Article

InGene: Finding influential genes from embeddings of nonlinear dimension reduction techniques

2023-06-21

Abstract excerpt

We introduce InGene , the first of its kind, fast and scalable non-linear, unsupervised method for analyzing single-cell RNA sequencing data (scRNA-seq). While non-linear dimensionality reduction techniques such as t-SNE and UMAP are effective at visualizing cellular sub-populations in low-dimensional space, they do not identify the specific genes that influence the transformation. InGene addresses this issue by...

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Literature Corpus work: cfe5ed6f-a722-5ed5-9053-0bcb45b1afa0
DOI: 10.1101/2023.06.19.545592

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