C1 CAGE detects transcription start sites and enhancer activity at single-cell resolution

[1]  Efthymios Motakis,et al.  CONFESS: Fluorescence-based single-cell ordering in R , 2018, bioRxiv.

[2]  I. Nikaido,et al.  Single-cell full-length total RNA sequencing uncovers dynamics of recursive splicing and enhancer RNAs , 2018, Nature Communications.

[3]  I. Nikaido,et al.  Single-cell full-length total RNA sequencing uncovers dynamics of recursive splicing and enhancer RNAs , 2018, Nature Communications.

[4]  Benoît Ballester,et al.  ReMap 2018: an updated atlas of regulatory regions from an integrative analysis of DNA-binding ChIP-seq experiments , 2017, Nucleic Acids Res..

[5]  Sachi Kato,et al.  SCPortalen: human and mouse single-cell centric database , 2017, Nucleic Acids Res..

[6]  S. Picelli Single-cell RNA-sequencing: The future of genome biology is now , 2017, RNA biology.

[7]  Jordan A. Ramilowski,et al.  An atlas of human long non-coding RNAs with accurate 5′ ends , 2017, Nature.

[8]  Jay W. Shin,et al.  Single-cell transcriptomes of fluorescent, ubiquitination-based cell cycle indicator cells , 2016, bioRxiv.

[9]  Matthew R. Krause,et al.  Single-cell profiling reveals that eRNA accumulation at enhancer–promoter loops is not required to sustain transcription , 2016, Nucleic acids research.

[10]  A. Regev,et al.  Revealing the vectors of cellular identity with single-cell genomics , 2016, Nature Biotechnology.

[11]  Valentine Svensson,et al.  Power Analysis of Single Cell RNA-Sequencing Experiments , 2016, Nature Methods.

[12]  M. Schaub,et al.  SC3 - consensus clustering of single-cell RNA-Seq data , 2016, Nature Methods.

[13]  Davis J. McCarthy,et al.  A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor , 2016, F1000Research.

[14]  John C Marioni,et al.  A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor , 2016, F1000Research.

[15]  David A. Knowles,et al.  Batch effects and the effective design of single-cell gene expression studies , 2016, Scientific Reports.

[16]  Hongkai Ji,et al.  TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis , 2016, Nucleic acids research.

[17]  J. Marioni,et al.  Pooling across cells to normalize single-cell RNA sequencing data with many zero counts , 2016, Genome Biology.

[18]  Fidel Ramírez,et al.  deepTools2: a next generation web server for deep-sequencing data analysis , 2016, Nucleic Acids Res..

[19]  C. Plessy,et al.  Targeted reduction of highly abundant transcripts using pseudo-random primers. , 2016, BioTechniques.

[20]  M. Rosenfeld,et al.  Enhancers as non-coding RNA transcription units: recent insights and future perspectives , 2016, Nature Reviews Genetics.

[21]  David J. Arenillas,et al.  CAGEd-oPOSSUM: motif enrichment analysis from CAGE-derived TSSs , 2016, bioRxiv.

[22]  J. Mesirov,et al.  The Molecular Signatures Database Hallmark Gene Set Collection , 2015 .

[23]  David J. Arenillas,et al.  JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles , 2015, Nucleic Acids Res..

[24]  Cole Trapnell,et al.  Defining cell types and states with single-cell genomics , 2015, Genome research.

[25]  Sarah A Teichmann,et al.  Computational assignment of cell-cycle stage from single-cell transcriptome data. , 2015, Methods.

[26]  Ning Leng,et al.  Oscope identifies oscillatory genes in unsynchronized single cell RNA-seq experiments , 2015, Nature Methods.

[27]  X. Zhuang,et al.  Spatially resolved, highly multiplexed RNA profiling in single cells , 2015, Science.

[28]  S. Itzkovitz,et al.  Bursty gene expression in the intact mammalian liver. , 2015, Molecular cell.

[29]  Thomas J. Ha,et al.  Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells , 2015, Science.

[30]  Michael Q. Zhang,et al.  Integrative analysis of 111 reference human epigenomes , 2015, Nature.

[31]  Timo Lassmann,et al.  TagDust2: a generic method to extract reads from sequencing data , 2015, BMC Bioinformatics.

[32]  M. Daly,et al.  Genetic and Epigenetic Fine-Mapping of Causal Autoimmune Disease Variants , 2014, Nature.

[33]  David P. Kreil,et al.  Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures , 2014, Nature Communications.

[34]  C. Glass,et al.  Enhancer RNAs and regulated transcriptional programs. , 2014, Trends in biochemical sciences.

[35]  Cesare Furlanello,et al.  A promoter-level mammalian expression atlas , 2015 .

[36]  T. Meehan,et al.  An atlas of active enhancers across human cell types and tissues , 2014, Nature.

[37]  Yoshihide Hayashizaki,et al.  Interactive visualization and analysis of large-scale sequencing datasets using ZENBU , 2014, Nature Biotechnology.

[38]  P. Spanheimer,et al.  TFAP2C Governs the Luminal Epithelial Phenotype in Mammary Development and Carcinogenesis , 2014, Oncogene.

[39]  Gioele La Manno,et al.  Quantitative single-cell RNA-seq with unique molecular identifiers , 2013, Nature Methods.

[40]  Yibin Kang,et al.  Transcriptional control of cancer metastasis. , 2013, Trends in cell biology.

[41]  N. Neff,et al.  Quantitative assessment of single-cell RNA-sequencing methods , 2013, Nature Methods.

[42]  L. Grøntved,et al.  eRNAs promote transcription by establishing chromatin accessibility at defined genomic loci. , 2013, Molecular cell.

[43]  James A. DeCaprio,et al.  The DREAM complex: master coordinator of cell cycle-dependent gene expression , 2013, Nature Reviews Cancer.

[44]  Piero Carninci,et al.  Suppression of artifacts and barcode bias in high-throughput transcriptome analyses utilizing template switching , 2012, Nucleic acids research.

[45]  Data production leads,et al.  An integrated encyclopedia of DNA elements in the human genome , 2012 .

[46]  Raymond K. Auerbach,et al.  An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.

[47]  Bronwen L. Aken,et al.  GENCODE: The reference human genome annotation for The ENCODE Project , 2012, Genome research.

[48]  C. Heldin,et al.  Regulation of EMT by TGFβ in cancer , 2012, FEBS letters.

[49]  G. Smyth,et al.  Camera: a competitive gene set test accounting for inter-gene correlation , 2012, Nucleic acids research.

[50]  H. Hurst,et al.  Histone Demethylase KDM5B Collaborates with TFAP2C and Myc To Repress the Cell Cycle Inhibitor p21cip (CDKN1A) , 2012, Molecular and Cellular Biology.

[51]  David Schneider,et al.  Dynamics of TGF-β induced epithelial-to-mesenchymal transition monitored by electric cell-substrate impedance sensing. , 2011, Biochimica et biophysica acta.

[52]  Nacho Molina,et al.  Mammalian Genes Are Transcribed with Widely Different Bursting Kinetics , 2011, Science.

[53]  Carsten O. Daub,et al.  Linking promoters to functional transcripts in small samples with nanoCAGE and CAGEscan , 2010, Nature Methods.

[54]  Kohei Miyazono,et al.  TGFβ signalling: a complex web in cancer progression , 2010, Nature Reviews Cancer.

[55]  Matthew D. Young,et al.  Gene ontology analysis for RNA-seq: accounting for selection bias , 2010, Genome Biology.

[56]  Richard Durbin,et al.  Fast and accurate long-read alignment with Burrows–Wheeler transform , 2010, Bioinform..

[57]  Christopher Williams,et al.  AP‐2γ promotes proliferation in breast tumour cells by direct repression of the CDKN1A gene , 2009, The EMBO journal.

[58]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[59]  S. Friedman,et al.  TGF-beta regulates the expression of transcription factor KLF6 and its splice variants and promotes co-operative transactivation of common target genes through a Smad3-Sp1-KLF6 interaction. , 2009, Biochemical Journal.

[60]  Steve Horvath,et al.  WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.

[61]  H. Baker,et al.  ALDH isozymes downregulation affects cell growth, cell motility and gene expression in lung cancer cells , 2008, Molecular Cancer.

[62]  Y. Qiu,et al.  Gfi-1 represses CDKN2B encoding p15INK4B through interaction with Miz-1 , 2008, Proceedings of the National Academy of Sciences.

[63]  Scott A. Rifkin,et al.  Imaging individual mRNA molecules using multiple singly labeled probes , 2008, Nature Methods.

[64]  J. Massagué,et al.  TGFβ in Cancer , 2008, Cell.

[65]  Martin S. Taylor,et al.  Genome-wide analysis of mammalian promoter architecture and evolution , 2006, Nature Genetics.

[66]  J. Kawai,et al.  Cap analysis gene expression for high-throughput analysis of transcriptional starting point and identification of promoter usage , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[67]  Jin Hong Liu,et al.  Functional association of TGF-β receptor II with cyclin B , 1999, Oncogene.

[68]  F S Fay,et al.  Visualization of single RNA transcripts in situ. , 1998, Science.

[69]  A. Akeson,et al.  A fluorometric assay for the quantitation of cell adherence to endothelial cells. , 1993, Journal of immunological methods.

[70]  M. Mhlanga,et al.  Visualization of Enhancer-Derived Noncoding RNA. , 2017, Methods in molecular biology.

[71]  M. Harbers,et al.  NanoCAGE: A Method for the Analysis of Coding and Noncoding 5'-Capped Transcriptomes. , 2017, Methods in molecular biology.

[72]  J. Mesirov,et al.  The Molecular Signatures Database (MSigDB) hallmark gene set collection. , 2015, Cell systems.

[73]  Piero Carninci,et al.  Detecting expressed genes using CAGE. , 2014, Methods in molecular biology.