Tissue-AdaPtive autoEncoder (TAPE)

TAPE is a deep-learning tool for reserchers to deconvolve bulk RNA-seq data to estimate the cell-type fractions and the cell-type-specific gene expression. This model is developed by computational biology group at CUHK with help from other institutions and groups.

For more information about TAPE, the related article Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis is accepted by Nature Communications. The concrete usage about TAPE will be introduced in the Installation and Usage part. Other supplementary information about Datasets and Experiments may also be helpful to you.