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Base-calling algorithm with vocabulary (BCV) method for analyzing population sequencing chromatogramsстатья
Статья опубликована в высокорейтинговом журнале
Информация о цитировании статьи получена из
Web of Science,
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 7 декабря 2013 г.
- Авторы: Fantin YS, Neverov AD, Favorov AV, Alvarez-Figueroa MV, Braslavskaya SI, Gordukova MA, Karandashova Kuleshov KV, Myznikova AI, Polishchuk MS, Reshetov DA, Voiciehovskaya YA, Mironov AA, Chulanov VP
- Журнал: PLoS ONE
- Том: 8
- Номер: 1
- Год издания: 2013
- Издательство: Public Library of Science
- Местоположение издательства: United States
- Первая страница: e54835
- DOI: 10.1371/journal.pone.0054835
- Аннотация: Sanger sequencing is a common method of reading DNA sequences. It is less expensive than high-throughput methods, and it is appropriate for numerous applications including molecular diagnostics. However, sequencing mixtures of similar DNA of pathogens with this method is challenging. This is important because most clinical samples contain such mixtures, rather than pure single strains. The traditional solution is to sequence selected clones of PCR products, a complicated, time-consuming, and expensive procedure. Here, we propose the base-calling with vocabulary (BCV) method that computationally deciphers Sanger chromatograms obtained from mixed DNA samples. The inputs to the BCV algorithm are a chromatogram and a dictionary of sequences that are similar to those we expect to obtain. We apply the base-calling function on a test dataset of chromatograms without ambiguous positions, as well as one with 3-14% sequence degeneracy. Furthermore, we use BCV to assemble a consensus sequence for an HIV genome fragment in a sample containing a mixture of viral DNA variants and to determine the positions of the indels. Finally, we detect drug-resistant Mycobacterium tuberculosis strains carrying frameshift mutations mixed with wild-type bacteria in the pncA gene, and roughly characterize bacterial communities in clinical samples by direct 16S rRNA sequencing.
- Добавил в систему: Миронов Андрей Александрович