D. Risso

发表

Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics

Russell B. Fletcher, S. Dudoit, E. Purdom, 2017, BMC Genomics.

A general and flexible method for signal extraction from single-cell RNA-seq data

S. Dudoit, Jean-Philippe Vert, D. Risso, 2018, Nature Communications.

Normalization of RNA-seq data using factor analysis of control genes or samples

S. Dudoit, T. Speed, J. Ngai, 2014, Nature Biotechnology.

Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-Seq

Sandrine Dudoit, Nir Yosef, Davide Risso, 2017 .

EDASeq : Exploratory Data Analysis and Normalization for RNA-Seq

D. Risso, 2013 .

Deconstructing Olfactory Stem Cell Trajectories at Single-Cell Resolution.

Russell B. Fletcher, S. Dudoit, E. Purdom, 2017, Cell stem cell.

Injury Activates Transient Olfactory Stem Cell States with Diverse Lineage Capacities.

Russell B. Fletcher, S. Dudoit, E. Purdom, 2017, Cell stem cell.

RUVSeq: Remove Unwanted Variation from RNA-Seq Data

D. Risso, 2016 .

ZINB-WaVE: A general and flexible method for signal extraction from single-cell RNA-seq data

Jean-Philippe Vert, Sandrine Dudoit, Davide Risso, 2017, bioRxiv.

Normalizing single-cell RNA sequencing data: challenges and opportunities

Sandrine Dudoit, Davide Risso, John C Marioni, 2017, Nature Methods.

An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types

Evan Z. Macosko, A. S. Booeshaghi, Ricky S. Adkins, 2020, bioRxiv.

Slingshot: Cell lineage and pseudotime inference for single-cell transcriptomics

Sandrine Dudoit, Nir Yosef, Davide Risso, 2017 .

Figures and figure supplements Complementary networks of cortical somatostatin interneurons enforce layer specific control

Daniel P. Mossing, L. Paninski, H. Adesnik, 2019 .

Complementary networks of cortical somatostatin interneurons enforce layer specific control

L. Paninski, H. Adesnik, J. Ngai, 2018, bioRxiv.

Deficiency of microRNA miR-34a expands cell fate potential in pluripotent stem cells

K. C. K. Lloyd, T. Speed, Z. Xuan, 2017, Science.

Oxysterols: From redox bench to industry

D. Risso, G. Poli, F. Biasi, 2021, Redox biology.

Cell-type, single-cell, and spatial signatures of brain-region specific splicing in postnatal development

Stephen R. Williams, Hagen U. Tilgner, A. Frankish, 2020, bioRxiv.

A multimodal cell census and atlas of the mammalian primary motor cortex

Satrajit S. Ghosh, Nicholas N. Foster, Evan Z. Macosko, 2020, Nature.

Non-neuronal expression of SARS-CoV-2 entry genes in the olfactory system suggests mechanisms underlying COVID-19-associated anosmia

Russell B. Fletcher, Hector Roux de Bézieux, David H. Brann, 2020, Science Advances.

Combinatorial Expression of Grp and Neurod6 Defines Dopamine Neuron Populations with Distinct Projection Patterns and Disease Vulnerability

J. Ngai, D. Risso, Helen S. Bateup, 2018, eNeuro.

Non-neuronal expression of SARS-CoV-2 entry genes in the olfactory system suggests mechanisms underlying COVID-19-associated anosmia

Russell B. Fletcher, Hector Roux de Bézieux, David H. Brann, 2020, Science Advances.

A nonparametric algorithm for clustering microarray data

Riccardo De Bin, D. Risso, 2010 .

Guided structure learning of DAGs for count data

Thi Kim Hue Nguyen, D. Risso, M. Chiogna, 2022, 2206.09754.

Performance Assessment and Selection of Normalization Procedures forSingle-Cell RNA-Seq

S. Dudoit, E. Purdom, N. Yosef, 2019 .

Assessment of statistical methods from single cell, bulk RNA-seq, and metagenomics applied to microbiome data

L. Waldron, D. Risso, N. Vitulo, 2020, Genome Biology.

Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications

Charlotte Soneson, Jean-Philippe Vert, Sandrine Dudoit, 2018, Genome Biology.

Silencing of Odorant Receptor Genes by G Protein βγ Signaling Ensures the Expression of One Odorant Receptor per Olfactory Sensory Neuron

Terence P. Speed, Sandrine Dudoit, Davide Risso, 2014, Neuron.

Pre-Processing for the Zebrash RNA-Seq Gene-Level Counts

D. Risso, 2016 .

CO-CLUSTERING OF SPATIALLY RESOLVED TRANSCRIPTOMIC DATA.

D. Risso, Andrea Sottosanti, 2021, The annals of applied statistics.

Guided structure learning of DAGs for count data

D. Risso, M. Chiogna, E. Banzato, 2022, 2206.09754.

A Bartlett-type correction for likelihood ratio tests with application to testing equality of Gaussian graphical models

D. Risso, M. Chiogna, Vera Djordjilović, 2022, Statistics & Probability Letters.

SpatialExperiment: infrastructure for spatially-resolved transcriptomics data in R using Bioconductor

Helena L. Crowell, D. Risso, A. Lun, 2021, bioRxiv.

Per-sample standardization and asymmetric winsorization lead to accurate clustering of RNA-seq expression profiles

Davide Risso, Stefano M. Pagnotta, D. Risso, 2020, bioRxiv.

Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-Seq.

Sandrine Dudoit, Nir Yosef, Davide Risso, 2019, Cell systems.

mbkmeans: Fast clustering for single cell data using mini-batch k-means

Stephanie C. Hicks, Davide Risso, Elizabeth Purdom, 2020, bioRxiv.

Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics

Russell B. Fletcher, S. Dudoit, E. Purdom, 2017, bioRxiv.

How data analysis affects power, reproducibility and biological insight of RNA-seq studies in complex datasets

Terence P. Speed, Davide Risso, Ted Abel, 2015, Nucleic acids research.

PsiNorm: a scalable normalization for single-cell RNA-seq data

D. Risso, C. Romualdi, Graziano Martello, 2021, bioRxiv.

Normalization of Single-Cell RNA-Seq Data.

D. Risso, 2021, Methods in molecular biology.

Orchestrating single-cell analysis with Bioconductor

Raphael Gottardo, Charlotte Soneson, Stephanie C. Hicks, 2019, Nature Methods.

A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex

Evan Z. Macosko, A. S. Booeshaghi, Ricky S. Adkins, 2021, Nature.

Learning-dependent chromatin remodeling highlights noncoding regulatory regions linked to autism

Nancy R. Zhang, John N. Koberstein, H. Hakonarson, 2018, Science Signaling.

GC-Content Normalization for RNA-Seq Data

Sandrine Dudoit, Davide Risso, Gavin Sherlock, 2011, BMC Bioinformatics.

Improving replicability in single-cell RNA-Seq cell type discovery with Dune

Sandrine Dudoit, Davide Risso, Jesse Gillis, 2020, bioRxiv.

NewWave: a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA-seq data

D. Risso, C. Romualdi, G. Sales, 2021, bioRxiv.

Assessment of statistical methods from single cell, bulk RNA-seq, and metagenomics applied to microbiome data

L. Waldron, D. Risso, N. Vitulo, 2020, Genome Biology.

Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications

S. Dudoit, Jean-Philippe Vert, M. Robinson, 2018, bioRxiv.

A general and flexible method for signal extraction from single-cell RNA-seq data

S. Dudoit, Jean-Philippe Vert, D. Risso, 2018, Nature Communications.

Assessment of statistical methods from single cell, bulk RNA-seq, and metagenomics applied to microbiome data

Chiara Romualdi, Davide Risso, Matteo Calgaro, 2020, Genome Biology.

Normalization benchmark of ATAC-seq datasets shows the importance of accounting for GC-content effects

S. Dudoit, J. Ngai, Kelly Street, 2021, bioRxiv.

clusterExperiment and RSEC: A Bioconductor package and framework for clustering of single-cell and other large gene expression datasets

Sandrine Dudoit, Davide Risso, Elizabeth Purdom, 2018, bioRxiv.

A mouse-specific retrotransposon drives a conserved Cdk2ap1 isoform essential for development

T. Speed, Z. Xuan, Lin He, 2021, Cell.

Epigenetic evolution and lineage histories of chronic lymphocytic leukemia

Rafael C. Schulman, Kevin Y. Huang, Nathaniel D. Omans, 2019, Nature.

Simultaneous inference for RNA-Seq data

Davide Risso, D. Risso, 2012 .

A novel approach to the clustering of microarray data via nonparametric density estimation

Davide Risso, Riccardo De Bin, D. Risso, 2011, BMC Bioinformatics.

A species-specific retrotransposon drives a conserved Cdk2ap1 isoform essential for preimplantation development

T. Speed, Z. Xuan, Lin He, 2021, bioRxiv.

Curated Single Cell Multimodal Landmark Datasets for R/Bioconductor

Martin T. Morgan, Marcel Ramos, L. Waldron, 2021 .

Rapid non-uniform adaptation to conformation-specific KRAS(G12C) inhibition

Davide Risso, Besnik Qeriqi, L. Mazutis, 2020, Nature.

A spatially resolved brain region- and cell type-specific isoform atlas of the postnatal mouse brain

Stephen R. Williams, Weill Cornell Medicine, Hagen U. Tilgner, 2021, Nature Communications.

Epigenetic evolution and lineage histories of chronic lymphocytic leukemia

Martin J. Aryee, Rafael C. Schulman, Kevin Y. Huang, 2019, Nature.

Clustering via nonparametric density estimation: an application to microarray data

Davide Risso, Riccardo De Bin, D. Risso, 2010 .

A Hierarchical Bayesian Model for RNA-Seq Data

Gabriele Sales, Monica Chiogna, Davide Risso, 2013 .

Removal of unwanted variation reveals novel patterns of gene expression linked to sleep homeostasis in murine cortex

John N. Koberstein, T. Speed, A. Watson, 2016, BMC Genomics.

signifinder enables the identification of tumor cell states and cancer expression signatures in bulk, single-cell and spatial transcriptomic data

D. Risso, G. Esposito, E. Calura, 2023, bioRxiv.

Receiver operating characteristic estimation and threshold selection criteria in three-class classification problems for clustered data

D. Risso, M. Chiogna, Duc-Khanh To, 2022, Statistical methods in medical research.

Rapid non-uniform adaptation to conformation-specific KRAS(G12C) inhibition

L. Mazutis, D. Risso, E. de Stanchina, 2019, Nature.

A modified LOESS normalization applied to microRNA arrays: a comparative evaluation

Monica Chiogna, Chiara Romualdi, Davide Risso, 2009, Bioinform..

Normalization of RNA-Seq

Davide Risso, D. Risso, 2012 .

Shank3 modulates sleep and expression of circadian transcription factors

D. Risso, M. Frank, L. Peixoto, 2018, bioRxiv.

Assessment of single cell RNA-seq statistical methods on microbiome data

Davide Risso, Matteo Calgaro, Levi Waldron, 2020 .

A comparison on effects of normalisations in the detection of differentially expressed genes

Monica Chiogna, Chiara Romualdi, Davide Risso, 2009, BMC Bioinformatics.

A-MADMAN: Annotation-based microarray data meta-analysis tool

Chiara Romualdi, Davide Risso, Silvio Bicciato, 2009, BMC Bioinformatics.

Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies

Paolo G. V. Martini, Gabriele Sales, Stefano Cagnin, 2011, BMC Bioinformatics.

Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics

Russell B. Fletcher, S. Dudoit, E. Purdom, 2018, BMC Genomics.

A general and flexible method for signal extraction from single-cell RNA-seq data

S. Dudoit, Jean-Philippe Vert, D. Risso, 2017, Nature Communications.

Complementary networks of cortical somatostatin interneurons enforce layer specific control

L. Paninski, H. Adesnik, J. Ngai, 2018, bioRxiv.

Removal of unwanted variation reveals novel patterns of gene expression linked to sleep homeostasis in murine cortex

John N. Koberstein, T. Speed, A. Watson, 2016, BMC Genomics.

Publisher Correction: A general and flexible method for signal extraction from single-cell RNA-seq data

Jean-Philippe Vert, Sandrine Dudoit, Davide Risso, 2019, Nature Communications.

Designing spatial transcriptomic experiments

D. Risso, D. Righelli, Andrea Sottosanti, 2023, Nature Methods.

The Role of Spike-In Standards in the Normalization of RNA-seq

Terence P. Speed, Sandrine Dudoit, Davide Risso, 2014 .

Structure learning for zero-inflated counts with an application to single-cell RNA sequencing data

D. Risso, M. Chiogna, T. Nguyen, 2020, Annals of Applied Statistics.

Contextual fear conditioning induces differential alternative splicing

John N. Koberstein, T. Speed, T. Abel, 2016, Neurobiology of Learning and Memory.

Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-Seq

S. Dudoit, E. Purdom, J. Ngai, 2017, bioRxiv.

Structured factorization for single-cell gene expression data

D. Risso, A. Canale, Giovanni Toto, 2023, 2305.11669.

A Latent Activated Olfactory Stem Cell State Revealed by Single Cell Transcriptomic and Epigenomic Profiling

E. Purdom, Kelly Street, D. Risso, 2023, bioRxiv.

A comparison on effects of normalisations in the detection of differentially expressed genes

D. Risso, M. Chiogna, C. Romualdi, 2009, BMC Bioinformatics.

Assessment of single cell RNA-seq statistical methods on microbiome data

L. Waldron, D. Risso, N. Vitulo, 2019 .