CN110706750B - Dynamic interactive microbiology online analysis cloud platform and generation method thereof - Google Patents
Dynamic interactive microbiology online analysis cloud platform and generation method thereof Download PDFInfo
- Publication number
- CN110706750B CN110706750B CN201911032717.3A CN201911032717A CN110706750B CN 110706750 B CN110706750 B CN 110706750B CN 201911032717 A CN201911032717 A CN 201911032717A CN 110706750 B CN110706750 B CN 110706750B
- Authority
- CN
- China
- Prior art keywords
- analysis
- user
- data
- providing
- cloud platform
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- 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
- G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Bioethics (AREA)
- Biophysics (AREA)
- Databases & Information Systems (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Biotechnology (AREA)
- Evolutionary Biology (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Theoretical Computer Science (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a dynamic interactive microbiology online analysis cloud platform and a generation method thereof, wherein the cloud platform comprises: the user login management module is used for providing user registration account information, acquiring login information, determining the authority of a login user according to the login information, and providing an interface for the login user to perform biological information analysis on 16S, ITS and 18S and microorganism metagenome sequencing by using a cloud platform; the data module is used for providing data uploading operation for a user and acquiring data uploaded by the user; the project analysis module is used for selecting the data uploaded by the user, constructing a sample relation single-grouping scheme and a sample relation single-comparison scheme, and performing new flow analysis operation on the selected sample relation single and corresponding parameters; and the dynamic interaction module is used for providing a user to realize dynamic interaction data analysis and presenting an analysis result in the form of an interactive user interface.
Description
Technical Field
The invention relates to the technical field of biological information analysis, in particular to a dynamic interactive microbiology online analysis cloud platform and a generation method thereof.
Background
With the progress and development of sequencing technology, the total amount of data generated by high-throughput sequencing technology reaches EB level, so that how to mine valuable core information from mass data by using a biological information technology and display the data so as to facilitate real-time analysis and key report data mining becomes a core problem for scientific researchers in the field. In the aspect of biological information analysis platforms, the currently well-known domestic and foreign platforms include: foreign Galaxy biological information analysis platform, and Huada gene BGI online platform. However, although these platforms are powerful and suitable for professional users of biometric information, they are difficult to use by users without any basis for biometric information.
Moreover, most high-throughput sequencing service companies in the market only provide traditional static problem reports, which are time-consuming and labor-consuming in data mining, are not favorable for scientific research personnel in the field to analyze and research data, and if the user offline data needs to modify parameters, the user needs to repeatedly communicate, discuss and modify the offline data through company technology and biological information engineers and re-analyze the offline data, so that the user needs to pay supplementary analysis cost, and the process wastes time and economic cost.
The microorganism comprises virus, bacteria, fungi, algae and the like, and the microbial diversity sequencing is a research method for detecting the characteristic sequences of the microbial species such as 16S, 18S, ITS and the like amplified by PCR by using a high-throughput sequencing technology. Microbiology is one of the major breakthroughs in the field of life science and biotechnology research after genomics, and has wide application prospects in the aspects of medical treatment, health, agriculture, ecological environment and industrial manufacturing. With the introduction of the human microbiome program, bioinformatic analysis of microbiology also faces the above problems.
However, at present, there is no bioinformatics online analysis platform which is simple in operation, high in safety and rich in personalized analysis, so that if a bioinformatics analysis platform capable of dynamically mining data and analyzing data results in real time can be provided, great industrial demands will be met.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention aims to provide a dynamic interactive microbiology online analysis cloud platform and a generation method thereof, so that dynamic data mining and real-time analysis of biological information are automatically realized, and scientific researchers without a biological information base can independently select parameters, generate an analysis result by one key and completely dynamically graph according to needs, thereby facilitating real-time data mining and analysis.
In order to achieve the above object, the present invention provides a dynamic interactive microbiology online analysis cloud platform, comprising:
the user login management module is used for providing user registration account information, acquiring login information, determining the authority of a login user according to the login information, and providing an interface for the login user to perform biological information analysis on 16S, ITS and 18S and microorganism metagenome sequencing by using a cloud platform;
the data module is used for providing data uploading operation for a user and acquiring data uploaded by the user;
the project analysis module is used for selecting the data uploaded by the user, constructing a sample relation single-grouping scheme and a sample relation single-comparison scheme, and performing new flow analysis operation on the selected sample relation single and corresponding parameters;
and the dynamic interaction module is used for providing a user to realize dynamic interaction data analysis and presenting an analysis result in the form of an interactive user interface.
Preferably, the user login management module includes:
the data sharing unit is used for sharing, discussing and handing over the data result with others by the user;
the task viewing unit is used for providing a user to link to the dynamic interaction module for analyzing content and viewing parameters and acquiring an analysis result;
the user authority management unit is used for providing process analysis content of corresponding authority of the cloud platform purchased by the user and providing different operation authorities of the user according to the recharging operation of the user;
and the cloud platform information providing unit is used for providing the relevant information of the cloud platform.
Preferably, the user login management module provides for the user to download all analysis data and personalized reports in bulk.
Preferably, the data module provides a user with a choice of data source, data type and data format of the data to be uploaded, uploads the selected data, and displays the data uploading state in real time during the uploading process.
Preferably, the data source is any one of bacteria/archaea/fungi/algae, 16S/ITS/18S, V3-V4/V5-V6, from which single or double-ended sequences of the barcode linker have been removed by different sequencing platforms, in the format of any one of the suffixes fastq/. fq/. fq.gz/. fastq.gz/. fastq.bz2/. fq.bz2.
Preferably, the item analysis module includes:
the data selection and naming module is used for providing a user to select the data uploaded by the user, and constructing and naming a data set according to the selected data;
a grouping/comparison scheme construction module for constructing a sample relationship single-grouping scheme and a sample relationship single-comparison scheme for the selected data set;
and the analysis module is used for carrying out data analysis on the selected sample relation list and the corresponding parameters.
Preferably, the analysis module performs conventional microbial diversity analysis including, but not limited to, group analysis, OTU clustering, statistics, analysis; species composition analysis, Alpha diversity analysis, Beta diversity analysis, functional analysis, environmental factor analysis and personality report generation.
Preferably, the dynamic interaction module includes:
the newly added task module is used for newly adding groups by acquiring a grouping scheme, newly adding an OTU table by OTU screening, and starting new task interaction analysis by the newly added groups and the newly added OTU table;
and the data mining module is used for selecting parameter switching through one key, and eliminating unsatisfactory clustering, so that data is analyzed at multiple angles, and expected experimental results are searched.
Preferably, the one-click selection parameter switching includes, but is not limited to, switching the OTU/phylum species classification level, switching sample/group, switching the analysis model, switching the threshold value, and the like.
In order to achieve the above object, the present invention further provides a method for generating a dynamic interactive microbiology online analysis cloud platform, comprising the following steps:
step S1, providing user registration account information, obtaining login information, determining the authority of the login user according to the login information, providing an interface for the login user to perform biological information analysis aiming at 16S, ITS and 18S and microorganism metagenome sequencing by using a cloud platform, and realizing a user login management module;
step S2, providing data uploading operation for users, and acquiring data uploaded by users;
step S3, selecting the data uploaded by the user, constructing a sample relation list-grouping scheme and a sample relation list-comparison scheme, and performing new process analysis operation on the selected sample relation list and corresponding parameters to realize a project analysis module
And step S4, providing a user to realize dynamic interactive data analysis.
Compared with the prior art, the dynamic interactive microbiology online analysis cloud platform and the generation method thereof have the advantages that through the cloud service platform packaging type design, the complex experiment and analysis processes in the background are presented to the terminal user in a simple and interactive mode, so that the complex biological information analysis can be completed by the user with the non-biological information background through the simple operation interface of the platform.
Drawings
FIG. 1 is a system architecture diagram of a dynamic interactive microbiology online analysis cloud platform according to the present invention;
FIG. 2 is a detailed structure diagram of a user login management module according to an embodiment of the present invention;
FIG. 3 is a detailed block diagram of a project analysis module according to an embodiment of the present invention;
FIG. 4a is a diagram illustrating a data selection and naming module in accordance with an embodiment of the present invention;
FIGS. 4b and 4c are schematic diagrams of a grouping/comparing scheme building block in an embodiment of the present invention;
FIG. 4d is a schematic diagram of an analysis module in accordance with an embodiment of the present invention;
FIG. 5 is a detailed structure diagram of a dynamic interaction module according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a data mining module in an embodiment of the present invention;
FIG. 7 is a flowchart illustrating the steps of a method for generating a dynamic interactive microbiology online analysis cloud platform according to the present invention;
fig. 8 is a diagram of an online analysis process of a cloud platform according to an embodiment of the present invention.
Detailed Description
Other advantages and capabilities of the present invention will be readily apparent to those skilled in the art from the present disclosure by describing the embodiments of the present invention with specific embodiments thereof in conjunction with the accompanying drawings. The invention is capable of other and different embodiments and its several details are capable of modification in various other respects, all without departing from the spirit and scope of the present invention.
FIG. 1 is a system structure diagram of a dynamic interactive microbiology online analysis cloud platform according to the present invention. As shown in fig. 1, the dynamic interactive microbiology online analysis cloud platform of the present invention comprises:
the user login management module 10 is configured to provide account information for user registration, obtain login information, determine the authority of a login user according to the login information, provide an interface for the login user to perform biological information analysis on 16S, ITS, 18S and microbial metagenome sequencing by using a cloud platform, and present an analysis result to the login user in an interactive user interface manner. Specifically, the cloud platform provides a registered account interface, the user inputs a registered account and a password, the user logs in by using the registered account and the registered password after the user successfully logs in, the user can log in according to the registered account and the registered password, the cloud platform is used for carrying out biological information analysis on 16S, ITS, 18S and microorganism metagenome sequencing after the user successfully logs in, analysis results are presented to the user in an interactive user interface mode, and the user login management module 10 can also provide the user with batch download of all analysis data and personalized reports.
Specifically, as shown in fig. 2, the user login management module 10 further includes
A data sharing unit 101, configured to provide a user to share, discuss, handover, and the like the data result with another person;
and the task viewing unit 102 is used for providing a user link to the dynamic interaction module for viewing analysis content, parameters and the like, and downloading an analysis result.
And the user right management unit 103 is used for providing process analysis content of corresponding rights of the cloud platform purchased by the user, and providing different operation rights of the user according to the recharging operation of the user. In the specific embodiment of the invention, the users are divided into common users and member users, the recharging operation includes but is not limited to account recharging, member purchasing, storage purchasing, recharging record and other operations, for the common users and the member users, both the common users and the member users can purchase the process analysis content of the corresponding authority of the cloud platform by recharging the account with the Ordoku, the account recharging can provide the users to select the payment modes of WeChat or Paibao and the like, the recharging amount is selectively recharged and paid, and invoices are issued according to the user requirements. The membership purchases, rights and interests such as larger storage space, capacity amplification and more cost-effective single sample analysis can be obtained, the storage purchase can amplify the storage space by purchasing storage after the user charges, and the uploaded data volume is more convenient to analyze when being too large.
A cloud platform information providing unit 104, configured to provide relevant information of the cloud platform. In the embodiment of the present invention, the cloud platform information providing unit 104 provides links of other units, so that a user can obtain unit links such as characteristics, technical parameters, example result display, operation cases, and reference documents of the cloud platform, and the user can view function display and analysis operations of the cloud platform, thereby facilitating the user to better know the cloud platform and perform personalized demand analysis operations after logging in the cloud platform.
And the data module 20 is used for providing data uploading operation for a user, and the function can be used for carrying out deep experiment result mining on the high-throughput sequencing data of the user. In the embodiment of the invention, the user is provided with a choice of the data source, the data type and the data format of the data to be uploaded, the selected data is uploaded, and the data uploading state can be displayed in real time in the uploading process.
Preferably, the data source may be any one of single-ended or double-ended sequences from which the barcode linker has been removed by different sequencing platforms, the data type may be any one of bacteria/archaea/fungi/algae, 16S/ITS/18S, V3-V4/V5-V6, and the data format may be any one of the suffixes: fastq/. fq/. fq.gz/. fastq.gz/. fastq.bz2/. fq.bz2.
And the project analysis module 30 is configured to select data uploaded by a user, construct a sample relation single-grouping scheme and a sample relation single-comparison scheme, and perform a new process analysis operation on the selected sample relation single and corresponding parameters.
Specifically, as shown in fig. 3, the item analysis module 30 includes:
and the data selecting and naming module 301 is used for providing the user to select the data uploaded by the user, and constructing and naming a data set according to the selected data. Specifically, as shown in fig. 4a, the data selection and naming module 301 is specifically configured to: 1. selecting a data type, item, where an item refers to a name of a folder to which a user uploads sequencing data (e.g., demo (25), which indicates that there are 25 samples of sequencing data in the folder/item, and the folder may be named by the user); 2, selecting all samples to be analyzed (because 1 project can be analyzed in batch or 2 projects are analyzed together, so that the samples are uploaded completely, the samples to be analyzed at this time need to be selected, and the selection of the sample name is to select the corresponding sequencing data); 3. data confirmation is carried out; 4. modifying the sample experiment name (name at the time of sequencing) to be the analysis name (i.e. the name used in the chart); 5. naming the data set name (i.e., naming the user-selected sample as a new data set, and therefore potentially multiple items, or a portion of 1 item); 6. data sample submission is performed.
A grouping/comparison scheme construction module 302 for constructing a sample relationship single-grouping scheme and a sample relationship single-comparison scheme for the selected data set.
Specifically, as shown in fig. 4b, the grouping/comparison scheme building module 302 specifically processes the following steps of building a sample relationship single-grouping scheme: 1. selecting a data set; 2. naming a sample relationship sheet; 3. naming a first group name; 4. selecting a sample of the packet; 5. completing sample selection; 6. clicking an adding group and setting other groups; 7. and after all grouping settings are completed, clicking to complete grouping.
As shown in fig. 4c, the grouping/comparison scheme construction module 302 constructs a sample relational single-comparison scheme as follows, selecting a single sample for comparison, selecting two-to-two inter-group comparisons, and selecting a multi-group comparison; and clicking to submit, and generating a sample relation list.
And the analysis module 303 is configured to perform data analysis on the selected sample relation list and the corresponding parameters. In particular embodiments of the invention, routine microbial diversity analysis may be performed, including but not limited to, group analysis, OTU clustering, statistics, analysis; species composition analysis, Alpha diversity analysis, Beta diversity analysis, functional analysis, environmental factor analysis, personality report generation and the like.
As shown in fig. 4d, the specific process of the analysis module 303 is as follows: 1. selecting a sample relation sheet; 2. filling in parameters (e.g., a database); 3. naming a process name; 4. starting to analyze clicking; 5. and popping up an information confirmation box, clicking to submit and analyze after the information is confirmed to be correct, and performing online data analysis.
Preferably, the item analysis module 30 provides an analysis result, and in the item analysis module 30, the analysis result can be clicked to enter the dynamic interaction module 40, and the item analysis module 30 can also provide operations of viewing process parameters, editing and modifying details based on the existing process, and resubmitting.
And the dynamic interaction module 40 is used for providing a user to realize dynamic interaction data analysis, including but not limited to new task operation, data mining operation and graph beautifying operation.
In particular, as shown in fig. 5, the dynamic interaction module 40 specifically includes
The newly added task module 401 performs newly added grouping by acquiring the grouping scheme, performs newly added OTU table screening by OTU, and starts new task interaction analysis by the newly added grouping and the newly added OTU table. Specifically, the user can click the grouping scheme to perform new grouping, click OTU screening to perform new OTU table, and start new task interaction analysis through the new grouping and the new OTU table.
The newly added task module 401 re-analyzes the OTU data obtained based on the process analysis according to the newly added packet and the OTU table. The newly added grouping operation can carry out one-key analysis processing on species pollution, outlier samples, modified sample names and the like; and adding an OTU table, and aiming at target groups, specifying and filtering OTUs or species, leveling, removing pollution and interference, carrying out stricter quality control and paying attention to high-abundance species. Meanwhile, the re-analysis can also add new environmental factors or metabolite data for analysis, so that compared with the traditional process that a user relies on a high-throughput sequencing company for analysis, the time consumption is shorter, and the experimental results are analyzed on the sample and data level more comprehensively.
The data mining module 402 selects parameter switching by one key, including but not limited to switching species classification levels such as OTU/phylum, switching sample/group, switching analysis models, switching thresholds, etc., to eliminate undesirable clustering, so that data is analyzed from multiple angles, and expected results of experiments are found, as shown in fig. 6.
The method comprises the following steps that corresponding parameter switching is clicked, sample/group can be switched in a one-click mode, when the sample size is large, group is convenient for fast searching for the rule of the component, and sample is convenient for paying attention to details in a group; the grouping display is convenient to select when the repeatability in the group is not good; by clicking on parameter switching, analysis charts such as a species stack chart, a species heat map, an Alpha diversity column chart, a dilution curve and a functional heat map can be generated in one key mode.
Wherein, corresponding parameter switching is clicked, models can be switched in one key mode, including but not limited to variance analysis such as chi-square distribution test, Welch's t test, Wilcoxon rank sum test, KW rank sum test, Lefse analysis and the like; alpha diversity indices such as Sobs, ACE, Shannon, Goods's coverage, Simpson, and the like; dimension reduction analysis such as PCoA and NMDS; species evolutionary distance analysis such as Bray, Jaccard, (un) weighted unifrac and the like; anosim, Adonis, etc. component tests; and analyzing the association of CCA, RDA and other environmental factors.
The method comprises the steps of clicking parameter switching, threshold switching and one-click personalized screening of data, wherein the data comprise but are not limited to Lefse analysis, custom species classification, the number and types of custom function heatmaps, custom environment factor types, custom heatmaps and network map correlation coefficient thresholds, LDA thresholds, difference analysis P values and Q values.
A graphics beautification module 403 for providing richer parameters covered by the cloud platform, one-click parameter adjustment and beautification graphics, including but not limited to color scheme switching, color modification, transparency adjustment, shape switching, font size adjustment, font type selection, caption modification, graphic borders, scales, auxiliary lines/circles, color schemes, bar graph error bars, heat map type switching, and the like.
Fig. 7 is a flowchart illustrating steps of a method for generating a dynamic interactive microbiology online analysis cloud platform according to the present invention, and fig. 8 is a diagram illustrating an online analysis process of a cloud platform according to an embodiment of the present invention. As shown in fig. 7 and 8, the method for generating a dynamic interactive microbiology online analysis cloud platform according to the present invention comprises the following steps:
and step S1, providing user registration account information, obtaining login information, determining the authority of the login user according to the login information, providing an interface for the login user to perform biological information analysis aiming at 16S, ITS and 18S and microorganism metagenome sequencing by using a cloud platform, and presenting an analysis result to the login user in an interactive user interface mode to realize a user login management module. Specifically, the cloud platform provides a registered account interface, a registered account and a password are input by a user, the user can log in by using the registered account and the registered password after the user is successfully registered, the user can log in according to the registered account and the registered password, biological information analysis is performed on 16S, ITS, 18S and microorganism metagenome sequencing by using the cloud platform after the user successfully logs in, analysis results are presented to the user in an interactive user interface mode, and the user login management module can provide the user with batch download of all analysis data and personalized reports.
And step S2, providing a user data uploading operation so that deep experiment result mining can be carried out on the user high-throughput sequencing data. In the embodiment of the invention, the user is provided with a choice of the data source, the data type and the data format of the data to be uploaded, the selected data is uploaded, and the data uploading state can be displayed in real time in the uploading process.
Preferably, the data source may be any one of single-ended or double-ended sequences from which the barcode linker has been removed by different sequencing platforms, the data type may be any one of bacteria/archaea/fungi/algae, 16S/ITS/18S, V3-V4/V5-V6, and the data format may be any one of the suffixes: fastq/. fq/. fq.gz/. fastq.gz/. fastq.bz2/. fq.bz2.
And step S3, selecting the data uploaded by the user, constructing a sample relation list-grouping scheme and a sample relation list-comparison scheme, and performing new flow analysis operation on the selected sample relation list and corresponding parameters to realize a project analysis module.
Specifically, step S3 further includes:
and step S300, providing a user to select the data uploaded by the user, and constructing and naming a data set according to the selected data. Specifically, the specific process of step S300 is as follows: selecting data types and items; selecting all samples to be analyzed; data confirmation is carried out; modifying the sample experiment name (name at the time of sequencing) to be the analysis name (i.e. the name used in the chart); naming a data set name; data sample submission is performed.
Step S301, a sample relationship single-grouping scheme and a sample relationship single-comparison scheme are constructed for the selected data set.
Specifically, the specific process of constructing the sample relationship single-grouping scheme in step S301 is as follows: selecting a data set; naming a sample relationship sheet; naming a first group name; selecting a sample of the packet; completing sample selection; clicking an adding group and setting other groups; and after all grouping settings are completed, clicking to complete grouping.
The specific process of constructing the sample relationship list-comparison scheme in step S301 is as follows: selecting a single sample comparison; selecting pairwise comparisons and selecting a multigroup comparison; and clicking to submit, and generating a sample relation list.
Step S302, data analysis is carried out on the selected sample relation list and corresponding parameters. In particular embodiments of the invention, routine microbial diversity analysis may be performed, including but not limited to, group analysis, OTU clustering, statistics, analysis; species composition analysis, Alpha diversity analysis, Beta diversity analysis, functional analysis, environmental factor analysis, personality report generation and the like.
The specific process of step S302 is: selecting a sample relation sheet; filling in parameters (e.g., a database); naming a process name; starting to analyze clicking; and popping up an information confirmation box, clicking to submit and analyze after the information is confirmed to be correct, and performing online data analysis.
Preferably, in step S3, an analysis result is further provided, the analysis result can be clicked to enter the dynamic interaction module, and the project analysis module can further provide operations of viewing the process parameters, editing and modifying the details based on the existing process, and resubmitting the details.
And step S4, providing a user to realize dynamic interactive data analysis, including but not limited to new task operation, data mining operation, and graph beautifying operation, and realizing a dynamic interactive module.
Specifically, step S4 further includes:
and S400, newly adding a group by acquiring the grouping scheme, newly adding an OTU table by screening the OTU, and starting new task interaction analysis by the newly added group and the newly added OTU table. Specifically, the user can click the grouping scheme to perform new grouping, click OTU screening to perform new OTU table, and start new task interaction analysis through the new grouping and the new OTU table.
And newly adding the task operation, namely performing reanalysis according to the newly added group and the OTU table based on the OTU data obtained by the process analysis. The newly added grouping operation can carry out one-key analysis processing on species pollution, outlier samples, modified sample names and the like; and adding an OTU table, and aiming at target groups, specifying and filtering OTUs or species, leveling, removing pollution and interference, carrying out stricter quality control and paying attention to high-abundance species. Meanwhile, the re-analysis can also add new environmental factors or metabolite data for analysis, so that compared with the traditional process that a user relies on a high-throughput sequencing company for analysis, the time consumption is shorter, and the experimental results are analyzed on the sample and data level more comprehensively.
Step S401, selecting parameter switching by one key, including but not limited to switching OTU/phylum and other species classification levels, switching sample/group, switching analysis models, switching threshold values and other aspects to perform operation, and eliminating clustering is not ideal, so that data is analyzed from multiple angles, and expected results of experiments are searched.
Step S402, providing richer parameters covered by the cloud platform, and performing one-click parameter adjustment and graphic beautification, wherein the parameters include but are not limited to color scheme switching, color modification, transparency adjustment, shape switching, font size adjustment, font type selection, title modification, graphic borders, scales, auxiliary lines/coils, color schemes, bar chart error bars, chart type switching and the like.
In summary, according to the dynamic interactive microbiology online analysis cloud platform and the generation method thereof, through the cloud service platform encapsulation type design, the complex experiment and analysis processes in the background are presented to the terminal user in a simple and interactive mode, so that the user with the non-biological information background can also complete the complex biological information analysis through the simple operation interface of the platform.
Compared with the prior art, the invention has the following advantages:
1) and (3) uploading sequencing data: the method can upload original sequencing reads at any time and any place, is compatible with various data sources and is compatible with various data types.
2) And (3) realizing the analysis of the newly added data flow: starting analysis by using original reads, and increasing a data adjustment space; items are freely merged and split, so that the limitation of multi-batch sampling analysis is avoided; sample names can be modified in batches; and the database version of the species annotation is customized, so that information updating and function analysis can be completed at any time.
3) The beautification and dynamic interaction degree of the perfected chart is high: a plurality of analysis points and dynamic interaction parameters are added, so that data/models can be switched at will, and data mining can be realized efficiently; beautifying parameters according to requirements to obtain a better quality data graph.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Modifications and variations can be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the present invention. Therefore, the scope of the invention should be determined from the following claims.
Claims (9)
1. A dynamic interactive microbiology online analysis cloud platform, comprising:
the user login management module is used for providing user registration account information, acquiring login information, determining the authority of a login user according to the login information, and providing an interface for the login user to perform biological information analysis on 16S, ITS and 18S and microorganism metagenome sequencing by using a cloud platform; providing a login user to download all analysis data and personalized reports in batch;
the user login management module comprises:
the data sharing unit is used for sharing, discussing and handing over the data result with others by the user;
the task viewing unit is used for providing a user link to the dynamic interaction module for analyzing content, viewing parameters and obtaining an analysis result;
the user authority management unit is used for providing process analysis content of corresponding authority of the cloud platform purchased by the user and providing different operation authorities of the user according to the recharging operation of the user;
the cloud platform information providing unit is used for providing relevant information of the cloud platform;
the data module is used for providing data uploading operation for a user and acquiring data uploaded by the user;
the project analysis module is used for selecting the data uploaded by the user, constructing a sample relation single-grouping scheme and a sample relation single-comparison scheme, and performing new flow analysis operation on the selected sample relation single and corresponding parameters;
and the dynamic interaction module is used for providing a user to realize dynamic interaction data analysis and presenting an analysis result in the form of an interactive user interface.
2. The dynamic interactive microbiology online analysis cloud platform of claim 1, wherein: the user login management module provides a user to download all analysis data and personalized reports in batch.
3. The dynamic interactive microbiology online analysis cloud platform of claim 1, wherein: the data module provides a user with the selection of data sources, data types and data formats of the data to be uploaded, uploads the selected data, and displays the data uploading state in real time in the uploading process.
4. The dynamic interactive microbiology online analysis cloud platform of claim 3, wherein: the data source is the single-ended or double-ended sequence of the different sequencing platforms from which the barcode linker has been removed, the data type is any one of bacteria/archaea/fungi/algae, 16S/ITS/18S, V3-V4/V5-V6, and the data format is any one of the suffixes fastq/. fq/. fq.gz/. fastq.gz/. fastq.bz2/. fq.bz2.
5. The dynamic interactive microbiology online analysis cloud platform of claim 1, wherein the project analysis module comprises:
the data selection and naming module is used for providing a user to select the data uploaded by the user, and constructing and naming a data set according to the selected data;
a grouping/comparison scheme construction module for constructing a sample relationship single-grouping scheme and a sample relationship single-comparison scheme for the selected data set;
and the analysis module is used for carrying out data analysis on the selected sample relation list and the corresponding parameters.
6. The dynamic interactive microbiology online analysis cloud platform of claim 5, wherein: the analysis module performs conventional microbial diversity analysis including, but not limited to, group analysis, OTU clustering/statistics/analysis, species composition analysis, Alpha diversity analysis, Beta diversity analysis, functional analysis, environmental factor analysis, personality report generation.
7. The dynamic interactive microbiology online analysis cloud platform of claim 1, wherein the dynamic interaction module comprises:
the newly added task module is used for newly adding groups by acquiring a grouping scheme, newly adding an OTU table by OTU screening, and starting new task interaction analysis by the newly added groups and the newly added OTU table;
and the data mining module is used for selecting parameter switching through one key, and eliminating unsatisfactory clustering, so that data is analyzed at multiple angles, and expected experimental results are searched.
8. The dynamic interactive microbiology online analysis cloud platform of claim 7, wherein: the one-click selection parameter switching comprises but is not limited to switching OTU/phylum species classification level, switching sample/group, switching analysis model and switching threshold.
9. A generation method of a dynamic interactive microbiology online analysis cloud platform comprises the following steps:
step S1, providing user registration account information, obtaining login information, determining the authority of the login user according to the login information, providing an interface for the login user to perform biological information analysis aiming at 16S, ITS and 18S and microorganism metagenome sequencing by using a cloud platform, and realizing a user login management module; providing a login user to download all analysis data and personalized reports in batch; the user is provided with the functions of sharing, discussing and handing over the data result with others; providing a user link to the dynamic interaction module for analyzing content, viewing parameters and acquiring an analysis result; providing process analysis content of corresponding rights of a user for purchasing the cloud platform, and providing different operation rights of the user according to the recharging operation of the user; providing relevant information of the cloud platform;
step S2, providing data uploading operation for users, and acquiring data uploaded by users;
step S3, selecting the data uploaded by the user, constructing a sample relation list-grouping scheme and a sample relation list-comparison scheme, and performing new flow analysis operation on the selected sample relation list and corresponding parameters to realize a project analysis module;
and step S4, providing a user to realize dynamic interactive data analysis.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911032717.3A CN110706750B (en) | 2019-10-28 | 2019-10-28 | Dynamic interactive microbiology online analysis cloud platform and generation method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911032717.3A CN110706750B (en) | 2019-10-28 | 2019-10-28 | Dynamic interactive microbiology online analysis cloud platform and generation method thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110706750A CN110706750A (en) | 2020-01-17 |
| CN110706750B true CN110706750B (en) | 2022-04-19 |
Family
ID=69202443
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911032717.3A Active CN110706750B (en) | 2019-10-28 | 2019-10-28 | Dynamic interactive microbiology online analysis cloud platform and generation method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110706750B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113643757B (en) * | 2020-12-02 | 2024-04-02 | 广东美格基因科技有限公司 | Microbiology data interaction analysis system |
| CN113377765A (en) * | 2021-07-09 | 2021-09-10 | 深圳华大基因科技服务有限公司 | Multi-group chemical data analysis system and data conversion method thereof |
| CN114707030A (en) * | 2022-03-29 | 2022-07-05 | 上海商汤智能科技有限公司 | Medical data management method and system, device and medium |
| CN117251290A (en) * | 2023-10-16 | 2023-12-19 | 广东美格基因科技有限公司 | Cloud server lease-based configurable group study data autonomous analysis system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105447336A (en) * | 2015-12-29 | 2016-03-30 | 北京百迈客生物科技有限公司 | Microbial diversity analysis method and system based on biological cloud platform |
| CN106599614A (en) * | 2016-11-07 | 2017-04-26 | 为朔医学数据科技（北京）有限公司 | Control method and system for processing and analysis process of high-throughput sequencing data |
| CN107368700A (en) * | 2017-07-21 | 2017-11-21 | 上海桑格信息技术有限公司 | Based on the microbial diversity interaction analysis system and method for calculating cloud platform |
| CN108537008A (en) * | 2018-03-20 | 2018-09-14 | 常州大学 | High-throughput gene sequencing big data analysis cloud platform system |
| CN109582292A (en) * | 2018-11-01 | 2019-04-05 | 广州基迪奥生物科技有限公司 | Online interaction cloud platform based on genomics and bioinformatics |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180165414A1 (en) * | 2016-12-14 | 2018-06-14 | FlowJo, LLC | Applied Computer Technology for Management, Synthesis, Visualization, and Exploration of Parameters in Large Multi-Parameter Data Sets |
-
2019
- 2019-10-28 CN CN201911032717.3A patent/CN110706750B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105447336A (en) * | 2015-12-29 | 2016-03-30 | 北京百迈客生物科技有限公司 | Microbial diversity analysis method and system based on biological cloud platform |
| CN106599614A (en) * | 2016-11-07 | 2017-04-26 | 为朔医学数据科技（北京）有限公司 | Control method and system for processing and analysis process of high-throughput sequencing data |
| CN107368700A (en) * | 2017-07-21 | 2017-11-21 | 上海桑格信息技术有限公司 | Based on the microbial diversity interaction analysis system and method for calculating cloud platform |
| CN109192242A (en) * | 2017-07-21 | 2019-01-11 | 上海桑格信息技术有限公司 | Based on the microbial diversity interaction analysis system and method for calculating cloud platform |
| CN108537008A (en) * | 2018-03-20 | 2018-09-14 | 常州大学 | High-throughput gene sequencing big data analysis cloud platform system |
| CN109582292A (en) * | 2018-11-01 | 2019-04-05 | 广州基迪奥生物科技有限公司 | Online interaction cloud platform based on genomics and bioinformatics |
Non-Patent Citations (1)
| Title |
|---|
| AVMCD：基于16S rRNA测序的微生物群落多样性分析与可视化平台;艾海新等;《辽宁大学学报(自然科学版)》;20190515;第46卷(第02期);第156-161页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110706750A (en) | 2020-01-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110706750B (en) | Dynamic interactive microbiology online analysis cloud platform and generation method thereof | |
| Chen et al. | IMG/M v. 5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes | |
| Kotopka et al. | Model-driven generation of artificial yeast promoters | |
| Vallenet et al. | MicroScope: an integrated platform for the annotation and exploration of microbial gene functions through genomic, pangenomic and metabolic comparative analysis | |
| Athar et al. | ArrayExpress update–from bulk to single-cell expression data | |
| von Kamp et al. | Use of CellNetAnalyzer in biotechnology and metabolic engineering | |
| Barrett et al. | BioProject and BioSample databases at NCBI: facilitating capture and organization of metadata | |
| Schmieder et al. | Quality control and preprocessing of metagenomic datasets | |
| Yue et al. | Long-read sequencing data analysis for yeasts | |
| Meyer et al. | Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit | |
| CN112133368A (en) | Automated analysis method of metagenome sequencing data based on third-generation sequencing technology | |
| Roven et al. | REDUCE: An online tool for inferring cis-regulatory elements and transcriptional module activities from microarray data | |
| CN111009289B (en) | RNA-seq online report flow analysis method and system based on cloud computing | |
| Wang | hppRNA—a Snakemake-based handy parameter-free pipeline for RNA-Seq analysis of numerous samples | |
| Tang et al. | GE-mini: a mobile APP for large-scale gene expression visualization | |
| Vrana et al. | Aquarium: open-source laboratory software for design, execution and data management | |
| Krakau et al. | nf-core/mag: a best-practice pipeline for metagenome hybrid assembly and binning | |
| Reeder et al. | MicrobiomeExplorer: an R package for the analysis and visualization of microbial communities | |
| Yu et al. | SCSsim: an integrated tool for simulating single-cell genome sequencing data | |
| Pereira et al. | MEWpy: a computational strain optimization workbench in Python | |
| Chen et al. | Selene: a PyTorch-based deep learning library for biological sequence-level data | |
| Gruenstaeudl | annonex2embl: automatic preparation of annotated DNA sequences for bulk submissions to ENA | |
| Belda et al. | Seeding the idea of encapsulating a representative synthetic metagenome in a single yeast cell | |
| Blanco et al. | Productive visualization of high-throughput sequencing data using the SeqCode open portable platform | |
| Gros et al. | ASHLEYS: automated quality control for single-cell Strand-seq data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |