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Currently, many analysis tools are available to better utilize these relatively noisy data. In this review, we summarize the most widely used methods for critical downstream analysis steps (i.e. clustering, trajectory inference, cell-type annotation and integrating datasets). The advantages and limitations are comprehensively discussed, and we provide suggestions for choosing proper methods in different situations. We hope this paper will be useful for scRNA-seq data analysts and bioinformatics tool developers.<\/jats:p>","DOI":"10.1093\/bib\/bbab105","type":"journal-article","created":{"date-parts":[[2021,3,10]],"date-time":"2021-03-10T12:12:00Z","timestamp":1615378320000},"source":"Crossref","is-referenced-by-count":64,"title":["Critical downstream analysis steps for single-cell RNA sequencing data"],"prefix":"10.1093","volume":"22","author":[{"given":"Zilong","family":"Zhang","sequence":"first","affiliation":[{"name":"University of Electronic Science and Technology of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feifei","family":"Cui","sequence":"additional","affiliation":[{"name":"University of Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Lin","sequence":"additional","affiliation":[{"name":"Fudan University in China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingling","family":"Zhao","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology in China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology in China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quan","family":"Zou","sequence":"additional","affiliation":[{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,4,5]]},"reference":[{"issue":"5","key":"2021090815525251900_ref1","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1038\/nmeth.1315","article-title":"mRNA-Seq whole-transcriptome analysis of a single cell","volume":"6","author":"Tang","year":"2009","journal-title":"Nat Methods"},{"issue":"8","key":"2021090815525251900_ref2","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1038\/s41581-018-0021-7","article-title":"Single-cell RNA sequencing for the study of development, physiology and disease","volume":"14","author":"Potter","year":"2018","journal-title":"Nat Rev Nephrol"},{"issue":"2","key":"2021090815525251900_ref3","doi-asserted-by":"crossref","first-page":"165","DOI":"10.2174\/1574893614666191017154427","article-title":"Comparative transcriptome profiling of disruptive technology, single-molecule direct RNA sequencing","volume":"15","author":"Pradeep","year":"2020","journal-title":"Curr Bioinforma"},{"issue":"6233","key":"2021090815525251900_ref4","doi-asserted-by":"crossref","first-page":"aaa6090","DOI":"10.1126\/science.aaa6090","article-title":"RNA imaging. 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