Davide Risso

发表

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

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

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.

Bioconductor workflow for single-cell RNA sequencing: Normalization, dimensionality reduction, clustering, and lineage inference

Sandrine Dudoit, Davide Risso, Fanny Perraudeau, 2017, F1000Research.

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 .

Orchestrating single-cell analysis with Bioconductor

Raphael Gottardo, Charlotte Soneson, Federico Marini, 2019, Nature Methods.

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

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

Normalizing single-cell RNA sequencing data: challenges and opportunities

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

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

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

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

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

A Hierarchical Bayesian Model for RNA-Seq Data

Gabriele Sales, Monica Chiogna, Davide Risso, 2013 .

Orchestrating single-cell analysis with Bioconductor

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

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.

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.

Clustering via nonparametric density estimation: an application to microarray data

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

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

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

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.

Simultaneous inference for RNA-Seq data

Davide Risso, D. Risso, 2012 .

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

Davide Risso, Matteo Calgaro, Levi Waldron, 2020 .

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

Mark D. Robinson, Charlotte Soneson, Jean-Philippe Vert, 2018 .

Normalization of RNA-Seq

Davide Risso, D. Risso, 2012 .

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

Sandrine Dudoit, Nir Yosef, Davide Risso, 2017 .

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

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

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

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

GC-Content Normalization for RNA-Seq Data

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

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

Monica Chiogna, Davide Risso, Thi Kim Hue Nguyen, 2020 .

Publisher Correction: Orchestrating single-cell analysis with Bioconductor

Raphael Gottardo, Charlotte Soneson, Federico Marini, 2019, Nature Methods.

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

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

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

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

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

Davide Risso, Stefano Maria Pagnotta, 2021, Bioinform..

Co-clustering of Spatially Resolved Transcriptomic Data

Andrea Sottosanti, Davide Risso, 2021 .

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

Chiara Romualdi, Davide Risso, Graziano Martello, 2021, Bioinform..

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

Sandrine Dudoit, Nir Yosef, Davide Risso, 2017 .

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.

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.

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

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