Related references
Note: Only part of the references are listed.A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex
Zizhen Yao et al.
NATURE (2021)
Comparative cellular analysis of motor cortex in human, marmoset and mouse
Trygve E. Bakken et al.
NATURE (2021)
Optimal marker gene selection for cell type discrimination in single cell analyses
Bianca Dumitrascu et al.
NATURE COMMUNICATIONS (2021)
THE ROLE OF SCALE IN THE ESTIMATION OF CELL-TYPE PROPORTIONS
Gregory J. Hunt et al.
ANNALS OF APPLIED STATISTICS (2021)
A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation
Zizhen Yao et al.
CELL (2021)
SCDC: bulk gene expression deconvolution by multiple single-cell RNA sequencing references
Meichen Dong et al.
BRIEFINGS IN BIOINFORMATICS (2021)
Probabilistic cell typing enables fine mapping of closely related cell types in situ
Xiaoyan Qian et al.
NATURE METHODS (2020)
Cell stress in cortical organoids impairs molecular subtype specification
Aparna Bhaduri et al.
NATURE (2020)
Extraction of Distinct Neuronal Cell Types from within a Genetically Continuous Population
Euiseok J. Kim et al.
NEURON (2020)
Innovations present in the primate interneuron repertoire
Fenna M. Krienen et al.
NATURE (2020)
A community-based transcriptomics classification and nomenclature of neocortical cell types
Rafael Yuste et al.
NATURE NEUROSCIENCE (2020)
Jointly defining cell types from multiple single-cell datasets using LIGER
Jialin Liu et al.
NATURE PROTOCOLS (2020)
Deconvolving the contributions of cell-type heterogeneity on cortical gene expression
Ellis Patrick et al.
PLOS COMPUTATIONAL BIOLOGY (2020)
VolcaNoseR is a web app for creating, exploring, labeling and sharing volcano plots
Joachim Goedhart et al.
SCIENTIFIC REPORTS (2020)
A human cell atlas of fetal gene expression
Junyue Cao et al.
SCIENCE (2020)
Benchmarking of cell type deconvolution pipelines for transcriptomics data
Francisco Avila Cobos et al.
NATURE COMMUNICATIONS (2020)
scMerge leverages factor analysis, stable expression, and pseudoreplication to merge multiple single-cell RNA-seq datasets
Yingxin Lin et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)
Comprehensive Integration of Single-Cell Data
Tim Stuart et al.
CELL (2019)
Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity
Joshua D. Welch et al.
CELL (2019)
Individual brain organoids reproducibly form cell diversity of the human cerebral cortex
Silvia Velasco et al.
NATURE (2019)
Accurate estimation of cell-type composition from gene expression data
Daphne Tsoucas et al.
NATURE COMMUNICATIONS (2019)
SCINA: A Semi-Supervised Subtyping Algorithm of Single Cells and Bulk Samples
Ze Zhang et al.
GENES (2019)
Conserved cell types with divergent features in human versus mouse cortex
Rebecca D. Hodge et al.
NATURE (2019)
Supervised classification enables rapid annotation of cell atlases
Hannah A. Pliner et al.
NATURE METHODS (2019)
A lineage-resolved molecular atlas of C. elegans embryogenesis at single-cell resolution
Jonathan S. Packer et al.
SCIENCE (2019)
Fast, sensitive and accurate integration of single-cell data with Harmony
Ilya Korsunsky et al.
NATURE METHODS (2019)
M3Drop: dropout-based feature selection for scRNASeq
Tallulah S. Andrews et al.
BIOINFORMATICS (2019)
A Spatiotemporal Organ-Wide Gene Expression and Cell Atlas of the Developing Human Heart
Michaela Asp et al.
CELL (2019)
A comparison of automatic cell identification methods for single-cell RNA sequencing data
Tamim Abdelaal et al.
GENOME BIOLOGY (2019)
Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors
Laleh Haghverdi et al.
NATURE BIOTECHNOLOGY (2018)
Integrating single-cell transcriptomic data across different conditions, technologies, and species
Andrew Butler et al.
NATURE BIOTECHNOLOGY (2018)
scmap: projection of single-cell RNA -seq data across data sets
Vladimir Yu Kiselev et al.
NATURE METHODS (2018)
Exponential scaling of single-cell RNA-seq in the past decade
Valentine Svensson et al.
NATURE PROTOCOLS (2018)
Evolution of pallium, hippocampus, and cortical cell types revealed by single-cell transcriptomics in reptiles
Maria Antonietta Tosches et al.
SCIENCE (2018)
Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor
Megan Crow et al.
NATURE COMMUNICATIONS (2018)
A general and flexible method for signal extraction from single-cell RNA-seq data
Davide Risso et al.
NATURE COMMUNICATIONS (2018)
Molecular Architecture of the Mouse Nervous System
Amit Zeisel et al.
CELL (2018)
Developmental diversification of cortical inhibitory interneurons
Christian Mayer et al.
NATURE (2018)
Co-expression in Single-Cell Analysis: Saving Grace or Original Sin?
Megan Crow et al.
TRENDS IN GENETICS (2018)
Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris
Nicholas Schaum et al.
NATURE (2018)
Shared and distinct transcriptomic cell types across neocortical areas
Bosiljka Tasic et al.
NATURE (2018)
Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region
Jeffrey R. Moffitt et al.
SCIENCE (2018)
VIPER: variability-preserving imputation for accurate gene expression recovery in single-cell RNA sequencing studies
Mengjie Chen et al.
GENOME BIOLOGY (2018)
Missing data and technical variability in single-cell RNA-sequencing experiments
Stephanie C. Hicks et al.
BIOSTATISTICS (2018)
Batch effects and the effective design of single-cell gene expression studies
Po-Yuan Tung et al.
SCIENTIFIC REPORTS (2017)
Cross-Laboratory Analysis of Brain Cell Type Transcriptomes with Applications to Interpretation of Bulk Tissue Data
B. Ogan Mancarci et al.
ENEURO (2017)
Transcriptional Architecture of Synaptic Communication Delineates GABAergic Neuron Identity
Anirban Paul et al.
CELL (2017)
Cerebral cortical neuron diversity and development at single-cell resolution
Matthew B. Johnsont et al.
CURRENT OPINION IN NEUROBIOLOGY (2017)
Disentangling neural cell diversity using single-cell transcriptomics
Jean-Francois Poulin et al.
NATURE NEUROSCIENCE (2016)
Generating Neuronal Diversity in the Mammalian Cerebral Cortex
Simona Lodato et al.
ANNUAL REVIEW OF CELL AND DEVELOPMENTAL BIOLOGY, VOL 31 (2015)
Genetic programs controlling cortical interneuron fate
Nicoletta Kessaris et al.
CURRENT OPINION IN NEUROBIOLOGY (2014)
A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium
Zhenqiang Su et al.
NATURE BIOTECHNOLOGY (2014)
Bayesian approach to single-cell differential expression analysis
Peter V. Kharchenko et al.
NATURE METHODS (2014)
Toward a Genetic Dissection of Cortical Circuits in the Mouse
Z. Josh Huang
NEURON (2014)
Beyond Power Calculations: Assessing Type S (Sign) and Type M (Magnitude) Errors
Andrew Gelman et al.
PERSPECTIVES ON PSYCHOLOGICAL SCIENCE (2014)
Deconvolution of Blood Microarray Data Identifies Cellular Activation Patterns in Systemic Lupus Erythematosus
Alexander R. Abbas et al.
PLOS ONE (2009)
Petilla terminology:: nomenclature of features of GABAergic interneurons of the cerebral cortex
Giorgio A. Ascoli et al.
NATURE REVIEWS NEUROSCIENCE (2008)
Regulatory logic of neuronal diversity: Terminal selector genes and selector motifs
Oliver Hobert
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2008)
The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements
Leming Shi et al.
NATURE BIOTECHNOLOGY (2006)
Statistical tests for differential expression in cDNA microarray experiments
XQ Cui et al.
GENOME BIOLOGY (2003)