Skip to main content
SNV Frequencies Australia MGRB 4k WGS Track Settings
 
SNV Frequencies: Australia Medical Genome Reference Bank - 4,011 WGS

Configure track container: SNV Frequencies from various cohorts or national projects

+  Description
+  All tracks in this collection (35)

Display mode:      Duplicate track

Sorry, couldn't access VCF file.


Display data as a density graph:

VCF configuration help

(Download unavailable, see below)
Version: Phase 3
Assembly: Human Dec. 2013 (GRCh38/hg38)

Description

The Australian Medical Genome Reference Bank (MGRB) collected whole-genome sequencing data of 4,011 healthy elderly individuals who lived ≥70 years, so the dataset is depleted of damaging genetic variants. Age and sex summary graphs are available from the MGRB website.

Data Access

Due to license restrictions, the data for this track cannot be downloaded from the UCSC Genome Browser. The Table Browser, Data Integrator, and download server are not available for this track.

VCF access can be requested via a form from Sydney Genomics.

Methods

The 4,011 MGRB samples underwent whole-genome sequencing on Illumina HiSeq X instruments at KCCG under ISO 15189 accreditation, with paired-end TruSeq DNA Nano libraries sequenced one lane per sample. Sequence reads were aligned to the hg38 reference genome assembly with bwa 0.7.15-r1140. Variants were called with GATK 4.1.4.0 following the Genome Analysis Toolkit (GATK) best practices procedure. A sites-only VCF with only passing variants (FILTER=PASS) was made with bcftools 1.20.

We received VCF files from m.hobbs@garvan.org.au via a transfer link and imported them. The makeDoc file of the track documents how all source files of the varFreqs track were converted. For some tracks, python scripts were needed; these are available from GitHub.

References

Lacaze P, Pinese M, Kaplan W, Stone A, Brion MJ, Woods RL, McNamara M, McNeil JJ, Dinger ME, Thomas DM. The Medical Genome Reference Bank: a whole-genome data resource of 4000 healthy elderly individuals. Rationale and cohort design. Eur J Hum Genet. 2019 Feb;27(2):308-316. PMID: 30353151; PMC: PMC6336775