piRNN Program(Python) Kai Wang 01/13/2017 GENERAL INFORMATION ----------------------------------------------------------------- - piRNN is a program that used for piRNA detection. The deep learning library that we used is Keras that running on top of TensorFlow. - The program can be downloaded at htps://github.com/wangk4/piRNN After downloading and unziping, the following items should be found in the folder: - piRNN.py - functions.py - Ele_piRNN.h5 - Dro_piRNN.h5 - Rat_piRNN.h5 - Hum_piRNN.h5 - README - test_input_data.fa - Four species' (C. elegans, D. melanogaster, Rat, and Human) piRNAs data were used for training four differnet models, respectively. USAGE NOTES ----------------------------------------------------------------- - The program can be easily executed in a terminal like: python piRNN.py [-h] -s <species code> -i <input file in fasta format> -o <output file> - The species code should be a number that from 1, 2, 3, or 4. - 1 means C. elegans model. - 2 means D. melanogaster model. - 3 means Rat model. - 4 means Human model. - The input file should be small RNA data that in fasta format. - The output file is also in fasta format. - Use "-h" to show help information. *please unzip the model files first. RUN EXAMPLE DATA ----------------------------------------------------------------- - The test_input_data.fa is used for testing the program. Users can run the following command to test the program. python piRNN.py -s 4 -i test_input_data.fa -o out.fa - The result should be in out.fa CONTACT INFORMATION ----------------------------------------------------------------- Kai Wang, Department of Biology, Miami University, Oxford, Ohio, USA Email: wangk4@miamioh.edu Prof. Chun Liang, Department of Biology, Miami University, Oxford, Ohio, USA Email: liangc@miamioh.edu