/GRN_linearRD

An efficient gene regulatory network inference algorithm for early Drosophila melanogaster embryogenesis

Primary LanguageR

An efficient gene regulatory network inference algorithm for early Drosophila melanogaster embryogenesis

Reference

In submission.

Download

git clone https://github.com/hmatsu1226/GRN_linearRD
cd GRN_linearRD

Or download from "Download ZIP" button and unzip it.

Usage
Rscript GRN_linearRD.R <Input_file> <Output_file1> <Output_file2> <s>
  • Input_file : G x S matrix of expression data; G is the number of gene, S is the number of position
  • Output_file1 : Inferred W.
  • Output_file2 : Inferred A (-W*W).
  • s : The size of small space step (delta s).
Example of running SCODE
Rscript GRN_linearRD.R data/data_dm.txt W_dm.txt A_dm.txt 0.001

Dataset

The smoothed gap gene expression data. The original expression data is downloaded from SuperFly (http://superfly.crg.eu).

data/data_dm.txt

The smoothed gap gene data (hb, Kr, gt, and kni) of Drosophila melanogaster.

data/data_ca.txt

The smoothed gap gene data (hb, Kr, gt, and knl) of Clogmia albipunctata.

License

Copyright (c) 2017 Hirotaka Matsumoto Released under the MIT license