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RNA-seq has become a routine approach for transcriptome profiling, generating unprecedented data that could be used to identify and quantify APA site usage. A number of computational approaches for identifying APA sites and\/or dynamic APA events from RNA-seq data have emerged in the literature, which provide valuable yet preliminary results that should be refined to yield credible guidelines for the scientific community. In this review, we provided a comprehensive overview of the status of currently available computational approaches. We also conducted objective benchmarking analysis using RNA-seq data sets from different species (human, mouse and Arabidopsis) and simulated data sets to present a systematic evaluation of 11 representative methods. Our benchmarking study showed that the overall performance of all tools investigated is moderate, reflecting that there is still lot of scope to improve the prediction of APA site or dynamic APA events from RNA-seq data. Particularly, prediction results from individual tools differ considerably, and only a limited number of predicted APA sites or genes are common among different tools. Accordingly, we attempted to give some advice on how to assess the reliability of the obtained results. We also proposed practical recommendations on the appropriate method applicable to diverse scenarios and discussed implications and future directions relevant to profiling APA from RNA-seq data.<\/jats:p>","DOI":"10.1093\/bib\/bbz068","type":"journal-article","created":{"date-parts":[[2019,5,15]],"date-time":"2019-05-15T19:13:36Z","timestamp":1557947616000},"page":"1261-1276","source":"Crossref","is-referenced-by-count":35,"title":["A survey on identification and quantification of alternative polyadenylation sites from RNA-seq data"],"prefix":"10.1093","volume":"21","author":[{"given":"Moliang","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Automation, Xiamen University, Xiamen 361005, China"},{"name":"Xiamen Research Institute of National Center of Healthcare Big Data, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoli","family":"Ji","sequence":"additional","affiliation":[{"name":"Department of Automation, Xiamen University, Xiamen 361005, China"},{"name":"Xiamen Research Institute of National Center of Healthcare Big Data, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongjuan","family":"Fu","sequence":"additional","affiliation":[{"name":"Department of Automation, Xiamen University, Xiamen 361005, China"},{"name":"Xiamen Research Institute of National Center of Healthcare Big Data, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianmin","family":"Lin","sequence":"additional","affiliation":[{"name":"Xiang' an hospital of Xiamen university, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Congting","family":"Ye","sequence":"additional","affiliation":[{"name":"Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian 361102, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenbin","family":"Ye","sequence":"additional","affiliation":[{"name":"Department of Automation, Xiamen University, Xiamen 361005, China"},{"name":"Xiamen Research Institute of National Center of Healthcare Big Data, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaru","family":"Su","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaohui","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Automation, Xiamen University, Xiamen 361005, China"},{"name":"Xiamen Research Institute of National Center of Healthcare Big Data, Xiamen 361005, 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