Methods for training and interpretation of an ensemble of neural networks for multi-task functional prediction of accessibility or histone modifications from DNA sequence.
We provide two methods of interpretation of trained DeepAccess models:
ExpectedPatternEffect and DifferentialExpectedPatternEffect can be run using either motifs in PWM or PCM representation (from a database like HOCOMOCO or HOMER) or patterns in a fasta representation which can be used to test spacing or combinations of motifs.
Per-nucleotide importance is run using an input of one or more fastas and returns the model-derived importance of each nucleotide within each fasta sequence.
For predicting from a trained model, input the directory of the model and one or more fasta sequences:
deepaccess interpret -trainDir trained_deepaccessmodel -fastas seqs_1.fa seqs_2.fa
The output will be files trained_deepaccessmodel/seqs_1.prediction, trained_deepaccessmodel/seqs_2.prediction, containing the predicted accessibility for each class.
usage: deepaccess interpret [-h] -trainDir TRAINDIR
[-fastas FASTAS [FASTAS ...]]
[-l LABELS [LABELS ...]] [
-c COMPARISONS [COMPARISONS ...]]
[-evalMotifs EVALMOTIFS]
[-evalPatterns EVALPATTERNS]
[-p POSITION] [-saliency]
[-subtract] [-bg BACKGROUND] [-vis]
optional arguments:
-h, --help show this help message and exit
-trainDir TRAINDIR, --trainDir TRAINDIR
-fastas FASTAS [FASTAS ...], --fastas FASTAS [FASTAS ...]
-l LABELS [LABELS ...], --labels LABELS [LABELS ...]
-c COMPARISONS [COMPARISONS ...], --comparisons COMPARISONS [COMPARISONS ...]
-evalMotifs EVALMOTIFS, --evalMotifs EVALMOTIFS
-evalPatterns EVALPATTERNS, --evalPatterns EVALPATTERNS
-p POSITION, --position POSITION
-saliency, --saliency
-subtract, --subtract
-bg BACKGROUND, --background BACKGROUND
-vis, --makeVis
| Argument | Description | Example |
|---|---|---|
| -h, –help | show this help message and exit | NA |
| -trainDir –trainDir | directory containing trained DeepAccess model | test/ASCL1vsCTCF |
| -fastas –fastas | list of fasta files to evaulate | test/ASCL1vsCTCF/test.fa |
| -l –labels | list of labels for each bed file | C1 C2 C3 |
| -c –comparisons | list of comparisons between different labels | ASCL1vsCTCF ASCL1vsNone runs differential EPE between ASCL1 and CTCF and EPE on ASCL1; C1,C2vsC3 runs differential EPE for (C1 and C2) vs C3 |
| -evalMotifs –evalMotifs | PWM or PCM data base of DNA sequence motifs | default/HMv11_MOUSE.txt |
| -evalPatterns –evalPatterns | fasta file containing DNA sequence patterns | data/ASCL1_space.fa |
| -bg –bg | fasta file containning background sequences | default/backgrounds.fa |
| -saliency –saliency | calculate per base nucleotide importance | NA |
| -subtract –subtract | use subtraction instead of ratio for EPE / DEPE | False |
| -vis –makeVis | to be used with saliency to make plot visualizing results | NA |