tivar 0.1.0

Translation Initiation Variation

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

NumPy

PyTorch

Install from source

git clone https://github.com/zhpn1024/TIVar

python setup.py install

or

python setup.py install --user

Usage

predict

This module can and 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	0.08535
Seq	20	aaaTGTACA-ATG-GATG	0.34153

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	0.31412	0.0	-0.3141	0.0	TI_decreased
ENSG00000134262.13	ENST00000369569.6	chr1:113895309:A>AC	113895310	-	2056	ACCCTCCAG-ATG-GCTC	CCCTCCAGA-GTG-GCTC	0.31412	0.04335	-0.2708	0.138	TI_decreased