/fcnarbb

A fully convolutional network (FCN) coupled with refinement residual block (RRB) and global average pooling layer (GAPL), namely FCNARRB

Primary LanguagePython

FCNA

Locating Transcription factor binding sites (TFBSs) by fully convolutional network

Requirements

  • Pytorch 1.1
  • Python 3.6
  • CUDA 9.0
  • Python packages: biopython, sklearn

Data preparation

(1) Downloading hg19.fa from http://hgdownload.soe.ucsc.edu/goldenPath/hg19/bigZips/, and put it into /your path/hg19/.

(2) Pre-processing datasets.

  • Usage: 
    bash process.sh <data path>

Implementation

Running FCNA

  • Usage: 
    bash run.sh <data path>

Locating TFBSs

  • Usage: 
    bash locate.sh <data path> <trained model path>

Predicting motifs

  • Usage: 
    bash motif.sh <data path> <trained model path>

Refining the prediction performance

  • Usage:
    Firstly encoding the located regions; Secondly running FCNAR on them.