
pmid: 19679825
Ranked gene lists are highly instable in the sense that similar measures of differential gene expression may yield very different rankings, and that a small change of the data set usually affects the obtained gene list considerably. Stability issues have long been under-considered in the literature, but they have grown to a hot topic in the last few years, perhaps as a consequence of the increasing skepticism on the reproducibility and clinical applicability of molecular research findings. In this article, we review existing approaches for the assessment of stability of ranked gene lists and the related problem of aggregation, give some practical recommendations, and warn against potential misuse of these methods. This overview is illustrated through an application to a recent leukemia data set using the freely available Bioconductor package GeneSelector.
Models, Statistical, Models, Genetic, Gene Expression Profiling, Databases, Genetic, Algorithms, Software, Oligonucleotide Array Sequence Analysis, 510
Models, Statistical, Models, Genetic, Gene Expression Profiling, Databases, Genetic, Algorithms, Software, Oligonucleotide Array Sequence Analysis, 510
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