TAPE
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Deep learning-based tissue compositions and cell-type-specific gene expression analysis with tissue-adaptive autoencoder (TAPE)
Thank you for sharing the script and the input pbmc_data.h5ad. I was able to reproduce the good performance with the script TAPE_realbulk.ipynb. However, when I extracted the input training and...
Hi, After reading the tutorials carefully, I still feel confused how to prepare the input data. In most cases, users want to get cell-type fractions from tumor bulk RNA-seq data...
Thanks for this wonderful tool. I have one question: when I simulated Psedobulk data using sc-RNAseq data, I just check the function "generate_simulated_data", it looks as print('Normalizing raw single cell...
No need to calculate the gene len if the file already provided.
Dear Sir or Madam, I am performing a benchmarking of deconvolution methods and I need to run TAPE and Scaden many times on multiple datasets. I wanted to know if...
Hello, I'm glad to learn this excellent paper. There is a problem with the running of this paper, which takes up your time. I hope to get your reply. After...
Hi, I've been using TAPE to deconvolve some cases from the TCGA dataset using reference single-cell sequencing (from 100-200 cells per phenotype, from 6 different phenotypes). It works well, and...
Hi, thanks for the nice paper and code. As I understand it, the decoder function reconstructs the bulk RNA-seq input B from X (the predicted cell fractions). The learnt weights...
Hello, I'm glad to learn this excellent paper. There is a problem with the running of this paper, which takes up your time. I hope to get your reply. I...
I am working with the GSE87544. It has 14k cells approx. The sampling is taking more than couple of hours. how to use GPU to accelerate this? I am unable...