TY - STD TI - Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014; 15(12):550. http://genomebiology.com/2014/15/12/550. UR - http://genomebiology.com/2014/15/12/550 ID - ref1 ER - TY - STD TI - Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010; 26(1):139–40. http://www.ncbi.nlm.nih.gov/pubmed/19910308. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2796818. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2796818 ID - ref2 ER - TY - STD TI - Law CW, Chen Y, Shi W, Smyth GK. voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 2014; 15(2):R29. http://www.pubmedcentral.nih.gov/articlerender.fcgi%3Fartid=4053721%26tool=pmcentrez%26rendertype=abstract. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi%3Fartid=4053721%26tool=pmcentrez%26rendertype=abstract ID - ref3 ER - TY - STD TI - Wang Z, Gerstein M, Snyder M. RNA-seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009; 10(1):57–63. http://www.nature.com/doifinder/10.1038/nrg2484. UR - http://www.nature.com/doifinder/10.1038/nrg2484 ID - ref4 ER - TY - STD TI - Goodwin S, McPherson JD, McCombie WR. Coming of age: ten years of next-generation sequencing technologies. Nat Rev Genet. 2016; 17(6):333–51. http://www.nature.com/doifinder/10.1038/nrg.2016.49. UR - http://www.nature.com/doifinder/10.1038/nrg.2016.49 ID - ref5 ER - TY - STD TI - Lönnberg T, Svensson V, James KR, Fernandez-Ruiz D, Sebina I, Montandon R, et al. Single-cell RNA-seq and computational analysis using temporal mixture modelling resolves Th1/Tfh fate bifurcation in malaria. Sci Immunol. 2017; 2(9). http://www.ncbi.nlm.nih.gov/pubmed/28345074. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC5365145. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC5365145 ID - ref6 ER - TY - STD TI - Buettner F, Natarajan KN, Casale FP, Proserpio V, Scialdone A, Theis FJ, et al.Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nat Biotechnol. 2015; 33(2):155–60. http://www.ncbi.nlm.nih.gov/pubmed/25599176. http://www.nature.com/doifinder/10.1038/nbt.3102. UR - http://www.nature.com/doifinder/10.1038/nbt.3102 ID - ref7 ER - TY - STD TI - 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(6190). http://science.sciencemag.org/content/344/6190/1396. UR - http://science.sciencemag.org/content/344/6190/1396 ID - ref8 ER - TY - STD TI - Kolodziejczyk AA, Kim JK, Tsang JCH, Ilicic T, Henriksson J, Natarajan KN, et al. Single cell RNA-sequencing of pluripotent states unlocks modular transcriptional variation. Cell Stem Cell. 2015; 17(4):471–85. http://www.ncbi.nlm.nih.gov/pubmed/26431182. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4595712. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4595712 ID - ref9 ER - TY - STD TI - Li L, Dong J, Yan L, Yong J, Liu X, Hu Y, et al. Single-cell RNA-seq analysis maps development of human germline cells and gonadal niche interactions. Cell Stem Cell. 2017; 20(6):858–73.e4. http://www.ncbi.nlm.nih.gov/pubmed/28457750. http://linkinghub.elsevier.com/retrieve/pii/S1934590917300784. UR - http://linkinghub.elsevier.com/retrieve/pii/S1934590917300784 ID - ref10 ER - TY - STD TI - Usoskin D, Furlan A, Islam S, Abdo H, Lönnerberg P, Lou D, et al. Unbiased classification of sensory neuron types by large-scale single-cell RNA-sequencing. Nat Neurosci. 2014; 18(1):145–53. http://www.nature.com/doifinder/10.1038/nn.3881. UR - http://www.nature.com/doifinder/10.1038/nn.3881 ID - ref11 ER - TY - STD TI - Kolodziejczyk AA, Kim JK, Svensson V, Marioni JC, Teichmann SA. The technology and biology of single-cell RNA-sequencing. Mol Cell. 2015; 58(4):610–20. http://linkinghub.elsevier.com/retrieve/pii/S1097276515002610. UR - http://linkinghub.elsevier.com/retrieve/pii/S1097276515002610 ID - ref12 ER - TY - STD TI - Nakamura T, Yabuta Y, Okamoto I, Aramaki S, Yokobayashi S, Kurimoto K, et al. SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression. Nucleic Acids Res. 2015; 43(9):e60. https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkv134. UR - https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkv134 ID - ref13 ER - TY - STD TI - Wu AR, Neff NF, Kalisky T, Dalerba P, Treutlein B, Rothenberg ME, et al. Quantitative assessment of single-cell RNA-sequencing methods. Nat Methods. 2013; 11(1):41–6. http://www.ncbi.nlm.nih.gov/pubmed/24141493. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4022966. http://www.nature.com/doifinder/10.1038/nmeth.2694. UR - http://www.nature.com/doifinder/10.1038/nmeth.2694 ID - ref14 ER - TY - STD TI - Islam S, Zeisel A, Joost S, La Manno G, Zajac P, Kasper M, et al. Quantitative single-cell RNA-seq with unique molecular identifiers. Nat Methods. 2013; 11(2):163–6. http://www.ncbi.nlm.nih.gov/pubmed/24363023. http://www.nature.com/doifinder/10.1038/nmeth.2772. UR - http://www.nature.com/doifinder/10.1038/nmeth.2772 ID - ref15 ER - TY - STD TI - Islam S, Kjällquist U, Moliner A, Zajac P, Fan JB, Lönnerberg P, et al. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. Genome Res. 2011; 21(7):1160–7. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3129258%26tool=pmcentrez%26rendertype=abstract. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3129258%26tool=pmcentrez%26rendertype=abstract ID - ref16 ER - TY - STD TI - Picelli S, Faridani OR, Björklund ÅK, Winberg G, Sagasser S, Sandberg R. Full-length RNA-seq from single cells using Smart-Seq2. Nat Protoc. 2014; 9(1):171–81. http://www.ncbi.nlm.nih.gov/pubmed/24385147. http://www.nature.com/doifinder/10.1038/nprot.2014.006. UR - http://www.nature.com/doifinder/10.1038/nprot.2014.006 ID - ref17 ER - TY - STD TI - Hashimshony T, Senderovich N, Avital G, Klochendler A, de Leeuw Y, Anavy L, et al. CEL-Seq2: sensitive highly-multiplexed single-cell RNA-seq. Genome Biol. 2016; 17:77. http://www.ncbi.nlm.nih.gov/pubmed/27121950. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4848782. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4848782 ID - ref18 ER - TY - STD TI - Finak G, McDavid A, Yajima M, Deng J, Gersuk V, Shalek AK, et al. MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA-sequencing data. Genome Biol. 2015; 16(1):278. http://genomebiology.com/2015/16/1/278. UR - http://genomebiology.com/2015/16/1/278 ID - ref19 ER - TY - STD TI - Raj A, van Oudenaarden A. Nature, nurture, or chance: stochastic gene expression and its consequences. Cell. 2008; 135(2):216–26. http://www.ncbi.nlm.nih.gov/pubmed/18957198. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3118044. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3118044 ID - ref20 ER - TY - STD TI - Raj A, Peskin CS, Tranchina D, Vargas DY, Tyagi S. Stochastic mRNA synthesis in mammalian cells. PLoS Biol. 2006; 4(10):e309. http://www.ncbi.nlm.nih.gov/pubmed/17048983. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC1563489. http://dx.plos.org/10.1371/journal.pbio.0040309. UR - http://dx.plos.org/10.1371/journal.pbio.0040309 ID - ref21 ER - TY - STD TI - Pierson E, Yau C. ZIFA: dimensionality reduction for zero-inflated single-cell gene expression analysis. Genome Biol. 2015; 16(1):241. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0805-z. UR - https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0805-z ID - ref22 ER - TY - STD TI - Risso D, Perraudeau F, Gribkova S, Dudoit S, Vert JP. A general and flexible method for signal extraction from single-cell RNA-seq data. Nat Commun. 2018; 9(1):284. http://www.nature.com/articles/s41467-017-02554-5. UR - http://www.nature.com/articles/s41467-017-02554-5 ID - ref23 ER - TY - STD TI - Setty M, Tadmor MD, Reich-Zeliger S, Angel O, Salame TM, Kathail P, et al.Wishbone identifies bifurcating developmental trajectories from single-cell data. Nat Biotechnol. 2016; 34(6):637–45. http://www.ncbi.nlm.nih.gov/pubmed/27136076. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4900897. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4900897 ID - ref24 ER - TY - STD TI - Qiu X, Mao Q, Tang Y, Wang L, Chawla R, Pliner HA, et al. Reversed graph embedding resolves complex single-cell trajectories. Nat Methods. 2017. https://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.4402.html. UR - https://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.4402.html ID - ref25 ER - TY - STD TI - Street K, Risso D, Fletcher RB, Das D, Ngai J, Yosef N, et al. Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics. 2017:128843. http://www.biorxiv.org/content/early/2017/04/19/128843. UR - http://www.biorxiv.org/content/early/2017/04/19/128843 ID - ref26 ER - TY - STD TI - Lun ATL, McCarthy DJ, Marioni JC. A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor. F1000Research. 2016; 5:2122. https://f1000research.com/articles/5-2122/v2. UR - https://f1000research.com/articles/5-2122/v2 ID - ref27 ER - TY - STD TI - Kharchenko PV, Silberstein L, Scadden DT. Bayesian approach to single-cell differential expression analysis. Nat Methods. 2014; 11(7):740–2. http://www.ncbi.nlm.nih.gov/pubmed/24836921. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4112276. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4112276 ID - ref28 ER - TY - STD TI - Jaakkola MK, Seyednasrollah F, Mehmood A, Elo LL. Comparison of methods to detect differentially expressed genes between single-cell populations. Brief Bioinform. 2016:bbw057. http://www.ncbi.nlm.nih.gov/pubmed/27373736. http://bib.oxfordjournals.org/lookup/doi/10.1093/bib/bbw057. UR - http://bib.oxfordjournals.org/lookup/doi/10.1093/bib/bbw057 ID - ref29 ER - TY - STD TI - Soneson C, Robinson MD. Bias, robustness and scalability in differential expression analysis of single-cell RNA-seq data. 2017. http://biorxiv.org/content/early/2017/05/28/143289. UR - http://biorxiv.org/content/early/2017/05/28/143289 ID - ref30 ER - TY - STD TI - McCarthy DJ, Chen Y, Smyth GK. Differential expression analysis of multifactor RNA-seq experiments with respect to biological variation. Nucleic Acids Res. 2012; 40(10):4288–97. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3378882%26tool=pmcentrez%26rendertype=abstract. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3378882%26tool=pmcentrez%26rendertype=abstract ID - ref31 ER - TY - CHAP AU - Colin Cameron, A. AU - Trivedi, P. K. PY - 2013 DA - 2013// TI - Zero-Inflated Count Models BT - Regression Analysis of Count Data. 2nd ed PB - Cambridge University Press CY - Cambridge UR - https://doi.org/10.1017/CBO9781139013567 DO - 10.1017/CBO9781139013567 ID - Colin Cameron2013 ER - TY - STD TI - Gagnon-Bartsch Ja, Speed TP. Using control genes to correct for unwanted variation in microarray data. Biostatistics. 2012; 13(3):539–52. http://www.ncbi.nlm.nih.gov/pubmed/22101192. UR - http://www.ncbi.nlm.nih.gov/pubmed/22101192 ID - ref33 ER - TY - STD TI - Risso D, Ngai J, Speed TP, Dudoit S. Normalization of RNA-seq data using factor analysis of control genes or samples. Nat Biotech. 2014; 32(9):896–902. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4404308%26tool=pmcentrez%26rendertype=abstract. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4404308%26tool=pmcentrez%26rendertype=abstract ID - ref34 ER - TY - STD TI - Islam S, Kjällquist U, Moliner A, Zajac P, Fan JB, Lönnerberg P, et al. Data sets: characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. 2011. Gene expression Omnibus, accession GSE29087. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29087. UR - https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29087 ID - ref35 ER - TY - STD TI - Trapnell C, Cacchiarelli D, Grimsby J, Pokharel P, Li S, Morse M, et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol. 2014; 32(4):381–6. http://www.ncbi.nlm.nih.gov/pubmed/24658644. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4122333. http://www.nature.com/articles/nbt.2859. UR - http://www.nature.com/articles/nbt.2859 ID - ref36 ER - TY - STD TI - Soneson C, Robinson MD. Towards unified quality verification of synthetic count data with countsimQC. Bioinformatics. 2017. http://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btx631/4345646/Towards-unified-quality-verification-of-synthetic. UR - http://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btx631/4345646/Towards-unified-quality-verification-of-synthetic ID - ref37 ER - TY - STD TI - Hicks SC, Teng M, Irizarry RA. On the widespread and critical impact of systematic bias and batch effects in single-cell RNA-seq data. 2015. http://biorxiv.org/content/early/2015/12/27/025528. UR - http://biorxiv.org/content/early/2015/12/27/025528 ID - ref38 ER - TY - STD TI - Butler A, Satija R. Integrated analysis of single cell transcriptomic data across conditions, technologies, and species. 2017:164889. https://www.biorxiv.org/content/early/2017/07/18/164889. UR - https://www.biorxiv.org/content/early/2017/07/18/164889 ID - ref39 ER - TY - STD TI - Sergushichev A. An algorithm for fast preranked gene set enrichment analysis using cumulative statistic calculation. 2016:060012. https://www.biorxiv.org/content/early/2016/06/20/060012. UR - https://www.biorxiv.org/content/early/2016/06/20/060012 ID - ref40 ER - TY - STD TI - Aran D, Hu Z, Butte AJ. xCell: digitally portraying the tissue cellular heterogeneity landscape. 2017:114165. https://www.biorxiv.org/content/early/2017/06/15/114165. UR - https://www.biorxiv.org/content/early/2017/06/15/114165 ID - ref41 ER - TY - STD TI - Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol. 1995; 57(1):289–300. https://www.jstor.org/stable/2346101?seq=1%23page_scan_tab_contents. UR - https://www.jstor.org/stable/2346101?seq=1%23page_scan_tab_contents ID - ref42 ER - TY - STD TI - Van den Berge K, Soneson C, Love MI, Robinson MD, Clement L. zingeR: unlocking RNA-seq tools for zero-inflation and single cell applications. 2017:157982. https://www.biorxiv.org/content/early/2017/06/30/157982. UR - https://www.biorxiv.org/content/early/2017/06/30/157982 ID - ref43 ER - TY - STD TI - Grün D, Kester L, van Oudenaarden A. Validation of noise models for single-cell transcriptomics. Nat Methods. 2014; 11(6):637–40. http://www.ncbi.nlm.nih.gov/pubmed/24747814. http://www.nature.com/doifinder/10.1038/nmeth.2930. UR - http://www.nature.com/doifinder/10.1038/nmeth.2930 ID - ref44 ER - TY - STD TI - Ziegenhain C, Vieth B, Parekh S, Reinius B, Guillaumet-Adkins A, Smets M, et al. Comparative analysis of single-cell RNA-sequencing methods. Mol Cell. 2017; 65(4):631–43. http://linkinghub.elsevier.com/retrieve/pii/S1097276517300497. UR - http://linkinghub.elsevier.com/retrieve/pii/S1097276517300497 ID - ref45 ER - TY - STD TI - Pal B, Chen Y, Vaillant F, Jamieson P, Gordon L, Rios AC, et al. Construction of developmental lineage relationships in the mouse mammary gland by single-cell RNA profiling. Nat Commun. 2017; 8(1):1627. http://www.nature.com/articles/s41467-017-01560-x. UR - http://www.nature.com/articles/s41467-017-01560-x ID - ref46 ER - TY - STD TI - Fujita K, Iwaki M, Yanagida T. Transcriptional bursting is intrinsically caused by interplay between RNA polymerases on DNA. Nat Commun. 2016; 7:13788. http://www.nature.com/doifinder/10.1038/ncomms13788. UR - http://www.nature.com/doifinder/10.1038/ncomms13788 ID - ref47 ER - TY - STD TI - Paulson JN, Stine OC, Bravo HC, Pop M. Differential abundance analysis for microbial marker-gene surveys. Nat Methods. 2013; 10(12):1200–2. http://www.ncbi.nlm.nih.gov/pubmed/24076764. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4010126. http://www.nature.com/doifinder/10.1038/nmeth.2658. http://dx.doi.org/10.1038/nmeth.2658. UR - http://dx.doi.org/10.1038/nmeth.2658 ID - ref48 ER - TY - STD TI - Xu L, Paterson AD, Turpin W, Xu W. Assessment and selection of competing models for zero-inflated microbiome data. PLoS ONE. 2015; 10(7):e0129606. http://www.ncbi.nlm.nih.gov/pubmed/26148172. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4493133. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4493133 ID - ref49 ER - TY - STD TI - McCarthy DJ, Chen Y, Smyth GK. Differential expression analysis of multifactor RNA-seq experiments with respect to biological variation. Nucleic Acids Res. 2012; 40(10):4288–97. http://www.ncbi.nlm.nih.gov/pubmed/22287627. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3378882. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3378882 ID - ref50 ER - TY - STD TI - Vallejos CA, Risso D, Scialdone A, Dudoit S, Marioni JC. Normalizing single-cell RNA-sequencing data: challenges and opportunities. Nat Methods. 2017; 14(6):565–71. https://doi.org/10.1038/nmeth.4292. http://www.nature.com/doifinder/10.1038/nmeth.4292. UR - http://www.nature.com/doifinder/10.1038/nmeth.4292 ID - ref51 ER - TY - STD TI - McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE. 2013; 8(4):e61217. http://dx.plos.org/10.1371/journal.pone.0061217. UR - http://dx.plos.org/10.1371/journal.pone.0061217 ID - ref52 ER - TY - STD TI - Bourgon R, Gentleman R, Huber W. Independent filtering increases detection power for high-throughput experiments. Proc Natl Acad Sci. 2010; 107(21):9546–51. http://www.ncbi.nlm.nih.gov/pubmed/20460310. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2906865. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2906865 ID - ref53 ER - TY - STD TI - Soneson C, Robinson MD. iCOBRA: open, reproducible, standardized and live method benchmarking. Nat Methods. 2016; 13(4):283. http://www.nature.com/doifinder/10.1038/nmeth.3805. UR - http://www.nature.com/doifinder/10.1038/nmeth.3805 ID - ref54 ER - TY - STD TI - Sengupta D, Rayan NA, Lim M, Lim B, Prabhakar S. Fast, scalable and accurate differential expression analysis for single cells. bioRxiv. 2016:049734. https://doi.org/10.1101/049734. https://www.biorxiv.org/content/early/2016/04/22/049734. Cold Spring Harbor Laboratory. UR - https://www.biorxiv.org/content/early/2016/04/22/049734 ID - ref55 ER - TY - STD TI - van de Wiel MA, Neerincx M, Buffart TE, Sie D, Verheul HM. ShrinkBayes: a versatile R package for analysis of count-based sequencing data in complex study designs. BMC Bioinform. 2014; 15(1):116. http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-116. UR - http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-116 ID - ref56 ER - TY - STD TI - Zhou X, Lindsay H, Robinson MD. Robustly detecting differential expression in RNA-sequencing data using observation weights. Nucleic Acids Res. 2014; 42(11):e91. http://www.ncbi.nlm.nih.gov/pubmed/24753412. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4066750. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4066750 ID - ref57 ER - TY - STD TI - Moore DF. Asymptotic properties of moment estimators for overdispersed counts and proportions. Biometrika. 1986; 73(3):583. http://www.jstor.org/stable/2336522?origin=crossref. UR - http://www.jstor.org/stable/2336522?origin=crossref ID - ref58 ER - TY - STD TI - McCullagh PP, Nelder JA. Generalized linear models. 2nd ed. New York: Chapman and Hall; 1989. https://www.crcpress.com/Generalized-Linear-Models-Second-Edition/McCullagh-Nelder/p/book/9780412317606. UR - https://www.crcpress.com/Generalized-Linear-Models-Second-Edition/McCullagh-Nelder/p/book/9780412317606 ID - ref59 ER - TY - STD TI - Wood SN. Thin plate regression splines. J R Stat Soc Ser B Stat Methodol. 2003; 65(1):95–114. http://doi.wiley.com/10.1111/1467-9868.00374. UR - http://doi.wiley.com/10.1111/1467-9868.00374 ID - ref60 ER - TY - STD TI - Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci. 2005; 102(43):15545–50. http://www.pnas.org/cgi/doi/10.1073/pnas.0506580102. UR - http://www.pnas.org/cgi/doi/10.1073/pnas.0506580102 ID - ref61 ER - TY - STD TI - Zheng GXY, 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. http://www.nature.com/doifinder/10.1038/ncomms14049. UR - http://www.nature.com/doifinder/10.1038/ncomms14049 ID - ref62 ER - TY - STD TI - Trapnell C, Cacchiarelli D, Grimsby J, Pokharel P, Li S, Morse M, et al. Data sets: the dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. 2014. Gene expression Omnibus, accession GSE52529. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE52529. UR - https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE52529 ID - ref63 ER - TY - STD TI - Usoskin D, Furlan A, Islam S, Abdo H, Lönnerberg P, Lou D, et al. Data sets: unbiased classification of sensory neuron types by large-scale single-cell RNA-sequencing. 2014. Linnarsson Lab Website. http://linnarssonlab.org/drg/. UR - http://linnarssonlab.org/drg/ ID - ref64 ER - TY - STD TI - Zheng GXY, Terry JM, Belgrader P, Ryvkin P, Bent ZW, Wilson R, et al. Data sets: massively parallel digital transcriptional profiling of single cells. 2017. Short Read Archive, accession SRP073767. https://www.ncbi.nlm.nih.gov/sra?term=SRP073767. UR - https://www.ncbi.nlm.nih.gov/sra?term=SRP073767 ID - ref65 ER - TY - STD TI - Deng Q, Ramsköld D, Reinius B, Sandberg R. Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science. 2014; 343(6167):193–6. http://www.ncbi.nlm.nih.gov/pubmed/24408435. UR - http://www.ncbi.nlm.nih.gov/pubmed/24408435 ID - ref66 ER - TY - STD TI - Bottomly D, Walter NAR, Hunter JE, Darakjian P, Kawane S, Buck KJ, et al. Evaluating gene expression in C57BL/6J and DBA/2J mouse striatum using RNA-seq and microarrays. PLoS ONE. 2011; 6(3):e17820. http://www.pubmedcentral.nih.gov/articlerender.fcgi%3Fartid=3063777%26tool=pmcentrez%26rendertype=abstract. UR - http://www.pubmedcentral.nih.gov/articlerender.fcgi%3Fartid=3063777%26tool=pmcentrez%26rendertype=abstract ID - ref67 ER -