CN108959848A - Based on genetic mutation and the matched hereditary disease forecasting system of disease phenotype auto-associating - Google Patents
Based on genetic mutation and the matched hereditary disease forecasting system of disease phenotype auto-associating Download PDFInfo
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Abstract
The present invention relates to one kind based on genetic mutation and the matched hereditary disease forecasting system of disease phenotype auto-associating, including data module, tool model, analysis workflow module, encoding gene variation solution read through model, Noncoding gene solution read through model and network gateway module；Data module is for the encrypted transmission of life group cosmogony data, intelligent recognition and integration configuration；Tool model is module integrated for software tool；Process and parallel operational process are built in analysis workflow module unitization；Encoding gene variation solution read through model is used to filter non-key encoding gene variation and is associated with matching disease phenotype information, and generates clinical interpret and report；Noncoding gene solution read through model generates clinical interpret and reports for retrieving, being associated with and matching Noncoding gene variation and its disease phenotype information；Network gateway module is disposed using virtualization encapsulation and cloud platform, establishes network terminal visualization portal application.
Description
Technical field
Field is excavated and interpreted the present invention relates to accurate medicine big data, is based on genetic mutation more particularly, to one kind
With the matched hereditary disease forecasting system of disease phenotype auto-associating.
Background technique
The hereditary disease of association matching gene mutation and disease phenotype based on life group data especially genomic data
Disease forecasting early warning, the developed countries such as America and Europe have been laid out and have converted in advance in this technical field, and there are also related sides both at home and abroad
To service product.With the present invention it is most like be dimension Kang Jijin Sang Ge research institute of Britain DECIPHER system, it is with heredity
Disease Clinical interpretation is attached most importance to, and the genome mutation for the rare disease of the mankind provides clinical interpretation.DECIPHER incorporates many bases
Because of the critical data of group annotation database, as human genome database Ensembl, Mendelian inheritance disease database OMIM,
Genetic mutation database D GV, bibliographic data base Pubmed, albumen database SwissProt, human phenotype database HPO etc., knot
Fruit provides clinical report, family's report and rare disease symptoms by online genome browser and reports.Details look at bibliography.
Domestic similar service product has the commercial companies such as Hua Da gene to provide gene human interpretation and rare patient's work sieve
It looks into, traditional gene mutation such as approach application SIFT, Polyphen explains software and carries out gene function note, then by artificial
To interpret the relationship of mutant gene and genetic disease.Since the service is commercial product, specific detailed process is unintelligible.
The shortcomings that above-mentioned prior art, is:
(1) data cover is not comprehensive enough.Wherein one most importantly above-mentioned technical method and system only considered coding
Gene is not covered with the data of Noncoding gene.Noncoding gene had been demonstrated related to disease genetic and morbidity in recent years
Property it is very high, using non-coding data become very necessary and urgent in genetic variation analysis reconciliation read procedure.
(2) concrete operations of above-mentioned technology need manual or semi-manual, and analysis result is also required to human interpretation.Above-mentioned technology
There is no the standardized ontology describings based on gene phenotype data during interpretation, thus can not accomplish comprehensive automatic
Change.
(3) result interpret report it is lack of standardization, without standard.Human interpretation does not judge dependent on personal knowledge and experience
Standard, leading to same genetic analysis result, there may be different interpretations.There is no be based on base during interpretation for above-mentioned technology
Because of the standardized ontology describing of phenotypic data, thus it can not accomplish the standardization of description.
(4) result interpretation is relatively limited to research application, not for the specification of clinical application.Due to being human interpretation
Or semi-artificial interpretation and its nonstandardized technique, so being difficult to form the clinical application of standardization.
(5) it is not also difficult to form seamless connection bottom analysis workflow and the online network application system of front end Chinese edition
System.
Bibliography:
DECIPHER:web-based,community resource for clinical interpretation of
rare variants in developmental disorders,Ganesh J.Swaminathan,et al(2012),
Human Molecular Genetics,1:R37–R44.(doi:10.1093/hmg/dds362)。
Summary of the invention
The present invention is to solve the above problem of the prior art, provides one kind and is closed automatically based on genetic mutation with disease phenotype
Join matched hereditary disease forecasting system.
To realize the above goal of the invention, the technical solution adopted is that:
Based on genetic mutation and the matched hereditary disease forecasting system of disease phenotype auto-associating, including data module, tool
Module, analysis workflow module, encoding gene variation solution read through model, Noncoding gene solution read through model and network gateway module；Number
According to module for the encrypted transmission of life group cosmogony data, intelligent recognition and integration configuration；Tool model is for software tool
It is module integrated；Process and parallel operational process are built in analysis workflow module unitization；Encoding gene variation solution read through model is used for
It filters non-key encoding gene and makes a variation and be associated with matching disease phenotype information, and generate clinical interpret and report；Noncoding gene solution
Read through model generates clinical interpret and reports for retrieving, being associated with and matching Noncoding gene variation and its disease phenotype information；Net
Network portal module is disposed using virtualization encapsulation and cloud platform, establishes network terminal visualization portal application.
Preferably, described group of data utilize LEON algorithmic technique to compress according to after the size piecemeal of data, then with SSL
Cipher mode encryption and synchronous transfer；By system intelligent recognition after data transmission and decryption；System is according to intelligent recognition as a result, shape
At data module.
Preferably, tool model is guiding effectively to excavate towards life group data, assesses different groups and learns data
The effect of parser technology, then integrated data analysis tool, forms optimal most suitable algorithmic tool module, realizes matter
Control, assembling, comparison, gene mutation identify these analytic functions.
Preferably, analysis workflow module be directed to life group data module, using SnakeMake, GNUMake,
Tool, standardization combination are formed automate workflow to these technologies of Cronwell or personalized customization forms building blocks chemical industry
Make process, the parallel analysis process run in module excavates the genetic mutation information in acquisition group data；System high-performance
Calculate integrated work allotment software parallel operating analysis process, the parallel full gene that obtains makes a variation information, generate VCF, YML or
The genetic mutation associated documents of the multiple format of PDE.
It preferably, include filtering non-key encoding gene variation, association in encoding gene variation solution read through model operational process
It makes a variation with the variation of matching encoding gene with phenotypic information, multi-mode Analysis on confidence confirmation Disease-causing gene, generate standardization interpretation
Report these steps.
It preferably, include retrieval association matching Noncoding gene variation and table in Noncoding gene solution read through model operational process
Type information, generates to standardize to interpret and reports these steps the variation of multi-mode Analysis on confidence confirmation Disease-causing gene.
Preferably, network gateway module disposes these network technologies using virtualization encapsulation and cloud platform, establishes network end
End visualization portal application；Visualization portal includes webpage, mobile terminal APP, network AP I, SDK these forms, passes through Spring
The bottom data of two parts exploitation, process conciliate read apparatus before these technologies of MVC, AJAX-RS are seamlessly connected；Utilize data-driven
Brand-new visualization technique, establish and meet the visualization interface of personalized application.
Compared with prior art, the beneficial effects of the present invention are:
(1) data cover is comprehensive: the present invention not only handles traditional encoding gene, also covers the number of Noncoding gene
According to, make analysis mining and interpret more comprehensively.Noncoding gene has been demonstrated related to genetic disease that the present invention is covered comprehensively in recent years
Lid coding and Noncoding gene data.
(2) fully automatic integral system, more efficient: the operation for analyzing processing no longer needs manual or semi-manual, analysis
As a result human interpretation is also no longer needed；Standardized process greatly improves the efficiency of analysis mining and interpretation；Personalized determines
Process processed provides the flexibility of analysis mining.
(3) method of multi-mode Analysis on confidence confirmation Disease-causing gene variation, substantially increases the confidence level of result.
(4) result interprets reporting obligations, standardization: automatic interpret depends on HPO and CHPO ontology standard terminology, has
The standard of authority's judgement has stronger readable and higher confidence level；As a result it interprets for scientific research and clinical application
As specification.
(5) system both can be by network gateway on-line analysis, while in view of medical data is to privacy and safety
Consider, it is also localizable to install and use.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of system.
Fig. 2 is the flow diagram that data module integrates source data.
Fig. 3 is the flow diagram of tool model integrated software tool.
Fig. 4 is the schematic diagram for analyzing workflow module and being formed and being run.
Fig. 5 is the flow diagram of encoding gene variation solution read through model.
Fig. 6 is the flow diagram of Noncoding gene solution read through model.
Fig. 7 is the schematic diagram of network gateway module encapsulation deployment and application.
Specific embodiment
The attached figures are only used for illustrative purposes and cannot be understood as limitating the patent；
Below in conjunction with drawings and examples, the present invention is further elaborated.
Embodiment 1
The present invention designs and establishes the analysis mining workflow towards genetic screening and solves read apparatus, shape with annotation
Be associated with matched hereditary disease prediction and warning application system comprehensively at full-automatic based on genetic mutation and disease phenotype, and with can
Depending on changing network gateway seamless connection, used for different types users such as scientific research institutions, hospital and third party inspection centers.
Present system is through the skill of the integration of life group data, Quality Control, configuration, processing, analysis, excavation, interpretation
Art engineering method.As shown in Figure 1, system is divided into data module, tool model, analysis workflow module, encoding gene variation solution
Read through model, Noncoding gene solution read through model and network gateway module.Data module for life group cosmogony data encrypted transmission,
Intelligent recognition and integration configuration；Tool model is module integrated for software tool；Stream is built in analysis workflow module unitization
Journey and parallel operational process；Encoding gene variation solution read through model is used to filter non-key encoding gene variation and is associated with matching disease
Phenotypic information, and generate clinical interpret and report；Noncoding gene solution read through model is for retrieving, being associated with and matching Noncoding gene change
Different and its disease phenotype information, and generate clinical interpret and report；Network gateway module is disposed using virtualization encapsulation and cloud platform
Etc. network technologies, establish the network terminal visualization portal application.
It is the detailed description to modules below.
(1) data module (Fig. 2)
Data module is used for ciphered compressed, parallel transmission, intelligence to the life group cosmogony data such as genome, exon group
Identification and integration configuration.The present invention is parallelly compressed by deblocking, encryption, transmission, identification, configuration are synchronous with calculating, mentions significantly
The efficiency that high global analysis is excavated.It is characterized in that group learn data according to after the size piecemeal of data utilize LEON algorithmic technique pressure
Then contracting encrypts simultaneously synchronous transfer in a manner of SSL encryption；By system intelligent recognition after data transmission and decryption；System is according to intelligence
Energy recognition result, forms data module；The formation of data module is synchronous with subsequent calculating.
(2) tool model (Fig. 3)
Tool model is used to analyze the technology evaluation and integration configuration of software tool.It is characterized in that with towards life group number
It is guiding according to effective excavate, assesses the effect that different groups learns the parser technology of data, then integrated data analysis tool,
Including FASTQC, PRINSEQ, the software tool packs such as BWA, SamTools, GATK form optimal most suitable algorithmic tool mould
Block realizes the analytic functions such as Quality Control, assembling, comparison, gene mutation identification.
(3) workflow module (Fig. 4) is analyzed
Analysis workflow module builds process and parallel operational process for unitization.It is characterized in that for genome, outer
The life group data modules such as aobvious subgroup, using technologies such as SnakeMake, GNU Make, Cronwell by tool, standardization group
Conjunction forms automate workflow or personalized customization forms unitization workflow, runs the analysis process in module parallel,
Excavate the genetic mutation information in acquisition group data；System calculates integrated work tune with the high performance such as LSF, PBS, HTConder
It is parallel to obtain full gene variation information with software parallel operating analysis process, generate the multiple formats such as VCF, YML or PDE
Genetic mutation associated documents.
(4) encoding gene variation solution read through model (Fig. 5)
Encoding gene variation solution read through model, which is used to filter non-key encoding gene variation and is associated with, matches its disease phenotype letter
Breath, and generate clinical interpret and report.It is characterized in that containing the non-key encoding gene variation of filtering, association and matching encoding gene
Variation and phenotypic information, multi-mode Analysis on confidence confirmation Disease-causing gene variation, generate standardization interpret report and etc..
Non-key encoding gene variation is filtered, this step is all kinds of parameters in the genetic mutation file based on different-format
(including variation frequency numerical value, the dominant and stealth characteristics of Mendelian inheritance, monogenic inheritance and multiple-factor inheritance model etc.), fortune
With command operations such as script process software and Grep, Pipe, non-key, nonpathogenic variant sites information is filtered out, to protect
Crucial variant sites information relevant to disease, such as nonsynonymous mutation (nSNV), copy number variation (CNV) are stayed, is retained
Information is stored in the formatted files such as new VCF.
Association and the variation of matching encoding gene and phenotypic information, phenotypic data library and operation of this step with encoding gene
Phenotype associated tool, including Exomiser, Poly-Gen, Extasy etc. are newest to be based on human phenotype ontology data (Human
Phenotype Ontology, HPO) tool, establish the Auto-matching of disease phenotype and encoding gene, pass through weighting isotype
Correlation model score is obtained, encoding gene key accidental data information is obtained, while reaching the automation integrated degree of operation.
Multi-mode Analysis on confidence confirms Disease-causing gene variation, this step passes through score value weighting pattern, content overlap scheme
The methods of obtain comprehensive association confidence value, then with the sequence of multiple scoring values obtain to different genetic diseases most it is related most
The Disease-causing gene variation set matched, and show the relating attribute and degree of each encoding gene variation and disease phenotype.
Generate standardization and interpret report, this step by matching human diseases ontology data (HPO and CHPO) it is controllable,
Standardization, the ontology vocabulary and term that reading can be calculated, the description and its classification of the disease phenotype of standard code gene association,
Report is interpreted in the standardization of foundation group data notes result, improves the accuracy and readability of interpretation.It interprets and contains in report
The associated details of matching of the molecule and disease phenotype of genetic mutation, can assist the prediction of human genetic diseases clinically pre-
Alert, risk assessment and Index for diagnosis etc..
(5) Noncoding gene solution read through model (Fig. 6)
The retrieval of Noncoding gene solution read through model, association and the variation of matching Noncoding gene and its disease phenotype information, and it is raw
Report is interpreted at clinic.It is characterized in that containing, retrieval association matching Noncoding gene variation and phenotypic information, multi-mode is credible
Interpretation report that degree is analyzed to identify Disease-causing gene variation, generation standardizes and etc..
Retrieval association matching Noncoding gene variation and phenotypic information, it includes newest non-coding RNA table that this step, which utilizes,
Type linked database (such as ncrPheDB, LncDisease) information and its parser carry out retrieval matching, obtain non-coding
Key gene and associated disease phenotype information.Noncoding gene has been demonstrated that heredity and generation to disease are related in recent years
Property is very high, and present system compensates for the associated missing of Noncoding gene data and disease phenotype in conventional method.
Multi-mode Analysis on confidence confirms Disease-causing gene variation, this step passes through score value weighting pattern, content overlap scheme
The methods of obtain comprehensive association confidence value, then with the sequence of multiple scoring values obtain to different genetic diseases most it is related most
The Disease-causing gene variation set matched, and obtain the relating attribute and degree of each Noncoding gene variation and disease phenotype
Generate standardization and interpret report, this step by matching human diseases ontology data (HPO and CHPO) it is controllable,
Standardization, the ontology vocabulary and term that can calculate reading standardize the description and its class of the associated disease phenotype of Noncoding gene
Not, report is interpreted in the standardization of foundation group data notes result, improves the accuracy and readability of interpretation.It interprets and contains in report
There are the associated details of matching of the molecule and disease phenotype of genetic mutation, the prediction of auxiliary human genetic diseases clinically is pre-
Alert, risk assessment and Index for diagnosis etc..
(6) network gateway module (Fig. 7)
Network gateway module establishes network terminal visualization door using the network technologies such as virtualization encapsulation and cloud platform deployment
Family application.It is characterized in that establishing network terminal visualization portal using the network technologies such as virtualization encapsulation and cloud platform deployment and answering
With；Visualizing portal includes the forms such as webpage, mobile terminal APP, network AP I, SDK, passes through the skills such as Spring MVC, AJAX-RS
The bottom data of two parts exploitation, process conciliate read apparatus before art is seamlessly connected；Using the brand-new visualization technique of data-driven,
Such as D3js, BootStrap, Json technology establishes the visualization interface for meeting personalized application.
The group data point of the finally formed standardization high efficient and reliable towards the application of genetic disease clinic diagnosis of the present invention
Analysis, which is excavated, interprets application system, can both be accessed and be used by network, can also localized encapsulation and install and use, services stages doctor
Medical institutions and the research units such as institute, third party inspection center provide high efficient and reliable personalized medicine and research application, including strong
Kang Guanli, assisting in diagnosis and treatment, drug use and exploitation, disease-susceptible humans detection, disease forecasting early warning, risk assessment, Index for diagnosis, doctor
Treat the application services such as insurance.
Inventive point of the invention is the following:
(1) genetic disease table is established using phenotypic data library and tool, including Exomiser, Poly-Gen, Extasy etc.
The Auto-matching of type and genetic mutation establishes full automatic mode, is no longer original traditional manual or semi-manual interpretation, significantly
It improves analysis and interprets efficiency.
It is (2) innovative that being associated with for non-coding inhereditary material and disease is matched using ncrPheDB genopathy database,
The data for covering encoding gene and Noncoding gene simultaneously, establish comprehensive match pattern, are points of hereditary disease prediction and warning
Analysis and interpretation are more comprehensively more credible.
(3) new method of multi-mode Analysis on confidence confirmation Disease-causing gene variation is created, substantially increase result can
Reliability.
(4) emphasis joined the result based on gene phenotype data normalization, the ontology describing that standardizes and interpret, and eliminate the reliance on
In personal knowledge and experience, the accuracy rate for improving analysis result conciliates the readability for announcement of reading the newspaper.
(5) network terminal portal, seamless connection front end, middleware and bottom workflow, towards scientific research and clinic are provided
Network application is provided, is used for commercial users such as scientific research institutions, hospital and third party inspection centers, is no longer limited to scientific research and answers
With expanding application range significantly.
Obviously, the above embodiment of the present invention be only to clearly illustrate example of the present invention, and not be pair
The restriction of embodiments of the present invention.For those of ordinary skill in the art, may be used also on the basis of the above description
To make other variations or changes in different ways.There is no necessity and possibility to exhaust all the enbodiments.It is all this
Made any modifications, equivalent replacements, and improvements etc., should be included in the claims in the present invention within the spirit and principle of invention
Protection scope within.
Claims (7)
1. based on genetic mutation and the matched hereditary disease forecasting system of disease phenotype auto-associating, it is characterised in that: including data
Module, tool model, analysis workflow module, encoding gene variation solution read through model, Noncoding gene solution read through model and web portal
Family module；Data module is for the encrypted transmission of life group cosmogony data, intelligent recognition and integration configuration；Tool model is for soft
Part tool it is module integrated；Process and parallel operational process are built in analysis workflow module unitization；Encoding gene variation is interpreted
Module makes a variation and is associated with matching disease phenotype information for filtering non-key encoding gene, and generates clinical interpretation report；Non- volume
Code gene solution read through model generates clinical solution for retrieving, being associated with and matching Noncoding gene variation and its disease phenotype information
It reads the newspaper announcement；Network gateway module is disposed using virtualization encapsulation and cloud platform, establishes network terminal visualization portal application.
2. according to claim 1 be based on genetic mutation and the matched hereditary disease forecasting system of disease phenotype auto-associating,
It is characterized by: described group of data utilize LEON algorithmic technique to compress according to after the size piecemeal of data, then with SSL encryption
Mode encrypts and synchronous transfer；By system intelligent recognition after data transmission and decryption；System is according to intelligent recognition as a result, forming number
According to module.
3. according to claim 1 be based on genetic mutation and the matched hereditary disease forecasting system of disease phenotype auto-associating,
It is characterized by: tool model is guiding effectively to excavate towards life group data, the analysis that different groups learns data is assessed
The effect of algorithmic technique, then integrated data analysis tool form optimal most suitable algorithmic tool module, realize Quality Control,
Assembling, comparison, gene mutation identify these analytic functions.
4. according to claim 1 be based on genetic mutation and the matched hereditary disease forecasting system of disease phenotype auto-associating,
It is characterized by: analysis workflow module is directed to life group data module, SnakeMake, GNU Make, Cronwell are utilized
Tool, standardization combination are formed automate workflow to these technologies or personalized customization forms unitization workflow, and
Analysis process in row operation module, excavates the genetic mutation information in acquisition group data；System is integrated with high-performance calculation
Work allotment software parallel operating analysis process, it is parallel to obtain full gene variation information, generate a variety of of VCF, YML or PDE
The genetic mutation associated documents of format.
5. according to claim 1 be based on genetic mutation and the matched hereditary disease forecasting system of disease phenotype auto-associating,
It is characterized by: include in encoding gene variation solution read through model operational process filter the variation of non-key encoding gene, association and
Report is interpreted with encoding gene variation and phenotypic information, the variation of multi-mode Analysis on confidence confirmation Disease-causing gene, generation standardization
These steps.
6. according to claim 1 be based on genetic mutation and the matched hereditary disease forecasting system of disease phenotype auto-associating,
It is characterized by: including retrieval association matching Noncoding gene variation and phenotype letter in Noncoding gene solution read through model operational process
Breath, generates to standardize to interpret and reports these steps the variation of multi-mode Analysis on confidence confirmation Disease-causing gene.
7. according to claim 1 be based on genetic mutation and the matched hereditary disease forecasting system of disease phenotype auto-associating,
It is characterized by: network gateway module disposes these network technologies using virtualization encapsulation and cloud platform, establishing the network terminal can
Depending on changing portal application；Visualization portal includes webpage, mobile terminal APP, network AP I, SDK these forms, by Spring MVC,
The bottom data of two parts exploitation, process conciliate read apparatus before these technologies of AJAX-RS are seamlessly connected；Utilize the fine of data-driven
New visualization technique establishes the visualization interface for meeting personalized application.
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