Python Program (Library) to calculate linear regression between gene expression and gene synapse
statsmodels, pyvcf, mysql-connector-python, scikit-learn, pandas, pysam
pip install --upgrade --no-deps statsmodels
pip install PyVCF
pip install mysql-connector-python
pip install scikit-learn
pip install pandas
pip install pysam
The Data file should be put into the Data folder
Acceptible data format: synpase .vcf, .txt, .vcf.gz
gene expression .txt
Important notes
- Please put the tabix index file for vcf: .vcf.gz.tbi inside the same directory.
- The name prefix of the tabix index file should be exactly same with the vcf file.
- User will nee to specify four input:
- synapse name (id)
- gene expression name
- synapse vcf data path
- gene expression data path
- User will specify their input by modifying the user_input.csv inside the user_input folder.
- Optimize the indexing of gene expression file (currently use a map for indexing, higher space complexity).
- Make sure the result is correcct when using real data to test
- Handle more exceptions and corner cases.