Dataset Information

An optimized procedure greatly improves EST vector contamination removal.

ABSTRACT:

Background

The enormous amount of sequence data available in the public domain database has been a gold mine for researchers exploring various themes in life sciences, and hence the quality of such data is of serious concern to researchers. Removal of vector contamination is one of the most significant operations to obtain accurate sequence data containing only a cDNA insert from the basecalls output by an automatic DNA sequencer. Popular bioinformatics programs to accomplish vector trimming include LUCY, cross_match and SeqClean.

Results

In a recent study, where the program SeqClean was used to remove vector contamination from our test set of EST data compiled through various library construction systems, however, a significant number of errors remained after preliminary trimming. These errors were later almost completely corrected by simply using a re-linearized form of the cloning vector to compare against the target ESTs. The modified trimming procedure for SeqClean was also compared with the trimming efficiency of the other two popular programs, LUCY2, and cross_match. Using SeqClean with a re-linearized form of the cloning vector significantly surpassed the other two programs in all tested conditions, while the performance of the other two programs was not influenced by the modified procedure. Vector contamination in dbEST was also investigated in this study: 2203 out of the 48212 ESTs sampled from dbEST (2007-04-18 freeze) were found to match sequences in UNIVEC.

Conclusion

Vector contamination remains a serious concern to the data quality in the public sequence database nowadays. Based on the results presented here, we feel that our modified procedure with SeqClean should be recommended to all researchers for the task of vector removal from EST or genomic sequences.

SUBMITTER: Chen YA

PROVIDER: S-EPMC2194723 | biostudies-literature | 2007 Nov

REPOSITORIES: biostudies-literature

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Publications

An optimized procedure greatly improves EST vector contamination removal.

Chen Yi-An YA Lin Chang-Chun CC Wang Chin-Di CD Wu Huan-Bin HB Hwang Pei-Ing PI

BMC genomics 20071113

<h4>Background</h4>The enormous amount of sequence data available in the public domain database has been a gold mine for researchers exploring various themes in life sciences, and hence the quality of such data is of serious concern to researchers. Removal of vector contamination is one of the most significant operations to obtain accurate sequence data containing only a cDNA insert from the basecalls output by an automatic DNA sequencer. Popular bioinformatics programs to accomplish vector trim ...[more]

PMID: 17997864

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Dataset Information

An optimized procedure greatly improves EST vector contamination removal.

Background

Results

Conclusion

Publications

An optimized procedure greatly improves EST vector contamination removal.

Similar Datasets

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