Changes between Version 21 and Version 22 of SOP/scRNA-seq

Timestamp:

08/25/20 15:59:31 (5 years ago)

Author:

ibarrasa

Comment:

--

SOP/scRNA-seq

@@ -91 +91 @@
 num.variable.features.to.find = 2000
 all_Filt <- FindVariableFeatures(object = all_Filt, selection.method = "vst", nfeatures = num.variable.features.to.find)
-
 }}}
 === Scale data === 
@@ -100 +99 @@
 
 === Perform and visualize dimensional analysis === 
+Perform principal components analysis
 {{{
 all_Filt <- RunPCA(object = all_Filt, features = VariableFeatures(object = all_Filt))
+pdf("./PCAPlot.pdf", w=11, h=8.5)
+DimPlot(object = all_Filt, reduction = "pca")
+DimPlot(object = all_Filt, dims = c(3, 4), reduction = "pca")
+dev.off()
+
+pdf("ElbowPlot.pdf", w=11, h=8.5)
+ElbowPlot(object = all_Filt)
+dev.off()
+}}}
+Based on the elbow plot decide how many components to use to run UMAP, tSNE and the Louvain clustering.
+Run non-linear dimensional reduction (UMAP/tSNE)
+{{{
+all_Filt <- RunUMAP(object = all_Filt, dims = 1:20)
+all_Filt <- RunTSNE(object = all_Filt, dims = 1:20)
+pdf("./UMAP_colorByExp.pdf", w=11, h=8.5)
+DimPlot(object = all_Filt, reduction = "umap")
+dev.off()
+pdf("./TSNE_colorByExp.pdf", w=11, h=8.5)
+TSNEPlot(object = all_Filt)
+dev.off()
 }}}
 === Partition cells into clusters === 
-
+Run Louvain clustering using different resolutions to then decide which one to follow up on for further analysis.
+The resolution chosen depends on the granularity we want to work with and the cell heterogeneity.
+{{{
+all_Filt <- FindNeighbors(object = all_Filt, dims = 1:20)
+all_Filt <- FindClusters(object = all_Filt, resolution = 0.5)
+pdf("./UMAP_colorByCluster_Res0.5.pdf", w=11, h=8.5)
+UMAPPlot(object = all_Filt, label= TRUE)
+dev.off()
+all_Filt <- FindClusters(object = all_Filt, resolution = 0.4)
+pdf("./UMAP_colorByCluster_Res0.4.pdf", w=11, h=8.5)
+UMAPPlot(object = all_Filt, label= TRUE)
+dev.off()
+all <- FindClusters(object = all_Filt, resolution = 0.3)
+pdf("./UMAP_colorByCluster_Res0.3.pdf", w=11, h=8.5)
+UMAPPlot(object = all_Filt, label= TRUE)
+dev.off()
+}}}
+The clustering at different resolutions are store in all_Filt$RNA_snn_res.0.3 all_Filt$RNA_snn_res.0.4 all_Filt$RNA_snn_res.0.5
 === Identify genes that differentially expressed between samples or clusters ===