HLAminer

HLAminer predicts HLA signatures from long-read sequencing data by streaming alignments directly into the software.

Key Features:

• Streaming alignment input: HLAminer processes sequence alignments streamed directly from read aligners, eliminating the need to store large alignment files on disk.
• SAM format compatibility: HLAminer works with any read aligner compatible with the SAM file format.
• Long-read sequencing support: HLAminer analyzes data from Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) platforms.
• Low coverage robustness: HLAminer produces robust predictions even with older, less accurate WGS nanopore datasets and relatively low (10×) sequencing coverage.
• HLA class I and class II prediction: HLAminer predicts both HLA class I and class II alleles from whole-genome shotgun (WGS) long-read sequencing data.
• Scalable processing: HLAminer scales efficiently with the number of sequences.

Scientific Applications:

• HLA typing from long-read WGS data: HLAminer enables prediction of HLA alleles from whole-genome shotgun long-read sequencing for immunogenomics studies.
• Analysis of polymorphic immune regions: HLAminer facilitates analysis of the highly complex human leukocyte antigen (HLA) gene cluster, a cornerstone of human immunity.
• Third-generation sequencing immunogenomics: HLAminer supports HLA prediction from third-generation long-read sequencing platforms for research applications.

Methodology:

HLAminer receives streamed sequence alignments directly from read aligners such as minimap2 in SAM format. The protocol involves running minimap2 to align long-read sequencing data and streaming the output directly into HLAminer for HLA class I and class II allele prediction.