https://github.com/carlomazzaferro/neoantigen

package to obtain neoantigen candidates from a vcf file.
https://github.com/carlomazzaferro/neoantigen

Last synced: 2 months ago
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package to obtain neoantigen candidates from a vcf file.

• Host: GitHub
• URL: https://github.com/carlomazzaferro/neoantigen
• Owner: carlomazzaferro
• License: other
• Created: 2016-08-09T17:45:17.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2017-02-08T04:07:00.000Z (over 8 years ago)
• Last Synced: 2025-03-20T02:17:56.563Z (3 months ago)
• Language: Jupyter Notebook
• Size: 16.5 MB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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```python

from VarP import utils

"""

Set reader names. Since these and the files will be sorted automatically

by name, make sure the names of readers and files are similar

"""

reader_names = ['Tumor_RNA_Reader', 'Tumor_Targeted_Reader',

           'Normal_DNA_Reader', 'Normal_Blood_Reader',

           'Somatic_Mutect_Reader']

path_to_files = '/Volumes/Seagate Backup Plus Drive/vcf_files/varcode_to_test/'

#Initialize class HandleReaders.

myhandler = utils.HandleReaders(reader_names)

"""

Create a list of variant collections. See varcode's documentation for

more info on this type of data

"""

list_collections = myhandler.create_collection_from_readers(path_to_files)

type(list_collections[4])  #variant.Collection

#Select one to work on

my_collection = list_collections[4]

#Obtain codon effects from variant collection

list_coding_effects = myhandler.return_list_coding_effects(my_collection)

#Obtain protein list from variant collection

protein_list = myhandler.return_protein_list(list_coding_effects)

#Return a dataframe for easy viz

dataframe = myhandler.return_dataframe(protein_list, list_coding_effects)

#Generate fasta file for post-processing

myhandler.generate_fasta_file(dataframe, path_to_files+'peps.txt')

```