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  "Title": "RNA-Seq Profile Classifier",
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  "Author": "Ville-Petteri Makinen [aut, cre]",
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  "Description": "We developed a lightweight machine learning tool for RNA\nprofiling of acute lymphoblastic leukemia (ALL), however, it\ncan be used for any problem where multiple classes need to be\nidentified from multi-dimensional data. The methodology is\ndescribed in Makinen V-P, Rehn J, Breen J, Yeung D, White DL\n(2022) Multi-cohort transcriptomic subtyping of B-cell acute\nlymphoblastic leukemia, International Journal of Molecular\nSciences 23:4574, <doi:10.3390/ijms23094574>. The classifier\ncontains optimized mean profiles of the classes (centroids) as\nobserved in the training data, and new samples are matched to\nthese centroids using the shortest Euclidean distance.\nCentroids derived from a dataset of 1,598 ALL patients are\nincluded, but users can train the models with their own data as\nwell. The output includes both numerical and visual\npresentations of the classification results. Samples with mixed\nfeatures from multiple classes or atypical values are also\nidentified.",
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