IP Library Patent Application 15574363
Patent Application
App. No. 15/574,363

SYSTEMS AND METHODS FOR PROVIDING IMPROVED PREDICTION OF CARRIER STATUS FOR SPINAL MUSCULAR ATROPHY

Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US None
App. No.
15/574,363
Abstract

Systems and methods of improved genetic mutation carrier screening may include, for a plurality of genetically similar genes in a reference genome, the plurality of genetically similar genes comprising a functional gene and a non-functional gene, masking the non-functional gene from the reference genome; aligning a plurality of functional gene reads and a plurality of non-functional gene reads of a patient's genetic sequence to the functional gene in the reference genome; tallying, at a first polymorphic locus-of-interest on each aligned read, a respective nucleotide type, wherein functional gene reads comprise a different nucleotide type than non-functional gene reads at the first polymorphic locus-of-interest; and calculating, based at least in part on a result of the tallying, a first gene ratio, wherein the first gene ratio indicates a first ratio of functional gene reads to non-functional gene reads.

Claims (70)

1 . A method of improved genetic mutation carrier screening, performed on a computer having a processor, memory, and one or more code sets stored in the memory and executing in the processor, the method comprising:

for a plurality of genetically similar genes in a reference genome, the plurality of genetically similar genes comprising a functional gene (FG) and a non-functional gene (NFG), masking, by the processor, the NFG from the reference genome;

aligning, by the processor, a plurality of FG reads and a plurality of NFG reads of a patient's genetic sequence to the FG in the reference genome;

tallying, by the processor, at a first polymorphic locus-of-interest (LOI) on each aligned read, a respective nucleotide type, wherein FG reads comprise a different nucleotide type than NFG reads at the first polymorphic LOI; and

calculating, by the processor, based at least in part on a result of the tallying, a first gene ratio, wherein the first gene ratio indicates a first ratio of FG reads to NFG reads.

2 . The method as in claim 1 , further comprising:

applying, by the processor, a statistical model to the first gene ratio; and

determining, by the processor, a probability of a carrier status based at least in part on the first gene ratio.

3 . The method as in claim 1 , further comprising:

for at least one other polymorphic LOI on each aligned read, tallying, by the processor, a respective number of each of a plurality of nucleotide types, wherein FG reads comprise a different nucleotide type than NFG reads at the at least one other polymorphic LOI; and

calculating, by the processor, based at least in part on a result of the tallying at the at least one other polymorphic LOI, a second gene ratio, wherein the second gene ratio indicates a second ratio of FG reads to NFG reads.

4 . The method as in claim 3 , further comprising:

determining whether the first gene ratio and the second gene ratio are within a tolerance threshold;

applying, by the processor, a statistical model to the first gene ratio and the second gene ratio, when the first gene ratio and the second gene ratio are within a tolerance threshold; and

determining, by the processor, a probability of a carrier status given the first gene ratio and the second gene ratio.

5 . The method as in claim 4 , wherein the threshold tolerance is less than or equal to 10%.

6 . The method as in claim 1 , wherein the FG is the SMN1 gene and the NFG is the SMN2 gene.

7 . The method as in claim 2 , further comprising:

identifying, by the processor, one or more housekeeping genes;

calculating, by the processor, a scaling factor based on a ratio of an average number of FG reads to an average number of the one or more housekeeping genes; and

normalizing, by the processor, the determined probability of a carrier status based at least in part on the scaling factor.

8 . The method as in claim 7 , wherein identifying the one or more housekeeping genes further comprises:

identifying, by the processor, one or more housekeeping genes which pass a preliminary coverage filter; and

determining, by the processor, whether the one or more identified housekeeping genes at least one of:

does not exceed an average coverage variability threshold; and

does not exceed a proportion variability threshold, wherein the proportion variability threshold is applied to a proportion of an average coverage for the FG to an average coverage for a particular housekeeping gene.

9 . A system for improved genetic mutation carrier screening, comprising:

a computer having:

a processor;

a memory; and

one or more code sets stored in the memory and executing in the processor, which, when executed, configure the processor to:

for a plurality of genetically similar genes in a reference genome, the plurality of genetically similar genes comprising a functional gene (FG) and a non-functional gene (NFG), mask the NFG from the reference genome;

align a plurality of FG reads and a plurality of NFG reads of a patient's genetic sequence to the FG in the reference genome;

tally at a first polymorphic locus-of-interest (LOI) on each aligned read, a respective nucleotide type, wherein FG reads comprise a different nucleotide type than NFG reads at the first polymorphic LOI; and

calculate, based at least in part on a result of the tallying, a first gene ratio, wherein the first gene ratio indicates a first ratio of FG reads to NFG reads.

10 . The system as in claim 9 , further configured to:

apply a statistical modeling algorithm to the first gene ratio; and

determine a probability of a carrier status based at least in part on the first gene ratio.

11 . The system as in claim 9 , further configured to:

for at least one other polymorphic LOI on each aligned read, tally a respective nucleotide type, wherein FG reads comprise a different nucleotide type than NFG reads at the at least one other polymorphic LOI; and

calculate, based at least in part on a result of the tallying at the at least one other polymorphic LOI, a second gene ratio, wherein the second gene ratio indicates a second ratio of FG reads to NFG reads.

12 . The system as in claim 11 , further configured to:

determine whether the first gene ratio and the second gene ratio are within a tolerance threshold;

apply a statistical modeling algorithm to the first gene ratio and the second gene ratio, when the first gene ratio and the second gene ratio are within a tolerance threshold; and

determine a probability of a carrier status given the first gene ratio and the second gene ratio.

13 . The system as in claim 12 , wherein the threshold tolerance is less than or equal to 10%.

14 . The system as in claim 9 , wherein the FG is the SMN1 gene and the NFG is the SMN2 gene.

15 . The system as in claim 10 , further configured to:

identify one or more housekeeping genes;

calculate a scaling factor based on a ratio of an average number of FG reads to an average number of the one or more housekeeping genes; and

normalize the determined probability of a carrier status based at least in part on the scaling factor.

16 . The system as in claim 15 , further configured to:

identify one or more housekeeping genes which pass a preliminary coverage filter; and

determine whether the one or more identified housekeeping genes at least one of:

does not exceed an average coverage variability threshold; and

does not exceed a proportion variability threshold, wherein the proportion variability threshold is applied to a proportion of an average coverage for the FG to an average coverage for a particular housekeeping gene.

17 . A method of improved genetic mutation carrier screening, performed on a computer having a processor, memory, and one or more code sets stored in the memory and executing in the processor, the method comprising:

for a plurality of genetically similar genes in a reference genome, the plurality of genetically similar genes comprising a functional gene (FG) and a non-functional gene (NFG), aligning, by the processor, a plurality of FG reads and a plurality of NFG reads of a patient's genetic sequence to the FG in the reference genome;

tallying, by the processor, at a first polymorphic locus-of-interest (LOI) on each aligned read, a respective nucleotide type, wherein FG reads comprise a different nucleotide type than NFG reads at the first polymorphic LOI; and

calculating, by the processor, based at least in part on a result of the tallying, a first gene ratio, wherein the first gene ratio indicates a first ratio of FG reads to NFG reads.

18 . The method as in claim 17 , further comprising:

applying, by the processor, a statistical modeling algorithm to the first gene ratio; and

determining, by the processor, a probability of a carrier status based at least in part on the first gene ratio.

19 . The method as in claim 17 , further comprising:

for at least one other polymorphic LOI on each aligned read, tallying, by the processor, a respective nucleotide type, wherein FG reads comprise a different nucleotide type than NFG reads at the at least one other polymorphic LOI; and

calculating, by the processor, based at least in part on a result of the tallying at the at least one other polymorphic LOI, a second gene ratio, wherein the second gene ratio indicates a second ratio of FG reads to NFG reads.

20 . The method as in claim 19 , further comprising:

determining whether the first gene ratio and the second gene ratio are within a tolerance threshold;

applying, by the processor, a statistical modeling algorithm to the first gene ratio and the second gene ratio, when the first gene ratio and the second gene ratio are within a tolerance threshold; and

determining, by the processor, a probability of a carrier status given the first gene ratio and the second gene ratio.

Assignments (7)
SECURITY INTEREST Recorded Dec 7, 2020
From: ANCESTRY.COM DNA, LLC; ANCESTRY.COM OPERATIONS INC.; IARCHIVES, INC.; ANCESTRYHEALTH.COM, LLC
To: WILMINGTON TRUST, NATIONAL ASSOCIATION
Reel/Frame 054627/0237 →
SECURITY INTEREST Recorded Dec 7, 2020
From: ANCESTRY.COM DNA, LLC; ANCESTRY.COM OPERATIONS INC.; IARCHIVES, INC.; ANCESTRYHEALTH.COM, LLC
To: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
Reel/Frame 054627/0212 →
RELEASE OF SECURITY INTEREST Recorded Nov 1, 2019
From: WESTERN ALLIANCE BANK
To: GENEPEEKS, INC.
Reel/Frame 050892/0394 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 17, 2018
From: GENEPEEKS, INC.
To: GENEPEEKS (ABC), LLC
Reel/Frame 047796/0385 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 17, 2018
From: GENEPEEKS (ABC), LLC
To: ANCESTRY.COM DNA, LLC
Reel/Frame 047796/0644 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 9, 2018
From: SILVER, LEE
To: GENEPEEKS, INC.
Reel/Frame 047715/0546 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 2, 2018
From: SILVER, ARI JULIAN; LARSON, JESSICA L.; BORROTO, CARLOS; SPURRIER, BRETT
To: GENEPEEKS, INC.
Reel/Frame 047032/0845 →