mrzResearchArena / iRecSpot

iRecSpot-EF: Effective Sequence Based Features for Recombination Hotspot Prediction

iRecSpot-EF: Effective Sequence Based Features for Recombination Hotspot Prediction

Installation Process :

Required Python Packages:

Install: python (version >= 3.5)
Install: sklearn (version >= 0.19.0)
Install: numpy (version >= 1.13.0)
Install: pandas (version >= 0.21.0)
Install: matplotlib (version >= 2.1.0)
Install: pickle

pip install < package name >
example: pip install sklearn

or
We can download from anaconda cloud.

Code Description :

• Features Extraction :

  user@machine:~$ python extractionFeatures.py

  Note #1: It will provide a dataset named fullDataset.csv from FASTA sequences. (fullDataset.csv)

  Note #2: readXY.py ( This file will fetch data from hotSpot.fasta and coldSpot.fasta files. )

• Features Selection :

  user@machine:~$ python selectionFeatures.py

  Note #1: It will provide a dataset named selectedDataset.csv from fullDataset.csv.

• Training Model :

  user@machine:~$ python modelDump