TIVar
Translation Initiation Variation
Predict translation initiation (TI) efficiency for potential start codons, based on the context sequence near the start codon. Given SNP/Indel variation, this tools can predict changes of TI efficiencies between ref and alt alleles.
INSTALL
Python version >= 3.4.
Requirements
Install from source
git clone https://github.com/zhpn1024/TIVar
python setup.py install
or
python setup.py install --user
Install from PyPI
pip install tivar
Usage
predict
This module can calculate TI efficiency scores from given sequences.
Fasta sequence file as input:
tivar predict -S test1.fa -o out1.txt
Provide sequence in the parameter:
tivar predict -s aaaaaacaaaaaaaTGTACAATGGATGCATTGAAATTATATGTAATTGTATAAATGGTGCAACA -o out1.txt
Provide transcript annotation and genome sequence:
tivar predict -g hg38_gc31.gtf.gz -f hg38.fa -o out1.txt
The output is like:
| SeqID | Pos | StartSeq | EffScore |
|---|---|---|---|
| Seq | 13 | aacaaaaaa-aTG-TACA | 0.30354 |
| Seq | 20 | aaaTGTACA-ATG-GATG | 0.37131 |
diff
This module predict TI changes caused by sequence variation.
tivar diff -i test.vcf -g hg38_gc31.gtf.gz -f hg38.fa -o out2.txt
The output is like:
| Gid | Tid | Var | GenoPos | Strand | Pos | RefSeq | AltSeq | EffeRef | EffeAlt | Diff | FC | Type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ENSG00000134262.13 | ENST00000369569.6 | chr1:113895309:A>AC | 113895310 | - | 2056 | ACCCTCCAG-ATG-GCTC | ACCCTCCAG-AGT-GGCT | 0.32097 | 0.0 | -0.321 | 0.0 | TI_decreased |
| ENSG00000134262.13 | ENST00000369569.6 | chr1:113895309:A>AC | 113895310 | - | 2056 | ACCCTCCAG-ATG-GCTC | CCCTCCAGA-GTG-GCTC | 0.32097 | 0.04335 | -0.2776 | 0.1351 | TI_decreased |
1 maintainer
Metadata
1 maintainer
Release files for tivar 0.1.3
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| File | Interpreter | ABI | Platform | Actions Reset |
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| tivar-0.1.3-py3-none-any.whl | Python 3 | none | any | Details for tivar-0.1.3-py3-none-any.whl |
Release files / tivar-0.1.3-py3-none-any.whl
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| Tags | Python 3 |
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