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5 kwi 2024 · To visualize the geometry of all genes, we convert pairwise gene–gene Wasserstein distances into gene–gene affinities and use diffusion map to get a low-dimensional representation of genes.
In this tutorial, we demonstrate gene-gene distance computation by selecting the genes expressed by 1% to 50% of cells among the top 500 variable genes. The expected running time for this computation is approximately 1 to 3 minutes.
24 gru 2022 · Map distance tells the expected number of crossovers between two loci and can be used as a proxy of recombination; the longer the map distance the higher the recombination frequency.
1 lut 2021 · The first cost function exploits a gene embedding, called gene2vec, which is used to map each gene to a high dimensional vector: the cost of moving a unit of mass of gene expression from a gene...
* Step 3. Generate a low-dimensional representation of genes (using Diffusion Map by default) based on the gene-gene Wasserstein distance matrix. Identify gene trajectories in a sequential manner. * Step 4. Determine the order of genes along each gene trajectory.
This paper introduces the Gene Mover’s Distance, a measure of similarity between a pair of cells based on their gene expression profiles obtained via single-cell RNA sequencing. The underlying idea of the proposed distance is to interpret the gene expression array of a single cell as a discrete probability measure.
A genetic map (or recombination map) is a representation of the linear order of genes (or loci), and their relative distances determined by crossover frequency, along a chromosome. The fact that such linear maps can be constructed supports the concept of genes being arranged in a fixed, linear order along a single duplex of DNA for each chromosome.
