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Risk-conscious correction of batch effects: maximising information extraction...
Background Batch effects are a persistent and pervasive form of measurement noise which undermine the scientific utility of high-throughput genomic datasets. At their most... -
Tilting the Lasso by Knowledge-Based Post-Processing
Background It is useful to incorporate biological knowledge on the role of genetic determinants in predicting an outcome. It is, however, not always feasible to fully elicit... -
Exact p-values for pairwise comparison of Friedman rank sums, with applicatio...
Background The Friedman rank sum test is a widely-used nonparametric method in computational biology. In addition to examining the overall null hypothesis of no significant... -
Combining location-and-scale batch effect adjustment with data cleaning by la...
Background In the context of high-throughput molecular data analysis it is common that the observations included in a dataset form distinct groups; for example, measured at... -
Evaluation of logistic regression models and effect of covariates for case–co...
Background Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression... -
An Eigenvalue test for spatial principal component analysis
AbstractBackgroundThe spatial Principal Component Analysis (sPCA, Jombart 2008) is designed to investigate non-random spatial distributions of genetic variation. Unfortunately,... -
MetaDiff: differential isoform expression analysis using random-effects meta-...
Background RNA sequencing (RNA-Seq) allows an unbiased survey of the entire transcriptome in a high-throughput manner. A major application of RNA-Seq is to detect differential... -
Handling missing rows in multi-omics data integration: multiple imputation in...
Background In omics data integration studies, it is common, for a variety of reasons, for some individuals to not be present in all data tables. Missing row values are...
