Analytical Report
D04701A4
  • Summary
  • Square Bin
  • Cell Bin
  • Image
Cell Bin Statistics
Cell Count
Number of cells
Mean/Median Cell Area
Mean/Median cell area (pixel)
Mean/Median Gene Type
Mean/Median gene types per cell
Mean/Median MID
Mean/Median MID count per cell
Cell Count
361,002
Mean Cell Area
333
Median Cell Area
294
Mean Gene Type
57.52
Median Gene Type
44
Mean MID
184
Median MID
135
Cell Bin
Violin plots show the distribution of deduplicated MID count, gene type and cell area in each bin
Clustering
(left) Clustering spots (cell bin) under tissue covered region with the Leiden algorithm
(right) UMAP projections of spots (cell bin) colored by automated clustering. Spots in the short distance are assigned with the same color have similar gene expression profile.
Tissue Plot with Spots (cellbin)
UMAP Projection of Spots (cellbin)
Top Markers by Cluster
The goal of the differential expression analysis is to identify markers that are more highly expressed in a cluster than the rest of the sample. For each marker, a differential expression test was run between each cluster and the remaining sample. An estimate of the log2 ratio of expression in a cluster to that in other coordinates is Log2 fold-change (L2FC). A value of 1.0 denotes a 2-fold increase in expression within the relevant cluster. Based on a negative binomial test, the p-value indicates the expression difference's statistical significance. The Benjamini-Hochberg method has been used to correct the p-value for multiple testing. Additionally, the top N features by L2FC for each cluster were kept after features in this table were filtered by (Mean UMI counts > 1.0). Grayed-out features have an adjusted p-value >= 0.10 or an L2FC < 0. N (ranges from 1 to 50) is the number of top features displayed per cluster, which is set to limit the amount of table entries displayed to 10,000. N=%10,000/K^2 where K is the number of clusters. Click on a column to sort by that value, or search a gene of interest.