標題: PEAT: an intelligent and efficient paired-end sequencing adapter trimming algorithm
作者: Li, Yun-Lung
Weng, Jui-Cheng
Hsiao, Chiung-Chih
Chou, Min-Te
Tseng, Chin-Wen
Hung, Jui-Hung
生物科技學系
生物資訊及系統生物研究所
Department of Biological Science and Technology
Institude of Bioinformatics and Systems Biology
公開日期: 21-一月-2015
摘要: Background: In modern paired-end sequencing protocols short DNA fragments lead to adapter-appended reads. Current paired-end adapter removal approaches trim adapter by scanning the fragment of adapter on the 3\' end of the reads, which are not competent in some applications. Results: Here, we propose a fast and highly accurate adapter-trimming algorithm, PEAT, designed specifically for paired-end sequencing. PEAT requires no a priori adaptor sequence, which is convenient for large-scale meta-analyses. We assessed the performance of PEAT with many adapter trimmers in both simulated and real life paired-end sequencing libraries. The importance of adapter trimming was exemplified by the influence of the downstream analyses on RNA-seq, ChIP-seq and MNase-seq. Several useful guidelines of applying adapter trimmers with aligners were suggested. Conclusions: PEAT can be easily included in the routine paired-end sequencing pipeline. The executable binaries and the standalone C++ source code package of PEAT are freely available online.
URI: http://dx.doi.org/10.1186/1471-2105-16-S1-S2
http://hdl.handle.net/11536/124718
ISSN: 1471-2105
DOI: 10.1186/1471-2105-16-S1-S2
期刊: BMC BIOINFORMATICS
Volume: 16
顯示於類別:期刊論文