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By finding recombination frequencies for many gene pairs, we can make linkage maps that show the order and relative distances of the genes on the chromosome.
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.
29 kwi 2020 · Overall, we have shown the capabilities of SpaOTsc to (1) map between scRNA-seq data and spatial data, (2) infer spatial distances between single cells, (3) quantitatively compare spatial...
Compute pairwise graph-based Wasserstein distance between gene distributions, which quantifies the minimum cost of transporting the distribution of a given gene into the distribution of another gene in the cell graph.
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 our framework, we have designed two strategies to accelerate the computation based on 1) cell graph coarse-graining, and 2) gene graph sparsification. Briefly, cell graph coarse-graining aims to reduce the cell number by aggregating nearest cells into “meta-cells”.
A genetic map shows the map distance, in cM, that separates any two loci, and the position of these loci relative to all other mapped loci. The genetic map distance is roughly proportional to the physical distance, i.e., the amount of DNA between two loci.
