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Date Time Novel guidelines help select optimal deconvolution method Biomedical scientists are increasingly using deconvolution methods, those used to computationally analyze the composition of complex mixtures of cells. One of their challenges is to select one method that is appropriate for their experimental conditions among nearly 50 available. To help with method selection, researchers at Baylor College of Medicine and the Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital have extensively evaluated 11 deconvolution methods that are based on RNA-sequencing (RNA-seq) data analysis, determining each method’s individual strengths and weaknesses in a variety of scenarios. From these analyses, the researchers derived guidelines that scientists can use to determine the deconvolution method that optimally fits their needs. The study appears in the journal Genome Biology.

United statesBaylor college of medicineHaijing jinZhandong liuChao family foundationDan duncan neurological research instituteHuffington foundationNational instituteCancer prevention research institute of texasBaylor collegeTexas childrenBioinformatics coreDan duncan neurological researchGeneral medical sciencesCancer prevention research instituteHouston endowment