mmsplice 0.2.1

Predict splicing variant effect from VCF

# mmsplice

[](https://pypi.python.org/pypi/mmsplice)
[](https://travis-ci.org/s6juncheng/mmsplice)

Predict splicing variant effect from VCF

* Free software: MIT license


## Usage example
------

NOTE: make sure you split and left-normalize the input VCF file.

Check notebooks/example.ipynb

```python
# Import
from mmsplice.vcf_dataloader import SplicingVCFDataloader
from mmsplice import MMSplice, predict_all_table
from mmsplice.utils import max_varEff

# example files
gtf = 'tests/data/test.gtf'
vcf = 'tests/data/test.vcf.gz'
fasta = 'tests/data/hg19.nochr.chr17.fa'
gtfIntervalTree = '../tests/data/test.pkl' # pickle exon interval Tree

# dataloader to load variants from vcf
dl = SplicingVCFDataloader(gtf,
fasta,
vcf,
out_file=gtfIntervalTree,
split_seq=False)

# Specify model
model = MMSplice(
exon_cut_l=0,
exon_cut_r=0,
acceptor_intron_cut=6,
donor_intron_cut=6,
acceptor_intron_len=50,
acceptor_exon_len=3,
donor_exon_len=5,
donor_intron_len=13)

# Do prediction
predictions = predict_all_table(model, dl, batch_size=1024, split_seq=False, assembly=False)

# Summerize with maximum effect size
predictionsMax = max_varEff(predictions)
```

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History
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0.1.0 (2018-07-17)
------------------

* First release on PyPI.