과제정보
This work is based the Master's degree thesis of SMY at Soongsil University, Seoul, Korea. We acknowledge the financial support from the Soongsil University Research Fund. The computational resources were kindly provided by Korea Institute of Science and Technology Information (GSDC & KREONET).
참고문헌
- Wang Y, Navin NE. Advances and applications of single-cell sequencing technologies. Mol Cell 2015;58:598-609. https://doi.org/10.1016/j.molcel.2015.05.005
- Svensson V, Vento-Tormo R, Teichmann SA. Exponential scaling of single-cell RNA-seq in the past decade. Nat Protoc 2018; 13:599-604. https://doi.org/10.1038/nprot.2017.149
- Zheng GX, Terry JM, Belgrader P, Ryvkin P, Bent ZW, Wilson R, et al. Massively parallel digital transcriptional profiling of single cells. Nat Commun 2017;8:14049. https://doi.org/10.1038/ncomms14049
- Azizi E, Carr AJ, Plitas G, Cornish AE, Konopacki C, Prabhakaran S, et al. Single-cell map of diverse immune phenotypes in the breast tumor microenvironment. Cell 2018;174:1293-1308. https://doi.org/10.1016/j.cell.2018.05.060
- Schelker M, Feau S, Du J, Ranu N, Klipp E, MacBeath G, et al. Estimation of immune cell content in tumour tissue using single-cell RNA-seq data. Nat Commun 2017;8:2032. https://doi.org/10.1038/s41467-017-02289-3
- Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H, et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 2014;344:1396-1401. https://doi.org/10.1126/science.1254257
- Aran D, Looney AP, Liu L, Wu E, Fong V, Hsu A, et al. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nat Immunol 2019;20:163-172. https://doi.org/10.1038/s41590-018-0276-y
- Pliner HA, Shendure J, Trapnell C. Supervised classification enables rapid annotation of cell atlases. Nat Methods 2019;16:983-986. https://doi.org/10.1038/s41592-019-0535-3
- Skelly DA, Squiers GT, McLellan MA, Bolisetty MT, Robson P, Rosenthal NA, et al. Single-cell transcriptional profiling reveals cellular diversity and intercommunication in the mouse heart. Cell Rep 2018;22:600-610. https://doi.org/10.1016/j.celrep.2017.12.072
- Haber AL, Biton M, Rogel N, Herbst RH, Shekhar K, Smillie C, et al. A single-cell survey of the small intestinal epithelium. Nature 2017;551:333-339. https://doi.org/10.1038/nature24489
- Butler A, Hoffman P, Smibert P, Papalexi E, Satija R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat Biotechnol 2018;36:411-420. https://doi.org/10.1038/nbt.4096
- Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 2008;9:559. https://doi.org/10.1186/1471-2105-9-559
- Janky R, Verfaillie A, Imrichova H, Van de Sande B, Standaert L, Christiaens V, et al. iRegulon: from a gene list to a gene regulatory network using large motif and track collections. PLoS Comput Biol 2014;10:e1003731. https://doi.org/10.1371/journal.pcbi.1003731
- Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 2013;29:15-21. https://doi.org/10.1093/bioinformatics/bts635
- Tarca AL, Draghici S, Bhatti G, Romero R. Down-weighting overlapping genes improves gene set analysis. BMC Bioinformatics 2012;13:136. https://doi.org/10.1186/1471-2105-13-136
- Jackson SH, Yu CR, Mahdi RM, Ebong S, Egwuagu CE. Dendritic cell maturation requires STAT1 and is under feedback regulation by suppressors of cytokine signaling. J Immunol 2004;172:2307-2315. https://doi.org/10.4049/jimmunol.172.4.2307
- Bornstein C, Winter D, Barnett-Itzhaki Z, David E, Kadri S, Garber M, et al. A negative feedback loop of transcription factors specifies alternative dendritic cell chromatin States. Mol Cell 2014;56:749-762. https://doi.org/10.1016/j.molcel.2014.10.014
- Prabhakaran S, Azizi E, Carr A, Pe'er D. Dirichlet process mixture model for correcting technical variation in single-cell gene expression data. JMLR Workshop Conf Proc 2016;48:1070-1079.