SCENIC: single-cell regulatory network inference and clustering

[en] We present SCENIC, a computational method for simultaneous gene regulatory network reconstruction and cell-state identification from single-cell RNA-seq data (http://scenic.aertslab.org). On a compendium of single-cell data from tumors and brain, we demonstrate that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity.

Disciplines :

Computer science
Biochemistry, biophysics & molecular biology

Author, co-author :

Aibar, Sara; Katholieke Universiteit Leuven - KUL > Department of Human Genetics

González-Blas, Carmen Bravo; Katholieke Universiteit Leuven - KUL > Department of Human Genetics

Moerman, Thomas; Katholieke Universiteit Leuven - KUL

Huynh-Thu, Vân Anh ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Algorith. des syst. en interaction avec le monde physique

Imrichova, Hana; Katholieke Universiteit Leuven - KUL > Department of Human Genetics

Hulselmans, Gert; Katholieke Universiteit Leuven - KUL > Department of Human Genetics

Rambow, Florian; Katholieke Universiteit Leuven - KUL > Department of Oncology

Marine, Jean-Christophe; Katholieke Universiteit Leuven - KUL > Department of Oncology

Geurts, Pierre ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Algorith. des syst. en interaction avec le monde physique

Aerts, Jan; Katholieke Universiteit Leuven - KUL

More authors (4 more)

Language :

English

Title :

SCENIC: single-cell regulatory network inference and clustering

Publication date :

09 October 2017

Journal title :

Nature Methods

ISSN :

1548-7091

eISSN :

1548-7105

Publisher :

Nature Publishing Group

Volume :

Pages :

1083–1086

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 17 November 2017

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Bibliography

Linnarsson, S. & Teichmann, S.A. Genome Biol. 17, 97 (2016).
Wagner, A., Regev, A. & Yosef, N. Nat. Biotechnol. 34, 1145-1160 (2016).
Stegle, O., Teichmann, S.A. & Marioni, J.C. Nat. Rev. Genet. 16, 133-145 (2015).
Raj, A. & van Oudenaarden, A. Cell 135, 216-226 (2008).
Moignard, V. et al. Nat. Biotechnol. 33, 269-276 (2015).
Pina, C. et al. Cell Rep. 11, 1503-1510 (2015).
Guo, M., Wang, H., Potter, S.S., Whitsett, J.A. & Xu, Y. PLoS Comput. Biol. 11, e1004575 (2015).
Huynh-Thu, V.A., Irrthum, A., Wehenkel, L. & Geurts, P. PLoS One 5, e12776 (2010).
Zeisel, A. et al. Science 347, 1138-1142 (2015).
Kiselev, V.Y. et al. Nat. Methods 14, 483-486 (2017).
Lake, B.B. et al. Science 352, 1586-1590 (2016).
Darmanis, S. et al. Proc. Natl. Acad. Sci. USA 112, 7285-7290 (2015).
Tirosh, I. et al. Nature 539, 309-313 (2016).
Tirosh, I. et al. Science 352, 189-196 (2016).
Alizadeh, A.A. et al. Nat. Med. 21, 846-853 (2015).
Johnson, W.E., Li, C. & Rabinovic, A. Biostatistics 8, 118-127 (2007).
Ritchie, M.E. et al. Nucleic Acids Res. 43, e47 (2015).
Perotti, V. et al. Oncogene 35, 2862-2872 (2016).
Chang, C.-Y. et al. Nature 495, 98-102 (2013).
Denny, S.K. et al. Cell 166, 328-342 (2016).
Müller, M.R. & Rao, A. Nat. Rev. Immunol. 10, 645-656 (2010).
Regev, A. et al. bioRxiv Preprint at: http://www.biorxiv.org/content/ early/2017/05/08/121202 (2017).
Zaharia, M. et al. In Proc. of the 9th USENIX Conference on Networked Systems Design and Implementation 2-2 (USENIX Association, 2012).
Marbach, D. et al. Nat. Methods 9, 796-804 (2012).
Islam, S. et al. Nat. Methods 11, 163-166 (2014).
Crow, M., Paul, A., Ballouz, S., Huang, Z.J. & Gillis, J. Genome Biol. 17, 101 (2016).
Lun, A.T.L., McCarthy, D.J. & Marioni, J.C. F1000Res. 5, 2122 (2016).
Friedman, J.H. Ann. Stat. 29, 1189-1232 (2001).
Chen, T. & Guestrin, C. In Proc.of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 785-794 (ACM, 2016).
Freund, Y. & Schapire, R.E. Jinko Chino Gakkaishi 14, 771-780 (1999).
S?awek, J. & Arodz, T. BMC Syst. Biol. 7, 106 (2013).
Dean, J. & Ghemawat, S. Commun. ACM 51, 107-113 (2008).
Aerts, S. et al. PLoS Biol. 8, e1000435 (2010).
Herrmann, C., Van de Sande, B., Potier, D. & Aerts, S. Nucleic Acids Res. 40, e114 (2012).
Janky, R. et al. PLoS Comput. Biol. 10, e1003731 (2014).
Krijthe, J. Rtsne: t-distributed stochastic neighbor embedding using Barnes-Hut implementation https://github.com/jkrijthe/Rtsne (2015).
Marques, S. et al. Science 352, 1326-1329 (2016).
Macosko, E.Z. et al. Cell 161, 1202-1214 (2015).
Durinck, S. et al. Bioinformatics 21, 3439-3440 (2005).
Warde-Farley, D. et al. Nucleic Acids Res. 38, W214-W220 (2010).
Leek, J. sva: Surrogate Variable Analysis. R package version 3.24.4 (2017).
Smyth, G. limma: Linear models for microarray data. (2015).
Forbes, S.A. et al. Nucleic Acids Res. 45, D777-D783 (2017).
Edgar, R., Domrachev, M. & Lash, A.E. Nucleic Acids Res. 30, 207-210 (2002).