Toward the development of a gene index to the human genome: an assessment of the nature of high-throughput EST sequence data.
A rigorous analysis of the Merck-sponsored EST data with respect to known gene sequences increases the utility of the data set and helps refine methods for building a gene index. A highly curated human transcript data base was used as a reference data set of known genes. A detailed analysis of EST sequences derived from known genes was performed to assess the accuracy of EST sequence annotation. The EST data was screened to remove low-quality and low-complexity sequences. A set of high-quality ESTs similar to the transcript data base was identified using BLAST; this subset of ESTs was compared with the set of known genes using the Smith-Waterman algorithm. Error rates of several types were assessed based on a flexible match criterion defining sequence identity. The rate of lane-tracking errors is very low, approximately 0.5%. Insert size data is accurate within approximately 20%. Reversed clone and internal priming error rates are approximately 5% and 2.5%, respectively, contributing to the incorrect identification of reads as 3' ends of genes. Follow-up investigation reveals that a significant number of clones, miscategorized as reversed, represent overlapping genes on the opposite strand of entries in the transcript data base. Relevance of these results to the creation of a high-quality index to the human genome capable of supporting diverse genomic investigations is discussed.
Merck Research Laboratories, Department of Bioinformatics, Rahway, New Jersey 07065, USA. aaronson@merck.com
J S
JS
Aaronson
B
B
Eckman
R A
RA
Blevins
J A
JA
Borkowski
J
J
Myerson
S
S
Imran
K O
KO
Elliston
D000465:Algorithms; D001483:Base Sequence; D002678:Chimera; D002874:Chromosome Mapping; D003001:Cloning, Molecular; D016208:Databases, Factual; D005260:Female; D015894:Genome, Human; D006801:Humans; D007223:Infant; D015203:Reproducibility of Results; D016324:Sequence Tagged Sites; D014158:Transcription, Genetic