Introduction

This report details the downstream analysis of the filtered single-cell RNA-seq data, starting from the quality-controlled SingleCellExperiment object (sce_filtered). The analysis includes:

  1. Normalization of counts.
  2. Identification of highly variable genes (HVGs).
  3. Dimensionality reduction using Principal Component Analysis (PCA).
  4. Cell clustering using graph-based methods.
  5. Visualization using UMAP.
  6. Identification of marker genes for each cluster.

1. Load Filtered Data

We load the sce_filtered object generated in the previous QC step.

The filtered object contains 32057 genes and 542 cells.

2. Normalization

We normalize the raw counts to account for differences in library size and capture efficiency between cells. We use the computeLibraryFactors function from scran followed by logNormCounts from scater.

The logcounts assay now contains normalized expression values suitable for downstream analysis.

3. Feature Selection (Highly Variable Genes)

We focus downstream analysis on genes that exhibit high biological variability across cells.

We selected the top 2500 HVGs for dimensionality reduction.

4. Dimensionality Reduction (PCA)

We perform PCA on the log-normalized counts, using only the selected HVGs.

PCA was performed using the HVGs. The variance explained plot helps decide how many PCs capture significant biological variation. We will proceed using the top 20 PCs.

5. Clustering

We perform graph-based clustering on the PCA reduced dimensions.

6. Visualization (UMAP)

We use UMAP to visualize the high-dimensional data in two dimensions.

The UMAP plot shows the separation of the identified cell clusters in two dimensions.

7 Identification of Cell Types Based on Marker Expression

We identify marker genes for each cluster using scran::findMarkers.

Marker genes were identified for each cluster.

Cluster 1

Top 30 Upregulated Markers for Cluster 1
Gene LogFC PValue
sox7 7.067 < 1e-10
kdrl 6.945 < 1e-10
pecam1 6.500 1.8e-10
clec14a 6.281 < 1e-10
cdh5 6.259 6.4e-10
cdc42 6.236 0.0041
pfn2 6.200 0.0027
ifi30 6.176 0.0029
sox18 6.140 < 1e-10
ramp2 6.128 4.0e-07
rasip1 6.126 < 1e-10
cldn5b 6.105 < 1e-10
tie1 6.078 < 1e-10
fscn1a 6.073 1.2e-07
palm1a 6.054 < 1e-10
etv2 6.052 7.4e-10
hlx1 6.029 0.0033
dll4 5.883 < 1e-10
ptbp1a 5.774 0.0025
elmo1 5.731 0.0039
snrpb 5.709 0.0047
mmp14b 5.676 7.1e-10
kirrel3l 5.663 < 1e-10
robo4 5.648 2.1e-08
crip2 5.642 5.3e-08
capns1b 5.617 0.0054
wu:fc21g02 5.600 0.0051
ugt1b1 5.590 < 1e-10
flt4 5.573 < 1e-10
fstl1b 5.565 0.0033

Cluster 2

Top 30 Upregulated Markers for Cluster 2
Gene LogFC PValue
rad21a 7.098 0.00097
anp32a 6.753 0.00156
setb 6.581 0.00160
eif2s2 6.473 0.00095
tnrc6a 6.377 < 1e-10
eif3ja 6.295 < 1e-10
smarca4a 6.282 0.00216
dnmt1 6.278 2.7e-10
rpl5a 6.172 0.01074
h3f3b.1 6.046 0.00252
cnbpa 6.045 0.00228
znfl2a 5.983 5.4e-05
ewsr1b 5.926 0.00237
slc11a2 5.903 5.0e-05
psma1 5.889 0.00319
snrpb 5.886 0.00371
hnrnpl2 5.836 0.00330
hnrnpl 5.778 0.00350
uqcrc1 5.770 0.00394
atf4b 5.754 0.01713
epn1 5.748 2.2e-09
psmc3 5.739 0.00246
tyms 5.724 1.4e-09
primpol 5.701 3.1e-07
krcp 5.687 6.2e-07
slc4a1a 5.686 0.01267
ska3 5.684 0.00352
si:dkeyp-113d7.1 5.665 < 1e-10
ccng1 5.664 0.01819
psma2 5.650 < 1e-10

Cluster 3

Top 30 Upregulated Markers for Cluster 3
Gene LogFC PValue
zgc:153499 7.965 < 1e-10
cnksr2b 7.619 < 1e-10
ctdnep1b 6.742 < 1e-10
cyp1a 5.700 < 1e-10
ddit4 5.546 < 1e-10
ncalda 5.228 < 1e-10
BX324216.3 5.072 < 1e-10
tanc1b 5.034 < 1e-10
eif1b 4.980 < 1e-10
si:dkey-229d11.5 4.911 < 1e-10
sox19b 4.793 < 1e-10
h1m 4.782 < 1e-10
qdpra 4.694 6.8e-09
NC_002333.4 4.371 < 1e-10
si:dkey-90l23.1 4.180 < 1e-10
tmsb4x 4.064 3.5e-06
sall4 4.007 < 1e-10
zp3e 3.898 < 1e-10
rcbtb2 3.702 3.5e-07
LO017877.2 3.480 < 1e-10
si:dkey-229d11.3 3.357 < 1e-10
fhod1 3.254 0.00068
nkx2.2a 3.177 1.1e-10
tpm1 3.143 2.8e-05
scarb1 3.091 1.3e-08
zgc:173544 2.917 2.9e-08
ednraa 2.906 0.47197
ptenb 2.898 1.4e-05
larp4ab 2.816 0.00018
BX323564.1 2.762 1.5e-05

Cluster 4

Top 30 Upregulated Markers for Cluster 4
Gene LogFC PValue
flt4 7.072 < 1e-10
CABZ01058261.1 6.951 < 1e-10
rad21a 6.945 0.0012
smc4 6.817 < 1e-10
clec14a 6.701 < 1e-10
cdh5 6.701 < 1e-10
si:dkey-30c15.10 6.635 < 1e-10
elmo1 6.593 0.0015
tie1 6.590 < 1e-10
si:ch211-14k19.8 6.538 < 1e-10
pecam1 6.470 1.3e-10
ptbp1a 6.389 0.0012
cldn5b 6.377 < 1e-10
rasip1 6.377 < 1e-10
aplnrb 6.372 3.3e-10
sox18 6.356 < 1e-10
cdc42 6.352 0.0035
eif3ba 6.329 0.0023
myct1a 6.289 < 1e-10
etv2 6.276 2.5e-10
pfn2 6.274 0.0022
kirrel3l 6.264 < 1e-10
mrc1a 6.246 < 1e-10
lsp1b 6.236 0.0021
tjp1a 6.189 < 1e-10
ramp2 6.169 2.8e-07
si:dkey-28n18.9 6.139 < 1e-10
plvapb 6.118 5.8e-10
ifi30 6.109 0.0030
arpc2 6.100 0.0029

Cluster 5

Top 30 Upregulated Markers for Cluster 5
Gene LogFC PValue
lyz 7.201 < 1e-10
abcc13 6.932 < 1e-10
neu3.3 6.634 < 1e-10
gusb 6.440 0.0015
npsn 6.065 < 1e-10
fgfbp2b 5.708 < 1e-10
hyal4 5.667 < 1e-10
si:ch1073-429i10.1 5.413 < 1e-10
clrn3 5.367 < 1e-10
lsp1b 5.096 0.0074
tert 4.980 < 1e-10
pald1a 4.915 0.0187
mtr 4.892 4.2e-09
FO681286.1 4.802 2.7e-09
ednraa 4.793 0.0696
mmp13a 4.734 3.4e-09
mpx 4.639 1.8e-08
zgc:153499 4.577 < 1e-10
FO704772.3 4.479 0.0687
slc38a3a 4.402 1.5e-07
pfkmb 4.390 1.6e-09
RANBP2 4.372 0.0257
hbs1l 4.285 4.4e-08
cotl1 4.267 0.1847
lcp1 4.227 8.4e-06
dusp5 4.169 0.1340
c1qtnf6b 4.089 5.6e-07
CR384075.1 4.052 4.4e-06
zgc:92140 3.951 0.0556
coro1a 3.859 4.5e-07

Cluster 6

Top 30 Upregulated Markers for Cluster 6
Gene LogFC PValue
he1.2 10.811 < 1e-10
he1.1 10.788 1.2e-09
actc1b 10.588 < 1e-10
pvalb1 10.057 < 1e-10
krt4 9.328 < 1e-10
pvalb2 9.098 < 1e-10
krt91 9.064 1.8e-10
fabp11a 9.008 3.6e-09
si:dkey-239j18.2 8.918 2.2e-08
krtt1c19e 8.914 < 1e-10
mylz3 8.894 < 1e-10
zgc:174855 8.688 2.0e-08
ckmb 8.592 < 1e-10
zgc:174154 8.491 4.1e-09
mylpfa 8.451 < 1e-10
rbp4 8.315 < 1e-10
sall4 8.006 8.9e-10
ctrb1 7.824 0.0017
atp2a1 7.729 0.0019
si:dkey-269i1.4 7.715 0.0016
zgc:153499 7.665 < 1e-10
si:dkey-269i1.4 7.599 0.0017
ctslb 7.572 0.0017
prss59.2 7.169 0.0018
si:dkey-229d11.3 7.148 0.0017
cyt1l 7.107 0.0018
ctdnep1b 6.975 < 1e-10
prss1 6.857 0.0180
cnksr2b 6.793 0.0035
h1m 6.637 0.0058

Cluster 7

Top 30 Upregulated Markers for Cluster 7
Gene LogFC PValue
lcp1 9.948 < 1e-10
coro1a 9.671 < 1e-10
mrps15 9.167 < 1e-10
tktb 8.940 < 1e-10
arhgdig 8.884 < 1e-10
myh9a 8.814 < 1e-10
pkma 8.781 < 1e-10
scinlb 8.730 < 1e-10
gpia 8.672 < 1e-10
mmp9 8.658 < 1e-10
rac2 8.220 < 1e-10
dusp2 8.200 < 1e-10
mpx 8.010 < 1e-10
arpc4 7.992 < 1e-10
gsr 7.915 < 1e-10
taldo1 7.799 < 1e-10
CU499336.2 7.776 < 1e-10
cebpb 7.645 < 1e-10
ncf1 7.578 < 1e-10
elovl1b 7.559 < 1e-10
spi1b 7.534 < 1e-10
cfbl 7.461 1.3e-10
si:ch1073-429i10.1 7.441 2.3e-09
laptm5 7.431 < 1e-10
pgk1 7.423 < 1e-10
itgb2 7.411 < 1e-10
myh11a 7.396 < 1e-10
aldh8a1 7.392 < 1e-10
fcer1gl 7.304 < 1e-10
mapre1a 7.231 < 1e-10

8 Heatmap of Specific Markers

9 Violin Plots for Specific Markers