MX2017004978A - Modelos de formacion de fases de haplotipo. - Google Patents

Modelos de formacion de fases de haplotipo.

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Publication number
MX2017004978A
MX2017004978A MX2017004978A MX2017004978A MX2017004978A MX 2017004978 A MX2017004978 A MX 2017004978A MX 2017004978 A MX2017004978 A MX 2017004978A MX 2017004978 A MX2017004978 A MX 2017004978A MX 2017004978 A MX2017004978 A MX 2017004978A
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MX
Mexico
Prior art keywords
models
haplotype
phase
discarded
model
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MX2017004978A
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English (en)
Inventor
G Chahine Kenneth
Ann Ball Catherine
J Barber Mathew
D Noto Keith
Wang Yong
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Ancestry Com Dna Llc
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Publication of MX2017004978A publication Critical patent/MX2017004978A/es

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B5/00—ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
    • G16B5/20—Probabilistic models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/20—Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/20—Supervised data analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/30—Unsupervised data analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B5/00—ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Medical Informatics (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Biotechnology (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • Software Systems (AREA)
  • Databases & Information Systems (AREA)
  • Molecular Biology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Epidemiology (AREA)
  • Public Health (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Bioethics (AREA)
  • General Physics & Mathematics (AREA)
  • Probability & Statistics with Applications (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Genetics & Genomics (AREA)
  • Analytical Chemistry (AREA)
  • Physiology (AREA)
  • Chemical & Material Sciences (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Physics (AREA)
  • General Engineering & Computer Science (AREA)
  • Operations Research (AREA)
  • Algebra (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

Los modelos Markov en grupo de haplotipo novedosos se usan para muestras genómicas de fase. Después de que se construyen los modelos, estos rápidamente y exactamente hacen fases de nuevas muestras sin requerir que las muestras nuevas se usen para reconstruir los modelos. Los modelos ajustan las probabilidades de transición de manera que la probabilidad para una aparición de cualquier alelo dentro de cualquier haplotipo es un número que no es cero. Adicionalmente, los pares de haplotipos más improbables se descartan de cada modelo en cada nivel hasta que de la masa de probabilidad en cada nivel se descarta. Los modelos también se construyen de tal manera que las ventanas de contribución de SNPs parcialmente se traslapan de manera que las decisiones de separación de fases cerca de uno de los bordes de extremo de cualquier modelo no son determinantes importantes de la fase. Adicionalmente, los modelos se configuran de tal manera que dos o más nodos pueden fusionarse durante el procedimiento de construcción/actualización para consolidar grupos de haplotipo que tienen distribuciones similares.
MX2017004978A 2014-10-17 2015-10-19 Modelos de formacion de fases de haplotipo. MX2017004978A (es)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201462065557P 2014-10-17 2014-10-17
US201462065726P 2014-10-19 2014-10-19
PCT/US2015/056164 WO2016061568A1 (en) 2014-10-17 2015-10-19 Haplotype phasing models

Publications (1)

Publication Number Publication Date
MX2017004978A true MX2017004978A (es) 2017-09-13

Family

ID=55747474

Family Applications (2)

Application Number Title Priority Date Filing Date
MX2017004980A MX2017004980A (es) 2014-10-17 2015-10-19 Genomas humanos ancestrales.
MX2017004978A MX2017004978A (es) 2014-10-17 2015-10-19 Modelos de formacion de fases de haplotipo.

Family Applications Before (1)

Application Number Title Priority Date Filing Date
MX2017004980A MX2017004980A (es) 2014-10-17 2015-10-19 Genomas humanos ancestrales.

Country Status (7)

Country Link
US (4) US10679729B2 (es)
EP (2) EP3207482B1 (es)
AU (3) AU2015331621B2 (es)
CA (2) CA2964905C (es)
MX (2) MX2017004980A (es)
NZ (2) NZ731884A (es)
WO (2) WO2016061570A1 (es)

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US10437858B2 (en) 2011-11-23 2019-10-08 23Andme, Inc. Database and data processing system for use with a network-based personal genetics services platform
US10025877B2 (en) 2012-06-06 2018-07-17 23Andme, Inc. Determining family connections of individuals in a database
US9213944B1 (en) 2012-11-08 2015-12-15 23Andme, Inc. Trio-based phasing using a dynamic Bayesian network
US9213947B1 (en) 2012-11-08 2015-12-15 23Andme, Inc. Scalable pipeline for local ancestry inference
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CA3079190A1 (en) * 2017-10-17 2019-04-25 President And Fellows Of Harvard College Methods and systems for detection of somatic structural variants
EP3776556A4 (en) 2018-04-05 2021-12-15 Ancestry.com DNA, LLC COMMUNITY ASSIGNMENTS IN THE IDENTITY THROUGH ANALINE NETWORKS AND GENETIC VARIANTS
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Also Published As

Publication number Publication date
MX2017004980A (es) 2017-12-07
WO2016061568A1 (en) 2016-04-21
US20170277827A1 (en) 2017-09-28
AU2015331621B2 (en) 2021-02-25
US10679729B2 (en) 2020-06-09
EP3207483A1 (en) 2017-08-23
AU2015331621A1 (en) 2017-06-08
AU2015331619A1 (en) 2017-06-08
AU2021201500B2 (en) 2022-07-14
CA2964902A1 (en) 2016-04-21
AU2015331619B2 (en) 2020-12-10
EP3207482B1 (en) 2023-04-05
CA2964905C (en) 2023-03-21
EP3207482A1 (en) 2017-08-23
US20170262577A1 (en) 2017-09-14
US10504611B2 (en) 2019-12-10
AU2021201500A1 (en) 2021-03-25
CA2964905A1 (en) 2016-04-21
CA2964902C (en) 2023-03-21
WO2016061570A1 (en) 2016-04-21
EP3207483A4 (en) 2018-04-04
EP3207482A4 (en) 2018-04-04
NZ731820A (en) 2017-05-26
US20200303035A1 (en) 2020-09-24
US20200098445A1 (en) 2020-03-26
NZ731884A (en) 2017-05-26

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