@article {148, title = {Accurate, scalable cohort variant calls using DeepVariant and GLnexus.}, journal = {Bioinformatics}, year = {2021}, month = {2021 Jan 05}, abstract = {

MOTIVATION: Population-scale sequenced cohorts are foundational resources for genetic analyses, but processing raw reads into analysis-ready cohort-level variants remains challenging.

RESULTS: We introduce an open-source cohort-calling method that uses the highly-accurate caller DeepVariant and scalable merging tool GLnexus. Using callset quality metrics based on variant recall and precision in benchmark samples and Mendelian consistency in father-mother-child trios, we optimized the method across a range of cohort sizes, sequencing methods, and sequencing depths. The resulting callsets show consistent quality improvements over those generated using existing best practices with reduced cost. We further evaluate our pipeline in the deeply sequenced 1000 Genomes Project (1KGP) samples and show superior callset quality metrics and imputation reference panel performance compared to an independently-generated GATK Best Practices pipeline.

AVAILABILITY AND IMPLEMENTATION: We publicly release the 1KGP individual-level variant calls and cohort callset (https://console.cloud.google.com/storage/browser/brain-genomics-public/research/cohort/1KGP) to foster additional development and evaluation of cohort merging methods as well as broad studies of genetic variation. Both DeepVariant (https://github.com/google/deepvariant) and GLnexus (https://github.com/dnanexus-rnd/GLnexus) are open-sourced, and the optimized GLnexus setup discovered in this study is also integrated into GLnexus public releases v1.2.2 and later.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btaa1081}, author = {Yun, Taedong and Li, Helen and Chang, Pi-Chuan and Lin, Michael F and Carroll, Andrew and McLean, Cory Y} } @article {78, title = {Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome.}, journal = {Nat Biotechnol}, volume = {37}, year = {2019}, month = {2019 Oct}, pages = {1155-1162}, abstract = {

The DNA sequencing technologies in use today produce either highly accurate short reads or less-accurate long reads. We report the optimization of circular consensus sequencing (CCS) to improve the accuracy of single-molecule real-time (SMRT) sequencing (PacBio) and generate highly accurate (99.8\%) long high-fidelity (HiFi) reads with an average length of 13.5 kilobases (kb). We applied our approach to sequence the well-characterized human HG002/NA24385 genome and obtained precision and recall rates of at least 99.91\% for single-nucleotide variants (SNVs), 95.98\% for insertions and deletions <50 bp (indels) and 95.99\% for structural variants. Our CCS method matches or exceeds the ability of short-read sequencing to detect small variants and structural variants. We estimate that 2,434 discordances are correctable mistakes in the {\textquoteright}genome in a bottle{\textquoteright} (GIAB) benchmark set. Nearly all (99.64\%) variants can be phased into haplotypes, further improving variant detection. De novo genome assembly using CCS reads alone produced a contiguous and accurate genome with a contig N50 of >15 megabases (Mb) and concordance of 99.997\%, substantially outperforming assembly with less-accurate long reads.

}, issn = {1546-1696}, doi = {10.1038/s41587-019-0217-9}, author = {Wenger, Aaron M and Peluso, Paul and Rowell, William J and Chang, Pi-Chuan and Hall, Richard J and Concepcion, Gregory T and Ebler, Jana and Fungtammasan, Arkarachai and Kolesnikov, Alexey and Olson, Nathan D and T{\"o}pfer, Armin and Alonge, Michael and Mahmoud, Medhat and Qian, Yufeng and Chin, Chen-Shan and Phillippy, Adam M and Schatz, Michael C and Myers, Gene and DePristo, Mark A and Ruan, Jue and Marschall, Tobias and Sedlazeck, Fritz J and Zook, Justin M and Li, Heng and Koren, Sergey and Carroll, Andrew and Rank, David R and Hunkapiller, Michael W} }