Virus gene recognition

ViMRT has built virus gene corpus from NCBI PubMed and gene database and developed a Python script to identify virus genes from virus mutation sentences.

Virus gene corpus

ViMRT has collected the gene name list of 7,194 viruses. Users can also add their own gene names at gene_vocabulary.txt file in genecorpus folder. Besides, ViMRT has further eliminated possible identification errors due to short virus gene names, eg., S gene of HBV in gene_vocabulary_error.txt file in genecorpus folder. Users can also complement errors according to their own needs.

Identifying virus gene

python Gene_Recognize.py  -i [input] -o [output] -v [virus]

input: the user can provide input file (gene_example.txt). The input file format: PMID+"|pmid|"+sentence
output: the user can provide output folder path. The default path is the current path.
virus: the user can choose virus name, such as HBV, HBV;HPV, etc. The default parameter is "fullvirus"

Example: python Gene_Recognize.py -i ./gene_example.txt -o ./ViMRT_gene/ -v HBV

*Note: we recommend selecting one virus name. Becuase the default parameter will match genes of all viruses in turn, which will run for a long time.

Disease recognition

ViMRT firstly needs a Python NLP Stanza library for many human languages to identify disease from virus mutation sentences. The stanza usage can refer to the github website.

Installing stanza

pip install stanza

Downloading stanza disease models

import stanza 
stanza.download('en', package='mimic', processors={'ner': 'bc5cdr'}, verbose=False)
stanza.download('en', package='mimic', processors={'ner': 'ncbi_disease'}, verbose=False)

Identifying disease

Disease corpus

ViMRT has built disease corpus from CTD database to optimize the results of stanza using Python script. Users can also add their own disease name at disease_vocabulary.txt file and complement new errors at disease_vocabulary_error.txt file in diseasecorpus folder to delete identification errors of stanza.

Identifying and optimizing disease

python Disease_Recognize.py -i [input] -o [output]

input: the user can provide input file (disease_example.txt). The input file format: PMID+"|pmid|"+sentence.
output: the user can provide output folder path. The default path is the current path.

Example: python Disease_Recognize.py -i ./disease_example.txt -o ./ViMRT_disease/ -v HBV

ViMRT web search engine

Overview

The ViMRT interface provides an easy-to-use graphical web interface. It can quickly and accurately search virus mutation-related information including virus genes and related disease for users.

Homepage

The homepage of ViMRT provides a navigation of our search engine, including listing the modules of upper right panel, providing two main features for helping users to use and search data. Users can enter their interested virus mutation or virus gene or related disease to retrieve the detail information in the centre select box.

Virus mutation information

The “Virus mutation information” page provides the best matching entity information of the query. Take the entry of “HBV-M:C1653T” in HBV as an example. After users choose the “HBV-M:C1653T”, ViMRT shows a list of publications including C1653T mutation with red background entities, ordered by publication date, as well as other co-occurrence entities with different colors including genes(green texts), diseases(purple texts), and other mutations (red texts) in same sentence. Click ‘More Details’ to show more mutation sentences of selected entity. The drop-down menu items on the upper left for users to get co-occurrence sentence of different entities. The drop-down menu items on lower left can filter publications based on "Year", "Position" and "PMID" of publication matching the query. The "Download the files" button on upper rigtht allows the user to download the search data files including mutation information.

Co-occurrence relationship

The “Co-occurrence relationship” page provides the co-occurrence correlation of the mutation and disease including 7 viruses based on the sentences. Users can firstly click the "To search the relationship" button in at the homepage, the web will acquiescently return the co-occurrence correlation of HBV by the histogram chart and table. Histogram chart shows the score of co-occurrence mutataions ranking top 10. The table shows the information including mutation, gene, disease, score, significance (Fisher's test,***, p < 0.001; **, p < 0.01; *, p < 0.05; ns, not significant). Click "View" to get the detailed literature information of choosed mutation. Click virus names in the left menu items to view the relationship information of each virus

Dataset Download

ViMRT allows the user to download related tools of ViMRT and literature files of 7 viruses on the “Dataset” page. Meanwhile, users can directly download mutation data files of 7 viruses including records with pmid, title, sentence, year, journal, region, mutation, gene, etc. in txt format.