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Nowadays, I am trying to calculate Pearson correlation values between two genes of my interest from single-cell RNA-data (features.tsv, barcodes.tsv, and matrix.mtx files) which are obtained from the 10xgenomics cellranger.

FYI, The filtered_feature_bc_matrix includes an aggregated population of tumor-infiltrating immune cells that are derived from 6 different syngeneic mouse tumors (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE121861). I downloaded fastq files and ran "cellranger count" and "cellranger aggr" commands to obtain combined data.

My strategy includes the use of the "feature scatter" function deposited in the library(Seurat). Finally, I ended up getting results below.

FeatureScatter plot

My question is that can we select a specific cluster(s) or identity on this plot? For example, I want to see correlation values in cluster 2 only. The usage of Feature scatter is as follows.

FeatureScatter( object, feature1, feature2, cells = NULL, group.by = NULL, cols = NULL, pt.size = 1, shape.by = NULL, span = NULL, smooth = FALSE, combine = TRUE, slot = "data" )

Do you know how to get the Pearson correlation of my two genes using Seurat? This is the best I can do.

Thank you.

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1 Answer 1

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You can use the cells argument to only display the data for a specific subset of cells.

For example to extract the values for a cluster 2:

# The cluster identity is stored in the meta.data
# In this example there is a clustering column called "RNA_snn_res.0.7" 
# but any metadata column can be used

clust2.cells <- rownames([email protected][Seurat.data$RNA_snn_res.0.7 == 2, ])

FeatureScatter(Seurat.data, feature1 = "gene_A", feature2 = "gene_B", cells = clust2.cells)
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  • $\begingroup$ Thank you so much. $\endgroup$
    – raiora
    Commented May 20, 2020 at 14:06
  • $\begingroup$ You can also subset your Seurat object within the call to FeatureScatter, such as FeatureScatter(subset(Seurat.data, idents = "2"), "gene_A", "gene_B") $\endgroup$
    – Dave Ross
    Commented Aug 11, 2020 at 17:45

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