Hello all,
can you please give a list of packages that have been developed to apply machine learning models on RNAseq data?
Thanks
Sara
Hello all,
can you please give a list of packages that have been developed to apply machine learning models on RNAseq data?
Thanks
Sara
If you go to the package listing page, on the left hand side are a set of 'biocViews', one of which is StatisticalMethod. Machine learning is a broad category that encompasses several of the methods there, but you should be able to look through the choices and see which package(s) are applicable.
Sara
perhaps you are referring to characteristics of RNA-Seq data that make it necessary to "preprocess" the data before applying regular ML methods: normalisation for library size and transformation to make the data less skewed and less heteroskedastic. Have a look at the variance stabilizing transformation in DESeq2. It's also described in the vignette.
Hope this helps
Wolfgang
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There is a bioconductor package "MLInterfaces" that contains interfaces to R machine learning procedures such as svm, random forest, knn, and etc. Those procedures are built for general purpose, yet you might find it quite helpful for expression data.