mRNN - mRNA RNN (mRNA recurrent neural network)
mRNN is a package for distinguishing coding transcripts from noncoding using gated recurrent neural networks (GRNNs).
How to get mRNN
You can obtain mRNN through github:
git clone https://github.com/hendrixlab/mRNN.git
mRNN: Included Files
Testing and Training
train_mRNN.py - training mRNN model based on input training sequences.
Example: $ python mRNN/train_mRNN.py -e 128 -r 32 -d 0.4 -o mRNN.16K.da1.1 -s 3 -E 4 mRNAs.train16K.da1.fa lncRNAs.train16K.da1.fa mRNAs.valid500.fa lncRNAs.valid500.fa > epochs.mRNN.16K.da1.1.txt
test_mRNN.py - test the accuracy of a known set of mRNAs and lncRNAs.
Example: $ python mRNN/test_mRNN.py -w w14u3.pkl -f test mRNAs.test500.fasta lncRNAs.test500.fasta
test_ensemble_mRNN.py - Ensemble testing with mRNN models. Models are provided as a comma-separated list.
Example: $ python mRNN/test_ensemble_mRNN.py -w w10u5.pkl,w14u3.pkl,w16u5.pkl,w18u1b.pkl,w23u2.pkl -f test mRNAs.test500.fasta lncRNAs.test500.fasta
mRNN.py - Basic prediction of coding probability for a set of input sequences.
mRNN_ensemble.py - Basic prediction of coding probability for a set of input sequences using a set of models.
mutation_analysis.py - For the provided input sequence, perform a mutation analysis involving every possible point-mutation on the input sequence, and computing its corresponding score change.
pair_mutation_analysis.py - For a provided input sequence, computer all possible pairs of mutation i,a,j,b where position i is changed to a and position j is changed to b.
shuffle_analysis.py - For the provided input sequences, shuffle each of them and report the scores of the shuffled sequence to the unaltered sequence.
truncation_analysis.py - Coding score trajectory. Compute the mRNN coding probability for all truncations of the input sequence from position 1 to i.
Core mRNN modules:
These modules aren't called directly, but involved in basic function of mRNN
fasta.py - input reading FASTA files model.py - building the mRNN model evaluate.py - Computing accuracy, batch testing preprocessing.py - Utilities for various preprocessing
How to get data from mRNN project
The data used to train mRNN and produce the weights provided in the weights directory, you can download them from the following location: