PublisherDOIYearVolumeIssuePageTitleAuthor(s)Link
Genomics & Informatics10.5808/gi.2020.18.3.e262020183e26A semi-automatic cell type annotation method for single-cell RNA sequencing datasetWan Kim, Sung Min Yoon, Sangsoo Kimhttp://genominfo.org/upload/pdf/gi-2020-18-3-e26.pdf, http://genominfo.org/journal/view.php?doi=10.5808/GI.2020.18.3.e26, http://genominfo.org/upload/pdf/gi-2020-18-3-e26.pdf
Bioinformatics10.1093/bioinformatics/btab286202137Supplement_1i51-i58CALLR: a semi-supervised cell-type annotation method for single-cell RNA sequencing dataZiyang Wei, Shuqin Zhanghttp://academic.oup.com/bioinformatics/article-pdf/37/Supplement_1/i51/39620010/btab286.pdf, http://academic.oup.com/bioinformatics/article-pdf/37/Supplement_1/i51/39620010/btab286.pdf
Computational and Structural Biotechnology Journal10.1016/j.csbj.2021.10.0272021195874-5887Automatic cell type identification methods for single-cell RNA sequencingBingbing Xie, Qin Jiang, Antonio Mora, Xuri Lihttps://api.elsevier.com/content/article/PII:S2001037021004499?httpAccept=text/xml, https://api.elsevier.com/content/article/PII:S2001037021004499?httpAccept=text/plain
Bioinformatics10.1093/bioinformatics/btab8402021MACA: marker-based automatic cell-type annotation for single-cell expression dataYang Xu, Simon J Baumgart, Christian M Stegmann, Sikander Hayathttps://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btab840/41936202/btab840.pdf, https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btab840/41936202/btab840.pdf
Frontiers in Genetics10.3389/fgene.2020.00490202011SCSA: A Cell Type Annotation Tool for Single-Cell RNA-seq DataYinghao Cao, Xiaoyue Wang, Gongxin Penghttps://www.frontiersin.org/article/10.3389/fgene.2020.00490/full
Bioinformatics10.1093/bioinformatics/btaa669202037143-49netAE: semi-supervised dimensionality reduction of single-cell RNA sequencing to facilitate cell labelingZhengyang Dong, Gil Alterovitzhttp://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btaa669/34774523/btaa669.pdf, http://academic.oup.com/bioinformatics/article-pdf/37/1/43/37005968/btaa669.pdf, http://academic.oup.com/bioinformatics/article-pdf/37/1/43/37005968/btaa669.pdf
iScience10.1016/j.isci.2020.1008822020233100882scCATCH: Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing DataXin Shao, Jie Liao, Xiaoyan Lu, Rui Xue, Ni Ai, Xiaohui Fanhttps://api.elsevier.com/content/article/PII:S2589004220300663?httpAccept=text/xml, https://api.elsevier.com/content/article/PII:S2589004220300663?httpAccept=text/plain
BMC Bioinformatics10.1186/s12859-021-04469-x2021221Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversamplingSaptarshi Bej, Anne-Marie Galow, Robert David, Markus Wolfien, Olaf Wolkenhauerhttps://link.springer.com/content/pdf/10.1186/s12859-021-04469-x.pdf, https://link.springer.com/article/10.1186/s12859-021-04469-x/fulltext.html, https://link.springer.com/content/pdf/10.1186/s12859-021-04469-x.pdf
Advances in Experimental Medicine and Biology10.1007/978-981-13-6037-4_120191-17Strategies for Converting RNA to Amplifiable cDNA for Single-Cell RNA Sequencing MethodsYohei Sasagawa, Tetsutaro Hayashi, Itoshi Nikaidohttp://link.springer.com/content/pdf/10.1007/978-981-13-6037-4_1
10.21203/rs.3.rs-36926/v32020gCAnno: a graph-based single cell type annotation methodXiaofei Yang, Shenghan Gao, Tingjie Wang, Boyu Yang, Ningxin Dang, Kai Yehttps://www.researchsquare.com/article/rs-36926/v3, https://www.researchsquare.com/article/rs-36926/v3.html