes of Health, USA (GM 075091). VRCA was supported by a postdoc fellowship from the São Paulo Funding Agency (FAPESP, http://www.fapesp.br/en/) (2014/12123-2 and 2016/24734-1).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  • Vitor R. C. Aguiar
    • 1
    Email author
  • Cibele Masotti
    • 2
  • Anamaria A. Camargo
    • 2
  • Diogo Meyer
    • 1
  1. 1.Department of Genetics and Evolutionary Biology, Institute of BiosciencesUniversity of São PauloSão PauloBrazil
  2. 2.Molecular Oncology Center, Hospital Sírio LibanêsSão PauloBrazil

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