Single cell epigenomic atlas of the developing human brain and organoids
暂无分享,去创建一个
Pawel F. Przytycki | E. Eichler | K. Pollard | Anat Kreimer | N. Ahituv | T. Nowakowski | M. Haeussler | S. Ament | Chang N. Kim | Alex M. Casella | Tychele N. Turner | Ryan S. Ziffra | Amy B. Wilfert | P. Przytycki | A. Kreimer
[1] Matthew W. Mosconi,et al. Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism , 2019, Cell.
[2] Trygve E Bakken,et al. Sex-Based Analysis of De Novo Variants in Neurodevelopmental Disorders. , 2019, American journal of human genetics.
[3] A. West,et al. Neurobiological functions of transcriptional enhancers , 2019, Nature Neuroscience.
[4] Nir Yosef,et al. Identification and Massively Parallel Characterization of Regulatory Elements Driving Neural Induction. , 2019, Cell stem cell.
[5] B. Ren,et al. An ultra high-throughput method for single-cell joint analysis of open chromatin and transcriptome , 2019, Nature Structural & Molecular Biology.
[6] S. Pääbo,et al. Organoid single-cell genomic atlas uncovers human-specific features of brain development , 2019, Nature.
[7] Allan R. Jones,et al. Conserved cell types with divergent features in human versus mouse cortex , 2019, Nature.
[8] David Kulp,et al. Innovations in Primate Interneuron Repertoire , 2019, bioRxiv.
[9] Neva C. Durand,et al. Activity-by-Contact model of enhancer-promoter regulation from thousands of CRISPR perturbations , 2019, Nature Genetics.
[10] Jakob Grove,et al. Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder , 2017, bioRxiv.
[11] B. Ren,et al. Fast and Accurate Clustering of Single Cell Epigenomes Reveals Cis-Regulatory Elements in Rare Cell Types , 2019 .
[12] Andrew C. Adey,et al. The accessible chromatin landscape of the murine hippocampus at single-cell resolution , 2019, Genome research.
[13] Allon M Klein,et al. Scrublet: Computational Identification of Cell Doublets in Single-Cell Transcriptomic Data. , 2019, Cell systems.
[14] R. Satija,et al. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression , 2019, Genome Biology.
[15] Christopher P. Tzeng,et al. A scalable platform for the development of cell-type-specific viral drivers , 2019, bioRxiv.
[16] Alicia R. Martin,et al. Identification of common genetic risk variants for autism spectrum disorder , 2019, Nature Genetics.
[17] Andrew J. Hill,et al. The single cell transcriptional landscape of mammalian organogenesis , 2019, Nature.
[18] Trygve E Bakken,et al. Epigenetic landscape and AAV targeting of human neocortical cell classes , 2019 .
[19] Garreck H. Lenz,et al. Prospective, brain-wide labeling of neuronal subclasses with enhancer-driven AAVs , 2019, bioRxiv.
[20] Gerald Quon,et al. scAlign: a tool for alignment, integration, and rare cell identification from scRNA-seq data , 2018, Genome Biology.
[21] Ian T. Fiddes,et al. Establishing Cerebral Organoids as Models of Human-Specific Brain Evolution , 2018, Cell.
[22] R. Marioni,et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions , 2018, Nature Neuroscience.
[23] Patrick J. Short,et al. Integrating healthcare and research genetic data empowers the discovery of 49 novel developmental disorders , 2019, bioRxiv.
[24] Gerome Breen,et al. Genetic identification of brain cell types underlying schizophrenia , 2017, Nature Genetics.
[25] Stephan J Sanders,et al. Integrative functional genomic analysis of human brain development and neuropsychiatric risks , 2018, Science.
[26] M. Gerstein,et al. Transcriptome and epigenome landscape of human cortical development modeled in organoids , 2018, Science.
[27] Matthew W. Mosconi,et al. Novel genes for autism implicate both excitatory and inhibitory cell lineages in risk , 2018, bioRxiv.
[28] Trygve E Bakken,et al. Neurodevelopmental disease genes implicated by de novo mutation and copy number variation morbidity , 2018, Nature Genetics.
[29] Allan R. Jones,et al. Shared and distinct transcriptomic cell types across neocortical areas , 2018, Nature.
[30] Andrew C. Adey,et al. Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data. , 2018, Molecular cell.
[31] Kevin R. Moon,et al. Recovering Gene Interactions from Single-Cell Data Using Data Diffusion , 2018, Cell.
[32] A. Regev,et al. Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis , 2018, Science.
[33] Ryan L. Collins,et al. An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder , 2018, Nature Genetics.
[34] Paul Hoffman,et al. Integrating single-cell transcriptomic data across different conditions, technologies, and species , 2018, Nature Biotechnology.
[35] Jakob Grove,et al. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection , 2018, Nature Genetics.
[36] D. Dickel,et al. Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation , 2018, Nature Neuroscience.
[37] D. Geschwind,et al. The Dynamic Landscape of Open Chromatin during Human Cortical Neurogenesis , 2018, Cell.
[38] P. Kharchenko,et al. Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain , 2017, Nature Biotechnology.
[39] Alex A. Pollen,et al. Spatiotemporal gene expression trajectories reveal developmental hierarchies of the human cortex , 2017, Science.
[40] M. Gerstein,et al. Molecular and cellular reorganization of neural circuits in the human lineage , 2017, Science.
[41] A. Tanay,et al. Multiscale 3D Genome Rewiring during Mouse Neural Development , 2017, Cell.
[42] Nicholas A. Sinnott-Armstrong,et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues , 2017, Nature Methods.
[43] William J. Greenleaf,et al. chromVAR: Inferring transcription factor-associated accessibility from single-cell epigenomic data , 2017, Nature Methods.
[44] Bradley P. Coe,et al. Targeted sequencing identifies 91 neurodevelopmental disorder risk genes with autism and developmental disability biases , 2017, Nature Genetics.
[45] Evan Z. Macosko,et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types , 2017, Nature Genetics.
[46] Joseph R Ecker,et al. Cerebral Organoids Recapitulate Epigenomic Signatures of the Human Fetal Brain. , 2016, Cell reports.
[47] Soher Balkhy,et al. Mutations in Human Accelerated Regions Disrupt Cognition and Social Behavior , 2016, Cell.
[48] Tomasz J. Nowakowski,et al. Transformation of the Radial Glia Scaffold Demarcates Two Stages of Human Cerebral Cortex Development , 2016, Neuron.
[49] Fidel Ramírez,et al. deepTools2: a next generation web server for deep-sequencing data analysis , 2016, Nucleic Acids Res..
[50] Adele M Doyle,et al. Fixed single-cell transcriptomic characterization of human radial glial diversity , 2015, Nature Methods.
[51] Bernat Gel,et al. regioneR: an R/Bioconductor package for the association analysis of genomic regions based on permutation tests , 2015, Bioinform..
[52] Madeline A. Lancaster,et al. Human cerebral organoids recapitulate gene expression programs of fetal neocortex development , 2015, Proceedings of the National Academy of Sciences.
[53] Alex A. Pollen,et al. Molecular Identity of Human Outer Radial Glia during Cortical Development , 2015, Cell.
[54] Yakir A Reshef,et al. Partitioning heritability by functional annotation using genome-wide association summary statistics , 2015, Nature Genetics.
[55] Qing-Yu He,et al. ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization , 2015, Bioinform..
[56] Howard Y. Chang,et al. Single-cell chromatin accessibility reveals principles of regulatory variation , 2015, Nature.
[57] Terrence J. Sejnowski,et al. Epigenomic Signatures of Neuronal Diversity in the Mammalian Brain , 2015, Neuron.
[58] Andrew C. Adey,et al. Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing , 2015, Science.
[59] Jing Leng,et al. Evolutionary changes in promoter and enhancer activity during human corticogenesis , 2015, Science.
[60] Kali T. Witherspoon,et al. Refining analyses of copy number variation identifies specific genes associated with developmental delay , 2014, Nature Genetics.
[61] L. Gudas,et al. Retinoic Acid Suppresses the Canonical Wnt Signaling Pathway in Embryonic Stem Cells and Activates the Noncanonical Wnt Signaling Pathway , 2014, Stem cells.
[62] C. Spencer,et al. Biological Insights From 108 Schizophrenia-Associated Genetic Loci , 2014, Nature.
[63] Hongkui Zeng,et al. Transcriptional Regulation of Enhancers Active in Protodomains of the Developing Cerebral Cortex , 2014, Neuron.
[64] Allan R. Jones,et al. Transcriptional Landscape of the Prenatal Human Brain , 2014, Nature.
[65] A. Visel,et al. Rapid and Pervasive Changes in Genome-wide Enhancer Usage during Mammalian Development , 2013, Cell.
[66] Katherine S. Pollard,et al. Many human accelerated regions are developmental enhancers , 2013, Philosophical Transactions of the Royal Society B: Biological Sciences.
[67] M. Eiraku,et al. Self-organization of axial polarity, inside-out layer pattern, and species-specific progenitor dynamics in human ES cell–derived neocortex , 2013, Proceedings of the National Academy of Sciences.
[68] Jan H Lui,et al. Non-epithelial stem cells and cortical interneuron production in the human ganglionic eminences , 2013, Nature Neuroscience.
[69] J. Rubenstein,et al. Subcortical origins of human and monkey neocortical interneurons , 2013, Nature Neuroscience.
[70] Howard Y. Chang,et al. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position , 2013, Nature Methods.
[71] J. Rubenstein,et al. CoupTFI Interacts with Retinoic Acid Signaling during Cortical Development , 2013, PloS one.
[72] Hani Z. Girgis,et al. A High-Resolution Enhancer Atlas of the Developing Telencephalon , 2013, Cell.
[73] C. Glass,et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. , 2010, Molecular cell.
[74] Steve Horvath,et al. WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.
[75] Clifford A. Meyer,et al. Model-based Analysis of ChIP-Seq (MACS) , 2008, Genome Biology.
[76] A. Mortazavi,et al. Genome-Wide Mapping of in Vivo Protein-DNA Interactions , 2007, Science.
[77] Inna Dubchak,et al. VISTA Enhancer Browser—a database of tissue-specific human enhancers , 2006, Nucleic Acids Res..
[78] David Haussler,et al. Forces Shaping the Fastest Evolving Regions in the Human Genome , 2006, PLoS genetics.
[79] D. Wotton,et al. TGIF Inhibits Retinoid Signaling , 2006, Molecular and Cellular Biology.
[80] Morriss Gm. Morphogenesis of the malformations induced in rat embryos by maternal hypervitaminosis A. , 1972 .
[81] G. Morriss. Morphogenesis of the malformations induced in rat embryos by maternal hypervitaminosis A. , 1972, Journal of anatomy.
[82] S. Counce. The Strategy of the Genes , 1958, The Yale Journal of Biology and Medicine.