Blogging My Genome, episode 6: variant calling, filtering, and QC

This is the sixth in a series of blog posts about my genome, which I recently had sequenced through Illumina's Understand Your Genome program.

I'd previously generated mappings of my sequence reads to the hs37d5 reference assembly. The next step is variant calling, to systematically identify the differences between my genome and the reference. There's a variety of popular tools for this, from which I selected FreeBayes to try first. FreeBayes is an example of a relatively new generation of algorithms capable of considering many hypothetical combinations of genetic variation and sequence alignments to explain the short read data mapped to a genomic region - all within a Bayesian statistical model, per the name.

FreeBayes took my BAM file and the hs37d5 reference as input, and produced a VCF (Variant Call Format) file with genome-wide calls. This took about 32 core-hours (parallelized on an 8-core cloud instance) and produced a VCF file of 377 MiB compressed - tiny compared to my 63 GiB BAM file, as it doesn't preserve the individual reads. Here's the one-line entry of my VCF file corresponding to my ALDH2*2 variant from last time:

$ dx cat "My Genome Analysis:/C2K.deduplicated.vcf.gz" | zcat | grep "12[[:space:]]112241766"
12 112241766 . G A 1264 . AB=0;ABP=0;AC=2;AF=1;AN=2;AO=42;CIGAR=1X;DP=42;DPB=42;DPRA=0;EPP=23.691;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=58.5772;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=1467;QR=0;RO=0;RPP=4.87156;RPPR=0;RUN=1;SAF=27;SAP=10.4553;SAR=15;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1 GT:DP:RO:QR:AO:QA:GL 1/1:42:0:0:42:1467:-10,-10,0

This line indicates that, at position #112,241,766 on chromosome 12, the reference assembly has a G but my reads indicate I've got an A. Further, the "1/1" prefixing the last string indicates I'm homozygous for the A, as all of my reads show it. Most of the nearly five million calls in my VCF are biallelic single-nucleotide variants (SNVs) like this one, but FreeBayes also calls more complex variation like indels and regions with two different non-reference alleles. Unfortunately, not all of them can be trusted immediately.

Blogging My Genome, episode 4: read mapping

This is the fourth in a series of blog posts about my genome, which I recently had sequenced through Illumina's Understand Your Genome program.

Last week's data wrangling produced eight FASTQ files containing the sequencing reads for my genome ($8=4 \times 2$, four lanes' worth of paired-end reads). The next step in making sense of these 1.3 billion reads is to map their positions of origin in the human reference genome assembly. This post will continue somewhat down in the weeds technically, but we'll end up in position to look at some interesting genetics next time.

If you're not interested in the technical minutiae - and that would be fair enough - you could skip to the last section.

Reads quality control with FastQC

Trust, but verify: since my data came from Illumina's CLIA lab, I wasn't terribly worried about gross quality problems - but some QC is always prudent before proceeding further. We have an app on DNAnexus to run reads through FastQC, which runs some essential sanity checks. I ran these on my four pairs of FASTQ files to get four FastQC reports. (It's worth examining the four lanes separately, because they could conceivably have independent quality issues.) Here's one representative plot:

Blogging My Genome, episode 3: data wrangling

After learning about Illumina's Understand Your Genome (UYG) program at ASHG 2013, I decided to sign up to get my genome sequenced. This is the third in a series of blog posts I'm writing about my own adventure in very personal genomics.

Along with my clinical report, Illumina delivered a portable hard drive (pictured) containing the underlying next-generation sequencing data. Given my computational genomics background, this was the product I'd most been looking forward to receiving. In fact, after picking it up, I found myself hastily biking five miles through the rain to get it to a computer!

The drive is protected using TrueCrypt, with the encryption key e-mailed separately. I installed the TrueCrypt on my Linux workstation, mounted the drive, and started to look around:

Working with cross-species genome alignments on the DNAnexus platform

I've recently been resurrecting some comparative genomics methods I developed in my last year of grad school, but never got to publish. These build on previous work to locate what we called Synonymous Constraint Elements (SCEs) in the human genome: short stretches within protein-coding ORFs that also encode additional, overlapping functional elements - evidenced by a markedly reduced apparent rate of synonymous substitutions in cross-species alignments. The first step in this analysis, and the subject of this post, involves extracting the cross-species sequence alignments of protein-coding ORFs from raw, whole-genome alignments. I hope to write a series of blog posts as I get various other parts of the pipeline going. I'm not exactly sure where it'll go from there, but it's pretty neat stuff I would eventually like to get peer-reviewed!