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  4. Transcript annotation tool (TransAT): an R package for retrieving annotations for transcript-specific genetic variants
 
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Transcript annotation tool (TransAT): an R package for retrieving annotations for transcript-specific genetic variants

Journal
BMC bioinformatics
Journal Volume
22
Journal Issue
1
Date Issued
2021-06-28
Author(s)
Shih, Ching-Yu
Amrita Chattopadhyay  
CHIEN-HUI WU  
YU-WEN TIEN  
TZU-PIN LU  
DOI
10.1186/s12859-021-04243-z
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/587899
URL
https://scholars.lib.ntu.edu.tw/handle/123456789/577821
Abstract
An individual's genetics play a role in how RNA transcripts are generated from DNA and consequently in their translation into protein. Transcriptional and translational profiling of patients furnishes the information that a specific marker is present; however, it fails to provide evidence whether the marker correlates with response to a therapeutic agent. A comparative analysis of the frequency of genetic variants, such as single nucleotide polymorphisms (SNPs), in diseased and general populations can identify pathogenic variants in individual patients. This is in part because SNPs have considerable effects on protein function and gene expression when they occur in coding regions and regulatory sequences, respectively. Therefore, a tool that can help users to obtain the allele frequency for a corresponding transcript is the need of the day. Several annotation tools such as SNPnexus and VariED are publicly available; however, none of them can use transcript IDs as input and provide the corresponding genomic positions of variants.
Subjects
Allele frequency; R package; TransAT; Transcript annotation; Variant annotation
SDGs

[SDGs]SDG3

Other Subjects
Gene expression; Proteins; Comparative analysis; Ethnic populations; General population; Global population; Protein functions; Regulatory sequences; Single nucleotide polymorphisms; Therapeutic agents; Translation (languages); genome; genomics; human; molecular genetics; single nucleotide polymorphism; software; Genome; Genomics; Humans; Molecular Sequence Annotation; Polymorphism, Single Nucleotide; Software
Type
journal article

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