swCAM

swCAM: Unsupervised Sample-wise Deconvolution, a tool for estimation of subtype-specific expressions in individual samples with unsupervised sample-wise deconvolution. We report a sample-wise Convex Analysis of Mixtures (swCAM) method that can estimate subtype proportions and subtype-specific expressions in individual samples from bulk tissue transcriptomes. We extend our previous CAM framework (https://github.com/Lululuella/debCAM) to include a new term accounting for between-sample variations and formulate swCAM as a nuclear-norm and l_(2,1)-norm regularized low-rank matrix factorization problem. We determine hyperparameter value using a cross-validation scheme with random entry exclusion and obtain swCAM solution using an efficient alternating direction method of multipliers. The swCAM is implemented in open-source R scripts.