Linked-read sequencing promises a one-method approach for genome-wide insights including single nucleotide variants (SNVs), structural variants, and haplotyping. We introduce Barcode Linked Reads (BLR), an open-source haplotyping pipeline capable of handling millions of barcodes and data from multiple linked-read technologies including DBS, 10× Genomics, TELL-seq and stLFR. Running BLR on DBS linked-reads yielded megabase-scale phasing with low (<0.2%) switch error rates. Of 13616 protein-coding genes phased in the GIAB benchmark set (v4.2.1), 98.6% matched the BLR phasing. In addition, large structural variants showed concordance with HPRC-HG002 reference assembly calls. Compared to diploid assembly with PacBio HiFi reads, BLR phasing was more continuous when considering switch errors. We further show that integrating long reads at low coverage (∼10×) can improve phasing contiguity and reduce switch errors in tandem repeats. When compared to Long Ranger on 10× Genomics data, BLR showed an increase in phase block N50 with low switch-error rates. For TELL-Seq and stLFR linked reads, BLR generated longer or similar phase block lengths and low switch error rates compared to results presented in the original publications. In conclusion, BLR provides a flexible workflow for comprehensive haplotype analysis of linked reads from multiple platforms.

Cancer genomes are prone to elevated rates of genomic alterations. Massive parallel sequencing technologies can answer some questions related to these aberrations; however, they remain limited when it comes to resolving the haplotype information. In this study, we applied the linked-read droplet barcode sequencing (DBS) technology to resolve the haplotype complexity of colorectal cancer genomes, using paired tumor/normal samples. The results show short somatic variants associated with almost all TCGA-identified oncogenic pathways. Several cancer-related genes had multiple variants in either one or both haplotypes. In the tumor suppressor gene APC, two nonsense variants ~2kb apart on separate haplotypes were identified in one patient. Additionally, a number haplotype-resolved somatic structural variants (SV) and copy number alterations (CNA) were detected and correlated with the small variants. The study demonstrates that DBS technology can characterize complex genetic variations in a haplotype context, revealing an extra layer of cancer genome complexity.