Abstract

Single-molecule long-read sequencing datasets were generated for a son-father-mother trio of Han Chinese descent that is part of the Genome in a Bottle (GIAB) consortium portfolio. The dataset was generated using the Pacific Biosciences Sequel System. The son and each parent were sequenced to an average coverage of 60 and 30, respectively, with N50 subread lengths between 16 and 18 kb. Raw reads and reads aligned to both the GRCh37 and GRCh38 are available at the NCBI GIAB ftp site (ftp://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/ChineseTrio/). The GRCh38 aligned read data are archived in NCBI SRA (SRX4739017, SRX4739121, and SRX4739122). This dataset is available for anyone to develop and evaluate long-read bioinformatics methods.

Alternate abstract:

Design Type(s)individual genetic characteristics comparison design • genotype designMeasurement Type(s)whole genome sequencing assayTechnology Type(s)DNA sequencingFactor Type(s)relationship • sexSample Characteristic(s)Homo sapiens

Machine-accessible metadata file describing the reported data (ISA-Tab format)

Details

Title
High-coverage, long-read sequencing of Han Chinese trio reference samples
Author
Wang, Ying-Chih 1 ; Olson, Nathan D 2   VIAFID ORCID Logo  ; Deikus, Gintaras 1 ; Shah, Hardik 1 ; Wenger, Aaron M 3   VIAFID ORCID Logo  ; Trow, Jonathan 4 ; Xiao, Chunlin 4 ; Sherry, Stephen 4 ; Salit, Marc L 5 ; Zook, Justin M 2 ; Smith, Melissa 6 ; Sebra, Robert 6 

1  Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA 
2  Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA 
3  Pacific Biosciences, Menlo Park, CA, USA 
4  National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA 
5  Joint Initiative for Metrology in Biology, Stanford, CA, USA 
6  Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Institute of Data Science and Genomic Technology, New York, NY, USA 
Pages
1-5
Publication year
2019
Publication date
Dec 2019
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41597-019-0098-2
ProQuest document ID
2240137579
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.