HLA typing software tools | RNA sequencing data analysis
The human leukocyte antigen (HLA) complex is the set of genes on chromosome 6 encoding proteins of the major histocompatibility complex (MHC). These genes are divided into multiple classes with similar but distinct functions. Class I genes, such as HLA-A, HLA-B, and HLA-C, are expressed in nearly all nucleated cells and are important for recognizing endogenous foreign antigens. These antigens can arise via infection or from somatic variations, such as those introduced in cancer. Class II genes, expressed on antigen-presenting cells, generally recognize exogenous foreign antigens, such as viral peptides entering the cytoplasm after apoptosis of infected cells. HLA genes are highly polymorphic, and the number of known alleles continues to grow. Accurately identifying which alleles are present in an individual is important in many areas, such as drug safety, disease susceptibility, neoantigen prediction for cancer treatment, regenerative medicine, and organ transplantation.
A HLA genotyping algorithm based on integer linear programming, capable of producing accurate predictions from NGS data not specifically enriched for the HLA cluster. OptiType significantly outperformed previously published in silico approaches with an overall accuracy of 97% enabling its use in a broad range of applications.
Obtains individual’s human leukocyte antigen (HLA) class I and II type and expression. Seq2HLA recognizes the HLA alleles associated with the greatest number of next generation sequencing (NGS) RNA-Seq reads. It doesn’t need to change laboratory protocols and can be employed for both existing datasets and future analysis. This tool represents another dimension for HLA typing and biomarker investigations.
A software for HLA class I and II predictions from next-generation shotgun (NGS) sequence read data that supports direct read alignment and targeted assembly of sequence reads. This approach circumvents the additional time and cost of generating HLA-specific data and capitalizes on the increasing accessibility and affordability of massively parallel sequencing.
A tool algorithm named to discover the most probable pair of HLA alleles at four-digit resolution or higher, via a unique integration of a candidate allele selection and a likelihood scoring. PHLAT significantly leverages the accuracy and flexibility of high resolution HLA typing based on genome-wide sequencing data. It may benefit both basic and applied research in immunology and related fields as well as numerous clinical applications.
Performs integrative immunogenomic analyses using next generation sequencing (NGS) data. TIminer analyzes single-sample RNA-seq data and somatic DNA mutations to characterize the tumor-immune interface. It is able to: (1) provide genotypes human leukocyte antigens (HLAs) from NGS data, (2) predict tumor neoantigens using mutation data and HLA types, (3) characterize tumor-infiltrating immune cells from bulk RNA-seq data; and (4) quantify tumor immunogenicity from expression data.
Predicts HLA haplotype by hierarchically weighting reads and using an iterative, greedy, top down pruning technique. HLAforest uses BioPerl to read in FASTA files. Alignments use Bowtie, although any alignment tool can be used to generate SAM alignments for use as input to HLAforest.
Gives high resolution results with whole genome, exome or very targeted DNA data, or with RNA seq data. Omixon Target HLA Typing offers high possible HLA typing precision using NGS data. There is no need to be an expert in NGS analysis to use the tool.