Comprehensive Integration of Single-Cell Data

Achim, 2015, High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin, Nat. Biotechnol., 33, 503, 10.1038/nbt.3209

Alemany, 2018, Whole-organism clone tracing using single-cell sequencing, Nature, 556, 108, 10.1038/nature25969

Allen Institute. 2018. Allen Brain Data Portal. http://celltypes.brain-map.org/api/v2/well_known_file_download/694413985.

Arya, S., Mount, D., Kemp, S.E., and Jefferis, G. (2018). RANN: Fast Nearest Neighbour Search (Wraps ANN Library) Using L2 Metric. https://cran.r-project.org/web/packages/RANN/index.html.

Baglama, J., Reichel, L., and Lewis, B.W. 2018. irlba: Fast Truncated Singular Value Decomposition and Principal Components Analysis for Large Dense and Sparse Matrices. https://cran.r-project.org/web/packages/irlba/index.html.

Baron, 2016, A Single-Cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure, Cell Syst., 3, 346, 10.1016/j.cels.2016.08.011

Benaglia, 2009, mixtools: An R Package for Analyzing Finite Mixture Models, J. Stat. Softw., 32, 1

Bendall, 2014, Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development, Cell, 157, 714, 10.1016/j.cell.2014.04.005

Blitzer, 2006, Domain adaptation with structural correspondence learning. Proc. Conf. Empir, Methods Nat. Lang. Process., 120

Butler, 2018, Integrating single-cell transcriptomic data across different conditions, technologies, and species, Nat. Biotechnol., 36, 411, 10.1038/nbt.4096

Büttner, 2017, Assessment of batch-correction methods for scRNA-seq data with a new test metric, bioRxiv

Cao, 2018, Joint profiling of chromatin accessibility and gene expression in thousands of single cells, Science, 361, 1380, 10.1126/science.aau0730

Codeluppi, 2018, Spatial organization of the somatosensory cortex revealed by osmFISH, Nat. Methods, 15, 932, 10.1038/s41592-018-0175-z

Corces, 2016, Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution, Nat. Genet., 48, 1193, 10.1038/ng.3646

Cusanovich, 2018, A Single-Cell atlas of in vivo mammalian chromatin accessibility, Cell, 174, 1309, 10.1016/j.cell.2018.06.052

de Bruin, 2014, Impact of interferon-γ on hematopoiesis, Blood, 124, 2479, 10.1182/blood-2014-04-568451

Dixit, 2016, Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens, Cell, 167, 1853, 10.1016/j.cell.2016.11.038

Dobin, 2013, STAR: ultrafast universal RNA-seq aligner, Bioinformatics, 29, 15, 10.1093/bioinformatics/bts635

Dudoit, 2002, Comparison of discrimination methods for the classification of tumors using gene expression data, J. Am. Stat. Assoc., 97, 77, 10.1198/016214502753479248

Falcon, 2007, Using GOstats to test gene lists for GO term association, Bioinformatics, 23, 257, 10.1093/bioinformatics/btl567

Feng, 1987, Progressive sequence alignment as a prerequisite to correct phylogenetic trees, J. Mol. Evol., 25, 351, 10.1007/BF02603120

Goltsev, 2018, Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging, Cell, 174, 968, 10.1016/j.cell.2018.07.010

Grün, 2016, De novo prediction of stem cell identity using Single-Cell transcriptome data, Cell Stem Cell, 19, 266, 10.1016/j.stem.2016.05.010

Hafemeister, 2019, Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression, bioRxiv

Haghverdi, 2018, Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors, Nat. Biotechnol., 36, 421, 10.1038/nbt.4091

Hahne, 2016, 335

Halpern, 2017, Single-cell spatial reconstruction reveals global division of labour in the mammalian liver, Nature, 542, 352, 10.1038/nature21065

Heinz, 2010, Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities, Mol. Cell, 38, 576, 10.1016/j.molcel.2010.05.004

Hie, 2019, Efficient integration of heterogeneous single-cell transcriptomes using Scanorama, Nat. Biotechnol., 10.1038/s41587-019-0113-3

Karaiskos, 2017, The Drosophila embryo at single-cell transcriptome resolution, Science, 358, 194, 10.1126/science.aan3235

Kelsey, 2017, Single-cell epigenomics: Recording the past and predicting the future, Science, 358, 69, 10.1126/science.aan6826

Keren, 2018, A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging, Cell, 174, 1373, 10.1016/j.cell.2018.08.039

Kiselev, 2018, scmap: projection of single-cell RNA-seq data across data sets, Nat. Methods, 15, 359, 10.1038/nmeth.4644

Lake, 2018, Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain, Nat. Biotechnol., 36, 70, 10.1038/nbt.4038

Langfelder, 2008, WGCNA: an R package for weighted correlation network analysis, BMC Bioinformatics, 9, 559, 10.1186/1471-2105-9-559

Langmead, 2009, Ultrafast and memory-efficient alignment of short DNA sequences to the human genome, Genome Biol., 10, R25, 10.1186/gb-2009-10-3-r25

Lara-Astiaso, 2014, Immunogenetics. Chromatin state dynamics during blood formation, Science, 345, 943, 10.1126/science.1256271

Lawlor, 2017, Single-cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes, Genome Res., 27, 208, 10.1101/gr.212720.116

Levine, 2015, Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis, Cell, 162, 184, 10.1016/j.cell.2015.05.047

Li, 2009, The Sequence Alignment/Map format and SAMtools, Bioinformatics, 25, 2078, 10.1093/bioinformatics/btp352

Li, 2010, De novo assembly of human genomes with massively parallel short read sequencing, Genome Res., 20, 265, 10.1101/gr.097261.109

Li, B., Kowalczyk, M.S., Dionne, K., Ashenberg, O., Tabaka, M., Tickle, T., Lee, J., Shekhar, K., Slyper, M., Waldman, J., et al. 2018. Census of Immune Cells. https://preview.data.humancellatlas.org.

Linnarsson, S. 2018. Data and code availability.http://linnarssonlab.org/osmFISH/availability.

Lopez, 2018, Deep generative modeling for single-cell transcriptomics, Nat. Methods, 15, 1053, 10.1038/s41592-018-0229-2

Love, 2014, Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2, Genome Biol., 15, 550, 10.1186/s13059-014-0550-8

Lun, 2016, A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor, F1000Res., 5, 2122

Luo, 2018, Robust single-cell DNA methylome profiling with snmC-seq2, Nat. Commun., 9, 3824, 10.1038/s41467-018-06355-2

Mayer, 2018, Developmental diversification of cortical inhibitory interneurons, Nature, 555, 457, 10.1038/nature25999

Moffitt, 2018, Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region, Science, 362, 5324, 10.1126/science.aau5324

Mount, D.M., and Arya, S. (2010). ANN: A Library for Approximate Nearest Neighbor Searching. http://www.cs.umd.edu/∼mount/ANN/.

Muraro, 2016, A Single-Cell transcriptome atlas of the human pancreas, Cell Syst., 3, 385, 10.1016/j.cels.2016.09.002

Nagano, 2013, Single-cell Hi-C reveals cell-to-cell variability in chromosome structure, Nature, 502, 59, 10.1038/nature12593

Navin, 2011, Tumour evolution inferred by single-cell sequencing, Nature, 472, 90, 10.1038/nature09807

Ntranos, 2019, A discriminative learning approach to differential expression analysis for single-cell RNA-seq, Nat. Methods, 16, 163, 10.1038/s41592-018-0303-9

Okhrimenko, 2014, Human memory T cells from the bone marrow are resting and maintain long-lasting systemic memory, Proc. Natl. Acad. Sci. USA, 111, 9229, 10.1073/pnas.1318731111

Paradis, 2004, APE: Analyses of phylogenetics and evolution in R language, Bioinformatics, 20, 289, 10.1093/bioinformatics/btg412

Peterson, 2017, Multiplexed quantification of proteins and transcripts in single cells, Nat. Biotechnol., 35, 936, 10.1038/nbt.3973

Pliner, 2018, Cicero predicts cis-regulatory DNA interactions from Single-Cell chromatin accessibility data, Mol. Cell, 71, 858, 10.1016/j.molcel.2018.06.044

Preissl, 2018, Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation, Nat. Neurosci., 21, 432, 10.1038/s41593-018-0079-3

Qiu, 2017, Reversed graph embedding resolves complex single-cell trajectories, Nat. Methods, 14, 979, 10.1038/nmeth.4402

Quinlan, 2010, BEDTools: a flexible suite of utilities for comparing genomic features, Bioinformatics, 26, 841, 10.1093/bioinformatics/btq033

Raina, 2007, Self-taught Learning: Transfer Learning from Unlabeled Data. Proc. Int. Conf, Mach. Learn, 759

Raj, 2018, Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain, Nat. Biotechnol., 36, 442, 10.1038/nbt.4103

Ramani, 2017, Massively multiplex single-cell Hi-C, Nat. Methods, 14, 263, 10.1038/nmeth.4155

Ramírez, 2016, deepTools2: a next generation web server for deep-sequencing data analysis, Nucleic Acids Res., 44, W160, 10.1093/nar/gkw257

Regev, 2017, The Human Cell Atlas, eLife, 6, 10.7554/eLife.27041

Rousseeuw, 1987, Silhouettes: A graphical aid to the interpretation and validation of cluster analysis, J. Comput. Appl. Math., 20, 53, 10.1016/0377-0427(87)90125-7

Safra, 2017, The m1A landscape on cytosolic and mitochondrial mRNA at single-base resolution, Nature, 551, 251, 10.1038/nature24456

Satija, 2015, Spatial reconstruction of single-cell gene expression data, Nat. Biotechnol., 33, 495, 10.1038/nbt.3192

2018, Barcoded Plate-Based Single Cell RNA-seq, Protocols.io

Sato, 2004, A functional genomics strategy reveals Rora as a component of the mammalian circadian clock, Neuron, 43, 527, 10.1016/j.neuron.2004.07.018

Saunders, 2018, Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain, Cell, 174, 1015, 10.1016/j.cell.2018.07.028

The Tabula Muris Consortium. (2017). Single-cell RNA-seq data from Smart-seq2 sequencing of FACS sorted cells. https://figshare.com/articles/Single-cell_RNA-seq_data_from_Smart-seq2_sequencing_of_FACS_sorted_cells/5715040.

The Tabula Muris Consortium. (2018a). Single-cell RNA-seq data from microfluidic emulsion. https://figshare.com/articles/Single-cell_RNA-seq_data_from_microfluidic_emulsion_v2_/5968960.

2018, Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris, Nature, 562, 367, 10.1038/s41586-018-0590-4

Segerstolpe, 2016, Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes, Cell Metab., 24, 593, 10.1016/j.cmet.2016.08.020

Shekhar, 2016, Comprehensive Classification of Retinal Bipolar Neurons by Single-Cell Transcriptomics, Cell, 166, 1308, 10.1016/j.cell.2016.07.054

Spanjaard, 2018, Simultaneous lineage tracing and cell-type identification using CRISPR-Cas9-induced genetic scars, Nat. Biotechnol., 36, 469, 10.1038/nbt.4124

Stein-O'Brien, 2019, Decomposing Cell Identity for Transfer Learning across Cellular Measurements, Platforms, Tissues, and Species, Cell Syst., 395, 10.1016/j.cels.2019.04.004

Stoeckius, 2017, Simultaneous epitope and transcriptome measurement in single cells, Nat. Methods, 14, 865, 10.1038/nmeth.4380

Stoeckius, 2018, Cell Hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics, Genome Biol., 19, 224, 10.1186/s13059-018-1603-1

Storey, 2003, Statistical significance for genomewide studies, Proc. Natl. Acad. Sci. USA, 100, 9440, 10.1073/pnas.1530509100

Stuart, 2019, Integrative single-cell analysis, Nat. Rev. Genet, 20, 257, 10.1038/s41576-019-0093-7

Svensson, 2017, Power analysis of single-cell RNA-sequencing experiments, Nat. Methods, 14, 381, 10.1038/nmeth.4220

Svensson, 2018, Exponential scaling of single-cell RNA-seq in the past decade, Nat. Protoc., 13, 599, 10.1038/nprot.2017.149

Syken, 2003, Expression of T cell receptor beta locus in central nervous system neurons, Proc. Natl. Acad. Sci. USA, 100, 13048, 10.1073/pnas.1735415100

Tanay, 2017, Scaling single-cell genomics from phenomenology to mechanism, Nature, 541, 331, 10.1038/nature21350

Tasic, 2016, Adult mouse cortical cell taxonomy revealed by single cell transcriptomics, Nat. Neurosci., 19, 335, 10.1038/nn.4216

Tasic, 2018, Shared and distinct transcriptomic cell types across neocortical areas, Nature, 563, 72, 10.1038/s41586-018-0654-5

Testi, 1989, T cell activation via Leu-23 (CD69), J. Immunol., 143, 1123, 10.4049/jimmunol.143.4.1123

Tibshirani, 2003, Class prediction by nearest shrunken centroids, with applications to DNA microarrays, Stat. Sci., 18, 104, 10.1214/ss/1056397488

Torre, 2018, Rare Cell Detection by Single-Cell RNA Sequencing as Guided by Single-Molecule RNA FISH, Cell Syst., 6, 171, 10.1016/j.cels.2018.01.014

Trapnell, 2009, TopHat: discovering splice junctions with RNA-Seq, Bioinformatics, 25, 1105, 10.1093/bioinformatics/btp120

van Dijk, 2018, Recovering Gene Interactions from Single-Cell Data Using Data Diffusion, Cell, 174, 716, 10.1016/j.cell.2018.05.061

Venkatadri, 2014, Differential expression of mGluR2 in the developing cerebral cortex of the mouse, J. Biomed. Sci. Eng., 7, 1030, 10.4236/jbise.2014.713100

Vitak, 2017, Sequencing thousands of single-cell genomes with combinatorial indexing, Nat. Methods, 14, 302, 10.1038/nmeth.4154

Wang, 2010, Heterogeneous Domain Adaptation Using Manifold Alignment, Proc. Int. Joint Conf. Artif. Intell, 1541

Wang

Wang, 2018, Three-dimensional intact-tissue sequencing of single-cell transcriptional states, Science, 361, 10.1126/science.aat5691

Welch, 2019, Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity, Cell, 177, 1873, 10.1016/j.cell.2019.05.006

Witten, 2009, A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis, Biostatistics, 10, 515, 10.1093/biostatistics/kxp008

Wolock, 2019, Scrublet: Computational identification of cell doublets in Single-Cell transcriptomic data, Cell Syst., 8, 281, 10.1016/j.cels.2018.11.005

Zheng, 2017, Massively parallel digital transcriptional profiling of single cells, Nat. Commun., 8, 14049, 10.1038/ncomms14049