Testis 4 Individual Clustering

UNDER CONSTRUCTION

Testis 4 Individual Clustering

Normalize Data

sobj <- FindVariableFeatures(
    sobj,
    selection.method = "vst",
    nfeatures = 2000,
    verbose = FALSE
)

top20 <- head(VariableFeatures(sobj), 20)

Scale Data

all_genes <- rownames(sobj)

sobj <- ScaleData(
    sobj,
    features = all_genes,
    vars.to.regress = "nCount_RNA",
    verbose = FALSE
)

Dimensionality Reduction

Dimensional Gene Loadings

Top Genes Heatmap

JackStraw

Elbow Plot

Dimension Selection

Clustering

ResolutionNum of Clusters
0.410
0.512
0.612
0.714
0.817
0.919
119
1.122
1.222

Look at marker genes

Spermatogonia

Spermatocytes

CySC

TE

PC

hub

Cluster Markers

clusterNum Biomarkers per Cluster
0105
1927
2536
3120
4560
51,162
6786
71,167
82,188
91,652
10719
111,090