Becky L Drees

US Patent:

20120053845, Mar 1, 2012

Filed:

Apr 27, 2011

Appl. No.:

13/095707

Inventors:

Jeremy Bruestle - Seattle WA, US
Becky Drees - Seattle WA, US
Tim Hunkapillar - Seattle WA, US

International Classification:

G06F 19/18

US Classification:

702 20

Abstract:

In one method embodiment low-coverage genome sequence data for each individual in a group of related individuals is obtained, the alignment of read sequences is determined relative to a reference sequence and to each other in a padded multiple alignment, the relative likelihoods of the observed base calls and quality scores obtained from the set of sequence reads for each individual for each position are determined for possible individual genotypes at that position, the most likely shared genotype between individuals for each position is determined to define a multi-individual consensus for each position, and individual genotypes and confidence levels are imputed to produce an error-corrected genome sequence for each individual.

US Patent:

20160246921, Aug 25, 2016

Filed:

Feb 25, 2015

Appl. No.:

14/631791

Inventors:

- Seattle WA, US
Becky L. Drees - Seattle WA, US

International Classification:

G06F 19/22
G06F 19/16

Abstract:

DNA assembly techniques for a DNA dataset comprised of DNA sequence reads make use of anchor points identified using a reference DNA sequence. Because the anchor point technique is dependent on a high accuracy dataset, related techniques to detect erroneous reads and to correct erroneous reads making use of k-Mer and statistical techniques are also disclosed. Upon preparing a high accuracy dataset, a read overlap graph is generated that removes exact matches with respect to the reference DNA sequence, thereby leaving behind potential structural variants. Using anchor points representing closed matches to the reference DNA dataset, the read overlap graph is traversed to detect potential structural variants. The structural variants are then validated. Use cases for anchor assembly and related techniques, including multi-sample differential variant detection are also disclosed.