Archive for October, 2014

The Anopheles gambiae 1000 genomes project is presenting us with some technical challenges, as genetic diversity within the mosquito populations we are studying is extremely high. Although the A. gambiae reference genome (~250Mb) is an order of magnitude smaller than the human genome, we still discover about 100 million SNPs, of which about half pass a reasonably conservative set of filters, which works out to about 1 good SNP every 5 bases or so.

Doing any kind of exploratory analysis of a dataset of ~100 million SNPs genotyped across ~1000 samples is difficult, and working directly from VCF files is impractical, because of the time it takes to parse. Genotype calls can be represented as two-dimensional arrays of numerical data, and there are a number of well-established and emerging software tools and standards for dealing in a generic way with large multi-dimensional arrays, so we’ve been doing some investigation and trying to leverage this work to speed up our analysis workflow.

In particular, the HDF5 format is well supported, and we’ve got a lot of mileage out of it already. I’ve been working on a package called vcfnp which provides support for converting data from a VCF file first into NumPy arrays, and from there to HDF5. You have to make some choices when loading data into an HDF5 file, in particular what type of compression to use, and how to chunk the data. In order to make an informed decision, I did some benchmarking, looking at performance under a number of access scenarios, comparing different compression options and chunk layouts.

The main finding was that using a chunk size of around 128kb, and a fairly narrow chunk width of around 10, provides a very good compromise solution, with good read performance under both column-wise and row-wise access patterns. While other compression options are available and are slightly faster, gzip is very acceptable, and is more widely supported, so we’ll be sticking with that for now. See the notebook linked above for the gory details.

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Anopheles gambiae 1000 genomes project

Posted: 22 October 2014 by Alistair Miles in Uncategorized

Back in June we officially launched the Anopheles gambiae 1000 genomes project, which is a consortial project generating and analysing whole genome sequence data on wild-caught mosquitoes of the species Anopheles gambiae and Anopheles coluzzii, the major vectors of Plasmodium falciparum malaria in Africa.

Along with the initial web page, we also made our first data release. The phase 1 preview release contains genotype data on 103 mosquitoes from Uganda, contributed by Martin Donnelly and David Weetman of the Liverpool School of Tropical Medicine. VCF files are available to download from the Ag1000G public FTP site, and there is also an early version of the Panoptes web application which provides an interactive environment for exploring the data.

The consortium is currently working hard on preparing and analysing the full phase 1 dataset, which comprises 765 samples from 8 countries spanning sub-Saharan Africa. We hope to release at least a beta version of these data before the end of the year, I’ll post here when it’s available.