Comparison of computational methods for identifying translation initiation sites in EST dataReport as inadecuate




Comparison of computational methods for identifying translation initiation sites in EST data - Download this document for free, or read online. Document in PDF available to download.

BMC Bioinformatics

, 5:14

First Online: 16 February 2004Received: 13 August 2003Accepted: 16 February 2004

Abstract

BackgroundExpressed Sequence Tag EST sequences are generally single-strand, single-pass sequences, only 200–600 nucleotides long, contain errors resulting in frame shifts, and represent different parts of their parent cDNA.
If the cDNAs contain translation initiation sites, they may be suitable for functional genomics studies.
We have compared five methods to predict translation initiation sites in EST data: first-ATG, ESTScan, Diogenes, Netstart, and ATGpr.

ResultsA dataset of 100 EST sequences, 50 with and 50 without, translation initiation sites, was created.
Based on analysis of this dataset, ATGpr is found to be the most accurate for predicting the presence versus absence of translation initiation sites.
With a maximum accuracy of 76%, ATGpr more accurately predicts the position or absence of translation initiation sites than NetStart 57% or Diogenes 50%.
ATGpr similarly excels when start sites are known to be present 90%, whereas NetStart achieves only 60% overall accuracy.
As a baseline for comparison, choosing the first ATG correctly identifies the translation initiation site in 74% of the sequences.
ESTScan and Diogenes, consistent with their intended use, are able to identify open reading frames, but are unable to determine the precise position of translation initiation sites.

ConclusionsATGpr demonstrates high sensitivity, specificity, and overall accuracy in identifying start sites while also rejecting incomplete sequences.
A database of EST sequences suitable for validating programs for translation initiation site prediction is now available.
These tools and materials may open an avenue for future improvements in start site prediction and EST analysis.

Electronic supplementary materialThe online version of this article doi:10.1186-1471-2105-5-14 contains supplementary material, which is available to authorized users.

Download fulltext PDF



Author: Afshin Nadershahi - Scott C Fahrenkrug - Lynda BM Ellis

Source: https://link.springer.com/



DOWNLOAD PDF




Related documents