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MOSAIC / MicrOSAtellite Instability Classifier
Predicts microsatellite instability (MSI) status. MOSAIC is a weighted-tree microsatellite instability classifier that ascertains MSI status from tumor–normal tissue pairs examined with exome-sequencing data. The software was used to assigned MSI status for 5,930 tumor exomes from 18 cancer types. As it corrects for class imbalance in its cross-validation training procedure, MOSAIC allows predictions in new cancer types to be made without prior assumption about the expected prevalence of MSI-H tumors.
MIRMMR / Microsatellite Instability Regression using Methylation and Mutations in R
Classifies microsatellite instability (MSI) status. MIRMMR trains logistic regression models using DNA methylation and mutation information from mismatch repair (MMR) pathway genes. It reports a score between zero and one, so a suitable cutoff to separate MSI-High samples from Not-MSI-High samples is necessary. This tool offers a promising new option for integrated MSI diagnosis that does not rely on measuring microsatellites.
MSIseq
Allows users to detect microsatellite instability (MSI) in somatic mutation data from whole exome sequencing. MSIseq provides two main functions which implement next-generation sequencing (NGS) classifier. The first one, MSIseq.train(), generates a classifier from training data. The second function classifies tumors using classifiers generated by MSIseq.train(). It also includes a helper function, Compute.input.variables (), to generate the input variables needed by these two functions.
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