Title:
DEEP LEARNING-BASED VARIANT CLASSIFIER
Document Type and Number:
WIPO Patent Application WO/2019/140402
Kind Code:
A1
Abstract:
The technology disclosed directly operates on sequencing data and derives its own feature filters. It processes a plurality of aligned reads that span a target base position. It combines elegant encoding of the reads with a lightweight analysis to produce good recall and precision using lightweight hardware. For instance, one million training examples of target base variant sites with 50 to 100 reads each can be trained on a single GPU card in less than 10 hours with good recall and precision. A single GPU card is desirable because it a computer with a single GPU is inexpensive, almost universally within reach for users looking at genetic data. It is readily available on could-based platforms.
Inventors:
SCHULZ-TRIEGLAFF OLE BENJAMIN (GB)
COX ANTHONY JAMES (GB)
FARH KAI-HOW (US)
COX ANTHONY JAMES (GB)
FARH KAI-HOW (US)
Application Number:
PCT/US2019/013534
Publication Date:
July 18, 2019
Filing Date:
January 14, 2019
Export Citation:
Assignee:
ILLUMINA INC (US)
ILLUMINA CAMBRIDGE LTD (GB)
ILLUMINA CAMBRIDGE LTD (GB)
International Classes:
G06N3/04; G16B20/20; G16B40/00
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M. SANDLER; A. HOWARD; M. ZHU; A. ZHINOGINOV; L. CHEN: "MobileNetV2: Inverted Residuals and Linear Bottlenecks", ARXIV:1801.04381V3, 2018
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T SAUNDERS, CHRISTOPHER; WONG, WENDY; SWAMY, SAJANI; BECQ, JENNIFER; J MURRAY, LISA; CHEETHAM, KEIRA: "Strelka: Accurate somatic small-variant calling from sequenced tumor-nonnal sample pairs", BIOINFORMATICS, vol. 28, 2012, pages 1811 - 7, XP055257165, DOI: doi:10.1093/bioinformatics/bts271
STROMBERG, MICHAEL; ROY, RAJAT; LAJUGIE, JULIEN; JIANG, YU; LI, HAOCHEN; MARGULIES, ELLIOTT, NIRVANA: CLINICAL GRADE VARIANT ANNOTATOR, 2017, pages 596 - 596
A. G. HOWARD; M. ZHU; B. CHEN; D. KALENICHENKO; W. WANG; T. WEYAND; M. ANDREETTO; H. ADAM: "Mobilenets: Efficient Convolutional Neural Networks for Mobile Vision Applications", ARXIV: 1704.04861, 2017
I. J. GOODFELLOW; D. WΗRDE-FARLEY; M. MIRZA; A. COURVILLE; Y. BENGIO: "Deep Learning", 2016, MIT PRESS, article "CONVOLUTIONAL NETWORKS"
"BATCH NORMALIZATION: ACCELERATING DEEP NETWORK TRAINING BY REDUCING INTERNAL COVARIATE SHIFT", ARXIV: 1502.03167, 2015
H. Y. XIONG ET AL: "The human splicing code reveals new insights into the genetic determinants of disease", SCIENCE, vol. 347, no. 6218, 18 December 2014 (2014-12-18), US, pages 1254806 - 1254806, XP055551008, ISSN: 0036-8075, DOI: 10.1126/science.1254806
SANGTAE KIM ET AL: "Strelka2: Fast and accurate variant calling for clinical sequencing applications", BIORXIV, 25 September 2017 (2017-09-25), XP055574094, Retrieved from the Internet
T SAUNDERS, CHRISTOPHER; WONG, WENDY; SWAMY, SAJANI; BECQ, JENNIFER; J MURRAY, LISA; CHEETHAM, KEIRA: "Strelka: Accurate somatic small-variant calling from sequenced tumor-normal sample pairs", BIOINFORMATICS (OXFORD, ENGLAND, vol. 28, 2012, pages 1811 - 7, XP055257165, DOI: doi:10.1093/bioinformatics/bts271
A. VAN DEN OORD; S. DIELEMAN; H. ZEN; K. SIMONYAN; O. VINYALS; A. GRAVES; N. KALCHBRENNER; A. SENIOR; K. KAVUKCUOGLU: "WAVENET: A GENERATIVE MODEL FOR RAW AUDIO", ARXIV: 1609.03499, 2016
S. 0. ARIK; M. CHRZANOWSKI; A. COATES; G. DIAMOS; A. GIBIANSKY; Y. RANG; X. LI; J. MILLER; A. NG; J. RAIMAN: "DEEP VOICE: REAL-TIME NEURAL TEXT-TO-SPEECH", ARXIV: 1702.07825, 2017
F. YU; V. KOLTUN: "MULTI-SCALE CONTEXT AGGREGATION BY DILATED CONVOLUTIONS", ARXIV:1511.07122, 2016
K. HE; X. ZHANG; S. REN; J. SUN: "DEEP RESIDUAL LEARNING FOR IMAGE RECOGNITION", ARXIV: 1512.03385, 2015
R.K. SRIVASTAVA; K. GREFF; J. SCHMIDHUBER: "HIGHWAY NETWORKS", ARXIV: 1505.00387, 2015
G. HUANG; Z. LIU; L. VAN DER MAATEN; K. Q. WEINBERGER: "DENSELY CONNECTED CONVOLUTIONAL NETWORKS", ARXIV: 1608.06993, 2017
C. SZEGEDY; W. LIU; Y. JIA; P. SERMANET; S. REED; D. ANGUELOV; D. ERHAN; V. VANHOUCKE; A. RABINOVICH: "GOING DEEPER WITH CONVOLUTIONS", ARXIV: 1409.4842, 2014
S. IOFFE; C. SZEGEDY: "BATCH NORMALIZATION: ACCELERATING DEEP NETWORK TRAINING BY REDUCING INTERNAL COVARIATE SHIFT", ARXIV: 1502.03167, 2015
SRIVASTAVA, NITISH; HINTON. GEOFFREY; KRIZHEVSKY, ALEX; SUTSKEVER. ILYA; SALAKHUTDINOV, RUSLAN: "DROPOUT: A SIMPLE WAY TO PREVENT NEURAL NETWORKS FROM OVERFITTING", THE JOURNAL OF MACHINE LEARNING RESEARCH, vol. 15, no. 1, 2014, pages 1929 - 1958, XP055193568
J. M. WOLTERINK; T. LEINER; M. A. VIERGEVER; I. IŠGUM: "DILATED CONVOLUTIONAL NEURAL NETWORKS FOR CARDIOVASCULAR MR SEGMENTATION IN CONGENITAL HEART DISEASE", ARXIV: 1704.03669, 2017
L. C. PIQUERAS: "AUTOREGRESSIVE MODEL BASED ON A DEEP CONVOLUTIONAL NEURAL NETWORK FOR AUDIO GENERATION", TAMPERE UNIVERSITY OF TECHNOLOGY, 2016
J. WU: "Introduction to Convolutional Neural Networks", 2017, NANJING UNIVERSITY
I. J. GOODFELLOW; D. WARDE-FARLEY; M. MIRZA; A. COURVILLE; Y. BENGIO: "Deep Learning", 2016, MIT PRESS, article "CONVOLUTIONAL NETWORKS"
J. GU; Z. WANG; J. KUEN; L. MA; A. SHAHROUDY; B. SHUAI; T. LIU; X. WANG; G. WANG: "RECENT ADVANCES IN CONVOLUTIONAL NEURAL NETWORKS", ARXIV:1512.07108, 2017
M. LIN; Q. CHEN; S. YAN: "Network in Network", PROC. OF ICLR, 2014
L. SIFRE: "Rigid-motion Scattering for Image Classification", PH.D. THESIS, 2014
L. SIFRE; S. MALLAT: "Rotation, Scaling and Deformation Invariant Scattering for Texture Discrimination", PROC. OF CVPR, 2013
F. CHOLLET: "Xception: Deep Learning with Depthwise Separable Convolutions", PROC. OF CVPR, 2017
X. ZHANG; X. ZHOU; M. LIN; J. SUN: "ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices", ARXIV: 1707.01083, 2017
K. HE; X. ZHANG; S. REN; J. SUN: "Deep Residual Learning for Image Recognition", PROC. OF CVPR, 2016
S. XIE; R. GIRSHICK; P. DOLLIR; Z. TU; K. HE: "Aggregated Residual Transformations for Deep Neural Networks", PROC. OF C'VPR, 2017
A. G. HOWARD; M. ZHU; B. CHEN; D. KATENICHENKO; W. WANG; T. WEYAND; M. ANDREETTO; H. ADAM: "Mobilenets: Efficient Convolutional Neural Networks for Mobile Vision Applications", ARXIV:1704.04861, 2017
M. SANDLER; A. HOWARD; M. ZHU; A. ZHINOGINOV; L. CHEN: "MobileNetV2: Inverted Residuals and Linear Bottlenecks", ARXIV:1801.04381V3, 2018
Z. QIN; Z. ZHANG; X. CHEN; Y. PENG: "FD-MobileNet: Improved MobileNet with a Fast Downsampling Strategy", ARXIV: 1802.03750, 2018
N. TEN DUKE: "Master's Thesis", 17 June 2017, UNIVERSITEIT LEIDEN OPLEIDING INFORMATICA, article "Convolutional Neural Networks for Regulatory Genomics"
BENTLEY ET AL., NATURE, vol. 456, 2008, pages 53 - 59
LIZARDI ET AL., NAT. GENET., vol. 19, 1998, pages 225 - 232
DUNN, TAMSEN; BERRY, GWENN; EMIG-AGIUS, DOROTHEA; JIANG, YU; IYER, ANITA; UDAR, NITIN; SΑIIMBERG, MICHAEL, PISCES: AN ACCURATE AND VERSATILE SINGLE SAMPLE SOMATIC AND GENNLINE VARIANT CALLER, 2017, pages 595 - 595
T SAUNDERS, CHRISTOPHER; WONG, WENDY; SWAMY, SAJANI; BECQ, JENNIFER; J MURRAY, LISA; CHEETHAM, KEIRA: "Strelka: Accurate somatic small-variant calling from sequenced tumor-nonnal sample pairs", BIOINFORMATICS, vol. 28, 2012, pages 1811 - 7, XP055257165, DOI: doi:10.1093/bioinformatics/bts271
STROMBERG, MICHAEL; ROY, RAJAT; LAJUGIE, JULIEN; JIANG, YU; LI, HAOCHEN; MARGULIES, ELLIOTT, NIRVANA: CLINICAL GRADE VARIANT ANNOTATOR, 2017, pages 596 - 596
A. G. HOWARD; M. ZHU; B. CHEN; D. KALENICHENKO; W. WANG; T. WEYAND; M. ANDREETTO; H. ADAM: "Mobilenets: Efficient Convolutional Neural Networks for Mobile Vision Applications", ARXIV: 1704.04861, 2017
I. J. GOODFELLOW; D. WΗRDE-FARLEY; M. MIRZA; A. COURVILLE; Y. BENGIO: "Deep Learning", 2016, MIT PRESS, article "CONVOLUTIONAL NETWORKS"
"BATCH NORMALIZATION: ACCELERATING DEEP NETWORK TRAINING BY REDUCING INTERNAL COVARIATE SHIFT", ARXIV: 1502.03167, 2015
Attorney, Agent or Firm:
DURDIK, Paul A. et al. (US)
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