pcbi.1011935.s005.docx (15.17 kB)
Mean and median ARI presented by STGIC on the DLPFCs dataset with various numbers of principal components around 15 and 50.
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posted on 2024-02-28, 18:37 authored by Chen Zhang, Junhui Gao, Hong-Yu Chen, Lingxin Kong, Guangshuo Cao, Xiangyu Guo, Wei Liu, Bin Ren, Dong-Qing Wein_components: number of principal components; all_mean: mean ARI resulting from PCA with all genes; all_median: median ARI resulting from PCA with all genes; hvg_mean: mean ARI resulting from PCA with the top 3000 highly variable genes; hvg_median: median ARI resulting from PCA with the top 3000 highly variable genes.
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transcriptionally similar togetherkullback – leiblerhigh confidence pseudogat ), feddepicting fine structuresdilated convolution frameworkvirtual image convertedgraph attention networkgene expression informationspatial continuity lossgraph convolution networkadaptive graph convolutionstgic attains statediv >< pg c clustering employs spatialimage convolutiontranscription informationspatial transcriptomicspatial domainspatial distancespatial coordinatesranscriptomic clusteringclustering performanceweight valuestraining objectivesupervision realizedset appropriatelyseq dataregular latticesoften usedmarker geneskernel sizeskernel centersfeature extractiondlpfc ).dilation ratescorresponding elementsbetter guidedbenchmark datasetbased method
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