The Personal Genome Project-UK, an open access resource of human multi-omics data

Abstract

Integrative analysis of multi-omics data is a powerful approach for gaining functional insights into biological and medical processes. Conducting these multifaceted analyses on human samples is often complicated by the fact that the raw sequencing output is rarely available under open access. The Personal Genome Project UK (PGP-UK) is one of few resources that recruits its participants under open consent and makes the resulting multi-omics data freely and openly available. As part of this resource, we describe the PGP-UK multi-omics reference panel consisting of ten genomic, methylomic and transcriptomic data. Specifically, we outline the data processing, quality control and validation procedures which were implemented to ensure data integrity and exclude sample mix-ups. In addition, we provide a REST API to facilitate the download of the entire PGP-UK dataset. The data are also available from two cloud-based environments, providing platforms for free integrated analysis. In conclusion, the genotype-validated PGP-UK multi-omics human reference panel described here provides a valuable new open access resource for integrated analyses in support of personal and medical genomics.

Fig. 1

PGP-UK workflow. Horizontal panels depict the general sample/data categories and options (e.g blood and/or saliva) and vertical panels depict specific data types and their flow from start to end.

Fig. 2

PGP-UK QC images for WGS, WGBS, RNA-seq and 450 k methylation data. (a) WGS coverage depth plot. (b) WGBS coverage depth plot. (c) RNA-seq reads distribution over the different genome features. (d) Density plot for Illumina 450 k methylation profiles.

Fig. 3

Multi-Omics Data Matching. (a) Multi-Omics Data Matching Schema. 65 loci were used in matching WGS with methylation and WGBS data, 279 loci were used in matching WGS with RNA-seq data. (b) Correlation plot displaying matching results for WGS vs. 450 k datasets. (c) Correlation plot displaying matching results for WGS vs. WGBS datasets. (d) Correlation plot displaying matching results for WGS vs. RNA-seq datasets. On correlation plots (b–d) scale is represented by the combination of ball size and colour (from white to dark blue) and goes from 0 (0% match) to 1 (perfect 100% match).