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Statistical Applications in Genetics and Molecular Biology|April 4, 2007
Using duplicate genotyped data in genetic analyses: testing association and estimating error ratesNathan L Tintle, Derek Gordon, Francis J McMahon, et al.
Statistical Applications in Genetics and Molecular Biology|April 4, 2007
Super learning: an application to the prediction of HIV-1 drug resistanceSandra E Sinisi, Eric C Polley, Maya L Petersen, et al.
Statistical Applications in Genetics and Molecular Biology|May 4, 2007
A Bayesian model of AFLP marker evolution and phylogenetic inferenceRuiyan Luo, Andrew L Hipp, Bret Larget
Statistical Applications in Genetics and Molecular Biology|October 20, 2006
Reader's reaction to "Dimension reduction for classification with gene expression microarray data" by Dai et al (2006)Anne-Laure Boulesteix
Statistical Applications in Genetics and Molecular Biology|October 25, 2019
Clustering methods for single-cell RNA-sequencing expression data: performance evaluation with varying sample sizes and cell compositionsAslı Suner
Statistical Applications in Genetics and Molecular Biology|August 11, 2021
Low variability in the underlying cellular landscape adversely affects the performance of interaction-based approaches for conducting cell-specific analyses of DNA methylation in bulk samplesRichard Meier, Emily Nissen, Devin C Koestler
Statistical Applications in Genetics and Molecular Biology|October 14, 2015
Sample size reassessment for a two-stage design controlling the false discovery rateSonja Zehetmayer, Alexandra C Graf, Martin Posch
Statistical Applications in Genetics and Molecular Biology|October 14, 2015
A model selection criterion for model-based clustering of annotated gene expression dataMélina Gallopin, Gilles Celeux, Florence Jaffrézic, et al.
Statistical Applications in Genetics and Molecular Biology|March 19, 2016
Testing differentially expressed genes in dose-response studies and with ordinal phenotypesElizabeth Sweeney, Ciprian Crainiceanu, Jan Gertheiss
Statistical Applications in Genetics and Molecular Biology|March 2, 2016
What if we ignore the random effects when analyzing RNA-seq data in a multifactor experimentShiqi Cui, Tieming Ji, Jilong Li, et al.
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