use Annotated Robj including PBMC10x to remove NonCD4Tcells from Control and B cells from L4
Nasir Mahmood Abbasi
2025-01-13
#In this script I will I will remove Non T cells from PBMC
1. load libraries
2. Load Seurat Object
#Load Seurat Object merged from cell lines and a control(PBMC) after filtration
load("0-imp_Robj/All_Samples_Merged_with_10x_Azitmuth_Annotated.robj")
All_samples_MergedAn object of class Seurat
36752 features across 59355 samples within 5 assays
Active assay: RNA (36601 features, 0 variable features)
2 layers present: data, counts
4 other assays present: ADT, prediction.score.celltype.l1, prediction.score.celltype.l2, prediction.score.celltype.l3
2 dimensional reductions calculated: integrated_dr, ref.umap3. Cell type Distribution to check clusters
# We can apply it later on R obj to get these tables to compare it to decide about resolution.
# Azimuth l1
janitor::tabyl(All_samples_Merged@meta.data, predicted.celltype.l1, cell_line) predicted.celltype.l1 L1 L2 L3 L4 L5 L6 L7 PBMC PBMC_10x
B 0 0 12 131 35 85 121 1093 957
CD4 T 5771 3124 6351 5967 4914 4575 4634 5448 3639
CD8 T 13 25 0 1 4 5 3 814 1379
DC 0 0 1 4 29 12 41 71 196
Mono 0 0 1 13 3 0 5 754 3165
NK 38 2784 6 25 11 259 38 92 463
other 0 0 57 8 1025 208 487 19 46
other T 3 2 0 1 1 4 2 63 317# Azimuth l2
janitor::tabyl(All_samples_Merged@meta.data, predicted.celltype.l2, cell_line) predicted.celltype.l2 L1 L2 L3 L4 L5 L6 L7 PBMC PBMC_10x
ASDC 0 0 0 0 0 0 0 0 3
B intermediate 0 0 2 54 2 2 0 457 179
B memory 0 0 11 34 38 82 120 164 74
B naive 0 0 0 41 0 0 0 459 692
CD14 Mono 0 0 1 14 5 0 6 755 3042
CD16 Mono 0 0 0 0 0 0 0 2 124
CD4 CTL 0 0 0 0 0 0 0 16 1
CD4 Naive 0 0 0 7 0 0 0 524 1512
CD4 Proliferating 2461 2852 5452 5391 4732 4002 4115 0 6
CD4 TCM 3320 270 887 562 178 557 517 4609 1978
CD4 TEM 1 0 0 0 0 0 0 68 25
CD8 Naive 0 0 0 0 0 0 0 361 1012
CD8 Proliferating 0 0 0 0 0 1 1 0 0
CD8 TCM 1 16 0 0 0 0 0 286 174
CD8 TEM 1 8 0 0 2 3 1 181 195
cDC1 0 0 0 0 2 6 0 21 13
cDC2 0 0 0 4 11 3 35 52 124
dnT 2 3 0 1 2 5 2 38 29
gdT 0 0 0 0 0 0 0 26 67
HSPC 0 0 60 7 1035 213 490 17 12
ILC 0 0 0 1 0 0 0 3 3
MAIT 0 0 0 0 0 0 0 14 228
NK 0 0 0 1 0 0 0 89 444
NK Proliferating 38 2785 6 24 11 259 38 1 5
NK_CD56bright 0 0 0 0 0 0 0 1 15
pDC 0 0 0 0 0 0 0 0 56
Plasmablast 0 0 0 0 0 0 0 9 10
Platelet 0 0 0 0 0 0 0 1 31
Treg 1 1 9 9 4 15 6 200 108# Azimuth l3
janitor::tabyl(All_samples_Merged@meta.data, predicted.celltype.l3, cell_line) predicted.celltype.l3 L1 L2 L3 L4 L5 L6 L7 PBMC PBMC_10x
ASDC_pDC 0 0 0 0 0 0 0 0 4
B intermediate kappa 0 0 0 1 0 0 0 75 51
B intermediate lambda 0 0 2 48 4 2 3 371 129
B memory kappa 0 0 7 1 7 22 55 38 42
B memory lambda 0 0 3 41 7 29 26 131 30
B naive kappa 0 0 0 0 0 0 0 267 645
B naive lambda 0 0 0 37 0 0 0 192 48
CD14 Mono 0 0 1 15 9 0 22 755 3043
CD16 Mono 0 0 0 0 0 0 0 2 124
CD4 CTL 0 0 0 0 0 0 0 27 1
CD4 Naive 0 0 0 9 0 0 0 528 1525
CD4 Proliferating 2462 2852 5452 5391 4732 4003 4115 0 6
CD4 TCM_1 1932 6 6 35 0 7 3 4057 1449
CD4 TCM_2 652 250 870 516 165 536 482 265 144
CD4 TCM_3 436 12 4 6 13 7 26 267 359
CD4 TEM_1 1 0 0 0 0 0 0 4 8
CD4 TEM_2 0 0 0 0 0 0 0 17 17
CD4 TEM_3 0 0 0 0 0 0 0 50 1
CD8 Naive 0 0 0 0 0 0 0 291 969
CD8 Naive_2 0 0 0 0 1 1 0 63 47
CD8 Proliferating 0 0 0 0 0 1 1 0 0
CD8 TCM_1 0 8 0 0 0 0 0 137 115
CD8 TCM_2 298 6 0 0 0 0 0 80 43
CD8 TCM_3 0 1 0 0 0 0 0 77 17
CD8 TEM_1 0 0 0 0 0 0 0 91 67
CD8 TEM_2 0 0 0 0 0 1 0 32 62
CD8 TEM_3 0 0 0 0 0 0 0 17 15
CD8 TEM_4 0 0 0 0 0 0 0 2 12
CD8 TEM_5 0 0 0 0 0 0 0 27 1
CD8 TEM_6 1 10 0 0 1 1 1 1 36
cDC1 0 0 0 1 17 36 16 28 13
cDC2_1 0 0 0 1 1 0 4 2 40
cDC2_2 0 0 1 3 12 4 33 46 83
dnT_2 2 3 0 2 2 6 2 42 31
gdT_1 0 0 0 0 0 0 0 33 52
gdT_3 0 0 0 0 0 0 0 1 15
HSPC 0 0 62 7 1036 214 493 17 12
ILC 0 0 1 3 0 0 0 4 3
MAIT 0 0 0 0 0 0 0 16 229
NK Proliferating 38 2785 6 24 11 259 38 1 5
NK_1 0 0 0 0 0 0 0 42 7
NK_2 0 0 0 0 0 0 0 18 386
NK_3 0 0 0 0 0 0 0 22 20
NK_4 0 0 0 0 0 0 0 3 30
NK_CD56bright 0 0 0 0 0 0 0 1 16
pDC 0 0 0 0 0 0 0 0 56
Plasma 0 0 0 0 0 0 0 9 10
Platelet 0 0 0 0 0 0 0 1 31
Treg Memory 3 2 13 9 4 19 11 200 89
Treg Naive 0 0 0 0 0 0 0 4 244. filter cells just keep CD4 T cells
Cell type Distribution to check clusters
# We can apply it later on R obj to get these tables to compare it to decide about resolution.
# Azimuth l1
janitor::tabyl(filtered_seurat@meta.data, predicted.celltype.l1, cell_line) predicted.celltype.l1 L1 L2 L3 L4 L5 L6 L7 PBMC PBMC_10x
B 0 0 12 4 35 85 121 1093 957
CD4 T 5771 3124 6351 5967 4914 4575 4634 5448 3639
CD8 T 13 25 0 1 4 5 3 814 1379
DC 0 0 1 4 29 12 41 71 196
Mono 0 0 1 13 3 0 5 754 3165
NK 38 2784 6 25 11 259 38 92 463
other 0 0 57 8 1025 208 487 19 46
other T 3 2 0 1 1 4 2 63 317janitor::tabyl(filtered_seurat@meta.data, predicted.celltype.l2, cell_line) predicted.celltype.l2 L1 L2 L3 L4 L5 L6 L7 PBMC PBMC_10x
ASDC 0 0 0 0 0 0 0 0 3
B intermediate 0 0 2 1 2 2 0 457 179
B memory 0 0 11 1 38 82 120 164 74
B naive 0 0 0 0 0 0 0 459 692
CD14 Mono 0 0 1 14 5 0 6 755 3042
CD16 Mono 0 0 0 0 0 0 0 2 124
CD4 CTL 0 0 0 0 0 0 0 16 1
CD4 Naive 0 0 0 7 0 0 0 524 1512
CD4 Proliferating 2461 2852 5452 5391 4732 4002 4115 0 6
CD4 TCM 3320 270 887 562 178 557 517 4609 1978
CD4 TEM 1 0 0 0 0 0 0 68 25
CD8 Naive 0 0 0 0 0 0 0 361 1012
CD8 Proliferating 0 0 0 0 0 1 1 0 0
CD8 TCM 1 16 0 0 0 0 0 286 174
CD8 TEM 1 8 0 0 2 3 1 181 195
cDC1 0 0 0 0 2 6 0 21 13
cDC2 0 0 0 4 11 3 35 52 124
dnT 2 3 0 1 2 5 2 38 29
gdT 0 0 0 0 0 0 0 26 67
HSPC 0 0 60 7 1035 213 490 17 12
ILC 0 0 0 1 0 0 0 3 3
MAIT 0 0 0 0 0 0 0 14 228
NK 0 0 0 1 0 0 0 89 444
NK Proliferating 38 2785 6 24 11 259 38 1 5
NK_CD56bright 0 0 0 0 0 0 0 1 15
pDC 0 0 0 0 0 0 0 0 56
Plasmablast 0 0 0 0 0 0 0 9 10
Platelet 0 0 0 0 0 0 0 1 31
Treg 1 1 9 9 4 15 6 200 108janitor::tabyl(filtered_seurat@meta.data, predicted.celltype.l3, cell_line) predicted.celltype.l3 L1 L2 L3 L4 L5 L6 L7 PBMC PBMC_10x
ASDC_pDC 0 0 0 0 0 0 0 0 4
B intermediate kappa 0 0 0 0 0 0 0 75 51
B intermediate lambda 0 0 2 0 4 2 3 371 129
B memory kappa 0 0 7 0 7 22 55 38 42
B memory lambda 0 0 3 1 7 29 26 131 30
B naive kappa 0 0 0 0 0 0 0 267 645
B naive lambda 0 0 0 0 0 0 0 192 48
CD14 Mono 0 0 1 15 9 0 22 755 3043
CD16 Mono 0 0 0 0 0 0 0 2 124
CD4 CTL 0 0 0 0 0 0 0 27 1
CD4 Naive 0 0 0 9 0 0 0 528 1525
CD4 Proliferating 2462 2852 5452 5391 4732 4003 4115 0 6
CD4 TCM_1 1932 6 6 35 0 7 3 4057 1449
CD4 TCM_2 652 250 870 516 165 536 482 265 144
CD4 TCM_3 436 12 4 6 13 7 26 267 359
CD4 TEM_1 1 0 0 0 0 0 0 4 8
CD4 TEM_2 0 0 0 0 0 0 0 17 17
CD4 TEM_3 0 0 0 0 0 0 0 50 1
CD8 Naive 0 0 0 0 0 0 0 291 969
CD8 Naive_2 0 0 0 0 1 1 0 63 47
CD8 Proliferating 0 0 0 0 0 1 1 0 0
CD8 TCM_1 0 8 0 0 0 0 0 137 115
CD8 TCM_2 298 6 0 0 0 0 0 80 43
CD8 TCM_3 0 1 0 0 0 0 0 77 17
CD8 TEM_1 0 0 0 0 0 0 0 91 67
CD8 TEM_2 0 0 0 0 0 1 0 32 62
CD8 TEM_3 0 0 0 0 0 0 0 17 15
CD8 TEM_4 0 0 0 0 0 0 0 2 12
CD8 TEM_5 0 0 0 0 0 0 0 27 1
CD8 TEM_6 1 10 0 0 1 1 1 1 36
cDC1 0 0 0 1 17 36 16 28 13
cDC2_1 0 0 0 1 1 0 4 2 40
cDC2_2 0 0 1 3 12 4 33 46 83
dnT_2 2 3 0 2 2 6 2 42 31
gdT_1 0 0 0 0 0 0 0 33 52
gdT_3 0 0 0 0 0 0 0 1 15
HSPC 0 0 62 7 1036 214 493 17 12
ILC 0 0 1 3 0 0 0 4 3
MAIT 0 0 0 0 0 0 0 16 229
NK Proliferating 38 2785 6 24 11 259 38 1 5
NK_1 0 0 0 0 0 0 0 42 7
NK_2 0 0 0 0 0 0 0 18 386
NK_3 0 0 0 0 0 0 0 22 20
NK_4 0 0 0 0 0 0 0 3 30
NK_CD56bright 0 0 0 0 0 0 0 1 16
pDC 0 0 0 0 0 0 0 0 56
Plasma 0 0 0 0 0 0 0 9 10
Platelet 0 0 0 0 0 0 0 1 31
Treg Memory 3 2 13 9 4 19 11 200 89
Treg Naive 0 0 0 0 0 0 0 4 243.Save the Seurat object as an Robj file
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