Sequencing

11th Annual Sequencing, Finishing, and Analysis in the Future Meeting
A REFERENCE-AGNOSTIC AND RAPIDLY
QUERYABLE NGS READ DATA FORMAT ALLOWS FOR
FLEXIBLE ANALYSIS AT SCALE
Friday, 3rd June 14:20 La Fonda Ballroom Talk (OS‐9.02)
Niranjan Shekar 1 , William Salerno 2 , Adam English 2 , Adina Mangubat 1 ,
Jeremy Bruestle 1 , Eric Boerwinkle 3 , Richard Gibbs 2
1 Spiral Genetics Inc, 2 Human Genome Sequencing Center Baylor College of Medicine,
3 University of Texas Health Science Center at Houston
In identifying the complement of genetic variants that are associated with complex disease, larger
sample sizes increase power. Studies such as the Alzheimer’s Disease Sequencing Project and the
CHARGE Consortium where samples are collected from a range of centers show heterogeneous data,
requiring informatics that can additively scale to thousands of samples and analytics that go beyond
identifying small variants in NGS data. At scale, the challenge of evaluating SNPs, indels and SVs
becomes the “N+1” problem of incrementally adding samples without having to perpetually
reevaluate petabytes of population read data stored in BAM files.
The Biograph Analysis Format (BAF) is a method of indexing NGS data that extends the Burrows
Wheeler Transform to allow for multiple paths, effectively creating a read overlap graph of the data.
A BAF of HiSeq X 30x WGS data is 8.3 Gb, 95% smaller than the corresponding BAM. Generated
from the BAM in 14 hours, the BAF can be queried up to 200,000 times a second. Multiple BAFs
can be combined, which at scale results in a file size of approximately 3GB per individual. Because
the BAF can be batched across individuals, query time grows less than linearly with the number of
individuals.
For example, if 30,000 putative SV sites to be queried, SV‐typing these sites across 10,000 HiSeq X
WGS samples in BioGraph Analysis Format would require less than 30 TB of storage (for all the
read data), 16 CPU hours, and 10 minutes (using 100 machines).
Here, we perform read over assembly to genotype 4,276 SVs larger than 80bp detected in at least one
individual of the Ashkenazi Jewish Trio by Pindel. At 1,195 of these locations, there was at least
one SV call in any one individual and all of these calls, except for 25 (2.1%) were consistent with
mendelian inheritance. Further, read overlap assembly to genotype variants was performed at 3,935
locations where PBHoney called an SV with long read sequencing data on the same Trio. Of those,
1,327 locations had at least one genotype with all but 55 (4.1%) being consistent with mendelian
inheritance.
Additionally, the data are reference‐agnostic, so variants can be called against any reference or against
the read graph of any other set of individuals, dramatically reducing the time for data harmonization.
Further, information is divided such that the “read overlap graph” created from all the individuals
is separate from the information indicating that path through the graph for each individual. This
allows a search for a particular variation of interest directly from the read data remotely and
rapidly, without the opportunity to reveal the exact individual(s) from that the variant originates.
Because the data are essentially a read overlap graph, it is possible to accurately characterize SVs
by traversing the graph from a particular location or search for a particular sequence associated
with the SV. So, fast querying of small files with reasonable compute requirements provides an N+1
solution for SVs.
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