A few weeks ago the 2014 AMIA Translational Bioinformatics Meeting (TBI) was held in beautiful San Francisco.  This meeting is full of great science that spans the divide between molecular and clinical research, but a true highlight of this meeting is the closing keynote, traditionally given by Russ Altman.

One of the most powerful tools you can learn to use in genomics research is a relational database system, such as MySQL.  These systems are fairly easy to setup and use, and provide users the ability to organize and manipulate data and statistical results with simple commands.  As a graduate student (during the height of GWAS), this single skill quickly turned me into an “expert”.

Manhattan plots have become the standard way to visualize results for genetic association studies, allowing the viewer to instantly see significant results in the rough context of their genomic position.  Manhattan plots are typically shown on a linear X-axis (although the circos package can be used for radial plots), and this is consistent with the linear representation of the genome in online genome browsers.

Since the near beginning of genome-wide association studies, the PLINK software package (developed by Shaun Purcell’s group at the Broad Institute and MGH) has been the standard for manipulating the large-scale data produced by these studies.

Here are links to all of this year's posts (excluding seminar/webinar announcements), with the most visited posts in bold italic . As always, you can follow me on Twitter for more frequent updates. Happy new year!

Thanks to the excellent work of Lucia Hindorff and colleagues at NHGRI, the GWAS catalog provides a great reference for the cumulative results of GWAS for various phenotypes.  Anyone familiar with GWAS also likely knows about dbGaP – the NCBI repository for genotype-phenotype relationships – and the wealth of data it contains.

In general, the standard practice for correcting for population stratification in genetic studies is to use principal components analysis (PCA) to categorize samples along different ethnic axes .  Price et al. published on this in 2006, and since then PCA plots are a common component of many published GWAS studies.

I’m a bit exhausted from a week of excellent science at ICHG. First, let me say that Montreal is a truly remarkable city with fantastic food and a fascinating blend of architectural styles, all making the meeting a fun place to be…. Now on to the genomics – I’ll recap a few of the most exciting sessions I attended. You can find a live-stream of tweets from the meeting by searching the #ICHG2011 and #ICHG hashtags.

Peter Visscher and colleagues have recently published a flurry of papers employing a new software package called GCTA to estimate the heritability of traits using GWAS data (GCTA stands for Genome-wide Complex Trait Analysis -- clever acronymity!). The tool, supported (and presumably coded) by Jian Yang is remarkably easy to use, based in part on the familiar PLINK commandline interface.

DNA genotyping and sequencing are getting cheaper every day. As Oxford Nanopore CTO Clive Brown recently discussed at Genomes Unzipped, when the cost of a full DNA sequence begins to fall below $1000, the value of having that information far outweighs the cost of data generation.