GSW-FI

Description

{GSW-FI: A GLM model incorporating shrinkage and double-weighted strategies for identifying cancer driver genes with functional impact}

Instructions to GSW-FI

Dependencies

Some R packages should be imported to apply GSW-FI, including:

1. data.table
2. plyr
3. stringr
4. MASS
5. gamlss

Run GSW-FI

Identify driver genes based on GSW-FI

1. Run data_preprocess.R

• Input:

  maf.file.name

• Output:

  cancer.name + ‘_gene_effect.txt’

  cancer.name + ‘_mutationdata.txt’

  cancer.name is the name of the cancer for the to MAF file.

• Folder structure:

  GSW-FI
  |__ README
  |__ data_preprocess.R
  |__ acc_tcga.maf.txt
  

2. Run calculateFIS_estimatedBFIS.R

• Input:

  maf.file.name or cancer.name

  cancer.name + ‘_gene_effect.txt’ obtained by data_preprocess.R

  cancer.name + ‘_mutationdata.txt’ obtained by data_preprocess.R

  mutation_type_dictionary_file.txt

  MA_scores_rel3_hg19_full (download from http://mutationassessor.org/r3/)

• Output:

  cancer.name + ‘_geneFeatureScore.txt’

• Folder structure:

  GSW-FI
  |__ README
  |__ calculateFIS_estimatedBFIS.R
  |__ ACC_gene_effect.txt
  |__ ACC_mutationdata.txt
  |__ mutation_type_dictionary_file.txt
  |__ ./MA_scores_rel3_hg19_full/MA_scores_rel3_hg19_chr
  

3. Run identify_drivers.R

• Input:

  maf.file.name or cancer.name

  cancer.name + ‘_geneFeatureScore.txt’

• Output:

  driver genes

• Folder structure:

  GSW-FI
  |__ README
  |__ identify_drivers.R
  |__ ACC_geneFeatureScore.txt
  

Developer

• Xiaolu Xu
• lu.xu@lnnu.edu.cn
• School of Computer and Artificial Intelligence
• Liaoning Normal University
• Dalian
• China