Publications

Peer reviewed

Correcting the Mean-Variance Dependency for Differential Variability Testing Using Single-Cell RNA Sequencing Data

N Eling, AC Richard, S Richardson, JC Marioni and CA Vallejos (2018)

Cell Systems

Extends BASiCS with a residual measure of variability that is not confounded by mean expression and with a robust procedure for quantifying technical noise in experiments without technical spike-in molecules.

Normalizing single-cell RNA sequencing data: challenges and opportunities

CA Vallejos, D Risso, A Scialdone, S Dudoit and JC Marioni (2017)

Nature Methods

Discusses commonly used normalization approaches for single-cell RNA sequencing data and illustrate how some of these can produce misleading results.

Bayesian survival analysis of university outcomes

CA Vallejos and MFJ Steel (2017)

Journal of the Royal Statistical Society - Series A

Introduces and applies a competing risks framework to identify risk factors associated to university dropouts and delayed graduations.

Aging increases cell-to-cell transcriptional variability upon immune stimulation

CP Martinez-Jimenez, N Eling, H Chen, CA Vallejos, AA Kolodziejczyk, F Connor, L Stojic, TF Rayner, MJT Stubbington, SA Teichmann, M de la Roche, JC Marioni and DT Odom (2017)

Science

Studies transcriptional heterogeneity in CD4+T cells using single-cell RNA sequencing of unstimulated and stimulated naïve and effector memory CD4+ T cells.

Incorporating unobserved heterogeneity in Weibull survival models: A Bayesian approach

CA Vallejos and MFJ Steel (2017)

Econometrics and Statistics

Extends Weibull regression survival models to account for outliers and other forms of unobserved heterogeneity.

Beyond comparisons of means: understanding changes in gene expression at the single-cell level

CA Vallejos, S Richardson and JC Marioni (2016)

Genome Biology

Extends BASiCS with a probabilistic framework to assess differential expression patterns (mean and variability) between cell populations using single-cell RNA sequencing data.

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data

CA Vallejos, JC Marioni and S Richardson (2015)

PLOS Computational Biology

Presents BASiCS as an integrated statistical framework for single-cell RNA sequencing data: normalisation, technical noise quantification as well as highly and lowly genes variable identification.

Objective Bayesian survival analysis using scale mixtures of log-normal distributions

CA Vallejos and MFJ Steel (2015)

Journal of the American Statistical Association

Introduces the family of shape mixtures of log-normal distributions as a flexible framework for survival modelling, studying Bayesian inference under nonsubjective priors based on the Jeffreys’ rule.

Others

Shrinkage estimation of large covariance matrices using multiple shrinkage targets

H Gray, GGR Leday, CA Vallejos, S Richardson (2018)

arXiv

Disentangling transcriptional heterogeneity among single-cells: a Bayesian approach

CA Vallejos, S Richardson and JC Marioni (2015)

Mini workshop: Recent Developments in Statistical Methods with Applications to Genetics and Genomics. Eds. I. Ionita-Laza, M. Krawczak, X. Lin, M. Nothnagel. Mathematisches Forschungsinstitut Oberwolfach Reports 52. DOI: 10.4171/OWR/2015/52

On posterior propriety for the Student-t linear regression model under Jeffreys priors

CA Vallejos and MFJ Steel (2013)

arXiv (CRiSM Working Paper 13-15)