So how many PCs should I consider for the downstream analyses like (find neighbors, find clusters and UMAP)? cond_integrated <- FindNeighbors(object = cond_integrated, dims = ?)Ĭond_integrated <- FindClusters(object = cond_integrated)Ĭond_integrated <- RunUMAP(cond_integrated, reduction = "pca", dims = ?)Īs I change the number of dimensions each time, I am getting different UMAP clustering. Do I need to consider the PCs which has only pvalue <0.05 (PC : 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14 and 15) for the downstream analyses?Īs per the Elbow plot, looks like at PC 34 the standard deviation is touching the ground and staying constant. How come even the PCs with p-value =1 is above the dashed line. As per the Jackstraw plot, ‘Significant’ PCs will show a strong enrichment of features with low p-values (solid curve above the dashed line).
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