biostudies-literatureTang FNational Key R&amp;D Program of ChinaNational Key R&D Program of China470https://www.ebi.ac.uk/biostudies/studies/S-EPMC11092001biostudies-literatureUnknown25(1)<h4>Background</h4>The absence of heterozygosity (AOH) is a kind of genomic change characterized by a long contiguous region of homozygous alleles in a chromosome, which may cause human genetic disorders. However, no method of low-pass whole genome sequencing (LP-WGS) has been reported for the detection of AOH in a low-pass setting of less than onefold. We developed a method, termed CNVseq-AOH, for predicting the absence of heterozygosity using LP-WGS with ultra-low sequencing data, which overcomes the sparse nature of typical LP-WGS data by combing population-based haplotype information, adjustable sliding windows, and recurrent neural network (RNN). We tested the feasibility of CNVseq-AOH for the detection of AOH in 409 cases (11 AOH regions for model training and 863 AOH regions for valBMC genomicsRecurrent neural network for predicting absence of heterozygosity from low pass WGS with ultra-low depth.PMC110920012023YFC2705600Xie XGuo XYan SJiang TTang FSun YQiao ZMan JPeng ZWang LPeng HSong LLi YYang YWang SFan LWang XWang YWang ZfalseRecurrent neural network for predicting absence of heterozygosity from low pass WGS with ultra-low depth.<h4>Background</h4>The absence of heterozygosity (AOH) is a kind of genomic change characterized by a long contiguous region of homozygous alleles in a chromosome, which may cause human genetic disorders. However, no method of low-pass whole genome sequencing (LP-WGS) has been reported for the detection of AOH in a low-pass setting of less than onefold. We developed a method, termed CNVseq-AOH, for predicting the absence of heterozygosity using LP-WGS with ultra-low sequencing data, which overcomes the sparse nature of typical LP-WGS data by combing population-based haplotype information, adjustable sliding windows, and recurrent neural network (RNN). We tested the feasibility of CNVseq-AOH for the detection of AOH in 409 cases (11 AOH regions for model training and 863 AOH regions for val2024-01-01T00:00:00Z2024 May2026-04-12T15:29:48.283Z2026-04-07T13:17:54.774ZS-EPMC110920013874514110.1186/s12864-024-10400-4