a spatial deconvolution method based on deep learning frameworks, which converts bulk transcriptomes into spatially resolved single-cell expression profiles
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Updated
Mar 22, 2023 - Jupyter Notebook
a spatial deconvolution method based on deep learning frameworks, which converts bulk transcriptomes into spatially resolved single-cell expression profiles
This repository contains the code developed for the analysis of tumour mass dormancy, immunological and angiogenic dormancy across cancers from the Cancer Genome Atlas (TCGA).
DETOPT is a combinatorial optimization method for DETermining Optimal Placement in Tumor progression history of SNVs from the genomic regions impacted by CNAs using multi-sample bulk DNA sequencing data
This is an automated workflow pipeline for analyzing and processing Bulk-RNA seq data, implemented primarily in bash, python and R, and wrapped in a NextFlow workflow to characterize the gene landscape in the samples.
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