2. Load Seurat Object
#Load Seurat Object merged from cell lines and a control(PBMC) after filtration
SS_All_samples_Merged <- load("/home/bioinfo/0-imp_Robj/Harmony_integrated_All_samples_Merged_with_PBMC10x_with_harmony_clustering.Robj")
All_samples_Merged
An object of class Seurat
64169 features across 59355 samples within 6 assays
Active assay: SCT (27417 features, 3000 variable features)
3 layers present: counts, data, scale.data
5 other assays present: RNA, ADT, prediction.score.celltype.l1, prediction.score.celltype.l2, prediction.score.celltype.l3
6 dimensional reductions calculated: integrated_dr, ref.umap, pca, umap, harmony, umap.harmony
DimPlot(All_samples_Merged, group.by = "cell_line", label = T, label.box = T)

3. Pre-Analysis using FeaturePlot
All_samples_Merged <- NormalizeData(All_samples_Merged, normalization.method = "CLR", margin = 1, assay = "ADT")
Normalizing across features
| | 0 % ~calculating
|+ | 2 % ~00s
|++ | 4 % ~00s
|+++ | 5 % ~00s
|++++ | 7 % ~00s
|+++++ | 9 % ~00s
|++++++ | 11% ~00s
|+++++++ | 12% ~00s
|++++++++ | 14% ~00s
|+++++++++ | 16% ~00s
|+++++++++ | 18% ~00s
|++++++++++ | 20% ~00s
|+++++++++++ | 21% ~00s
|++++++++++++ | 23% ~00s
|+++++++++++++ | 25% ~00s
|++++++++++++++ | 27% ~00s
|+++++++++++++++ | 29% ~00s
|++++++++++++++++ | 30% ~00s
|+++++++++++++++++ | 32% ~00s
|+++++++++++++++++ | 34% ~00s
|++++++++++++++++++ | 36% ~00s
|+++++++++++++++++++ | 38% ~00s
|++++++++++++++++++++ | 39% ~00s
|+++++++++++++++++++++ | 41% ~00s
|++++++++++++++++++++++ | 43% ~00s
|+++++++++++++++++++++++ | 45% ~00s
|++++++++++++++++++++++++ | 46% ~00s
|+++++++++++++++++++++++++ | 48% ~00s
|+++++++++++++++++++++++++ | 50% ~00s
|++++++++++++++++++++++++++ | 52% ~00s
|+++++++++++++++++++++++++++ | 54% ~00s
|++++++++++++++++++++++++++++ | 55% ~00s
|+++++++++++++++++++++++++++++ | 57% ~00s
|++++++++++++++++++++++++++++++ | 59% ~00s
|+++++++++++++++++++++++++++++++ | 61% ~00s
|++++++++++++++++++++++++++++++++ | 62% ~00s
|+++++++++++++++++++++++++++++++++ | 64% ~00s
|++++++++++++++++++++++++++++++++++ | 66% ~00s
|++++++++++++++++++++++++++++++++++ | 68% ~00s
|+++++++++++++++++++++++++++++++++++ | 70% ~00s
|++++++++++++++++++++++++++++++++++++ | 71% ~00s
|+++++++++++++++++++++++++++++++++++++ | 73% ~00s
|++++++++++++++++++++++++++++++++++++++ | 75% ~00s
|+++++++++++++++++++++++++++++++++++++++ | 77% ~00s
|++++++++++++++++++++++++++++++++++++++++ | 79% ~00s
|+++++++++++++++++++++++++++++++++++++++++ | 80% ~00s
|++++++++++++++++++++++++++++++++++++++++++ | 82% ~00s
|++++++++++++++++++++++++++++++++++++++++++ | 84% ~00s
|+++++++++++++++++++++++++++++++++++++++++++ | 86% ~00s
|++++++++++++++++++++++++++++++++++++++++++++ | 88% ~00s
|+++++++++++++++++++++++++++++++++++++++++++++ | 89% ~00s
|++++++++++++++++++++++++++++++++++++++++++++++ | 91% ~00s
|+++++++++++++++++++++++++++++++++++++++++++++++ | 93% ~00s
|++++++++++++++++++++++++++++++++++++++++++++++++ | 95% ~00s
|+++++++++++++++++++++++++++++++++++++++++++++++++ | 96% ~00s
|++++++++++++++++++++++++++++++++++++++++++++++++++| 98% ~00s
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s
FeaturePlot(All_samples_Merged, features = c("PRF1", "GZMB", "NKG7"), reduction = "umap.harmony")

FeaturePlot(All_samples_Merged, features = c("CCR7", "CCR4", "CD27", "CD62L", "SELL", "CD45RA", "CD45RO", "CD95"), reduction = "umap.harmony")
Warning: Could not find CD62L in the default search locations, found in ‘ADT’ assay insteadWarning: Could not find CD45RA in the default search locations, found in ‘ADT’ assay insteadWarning: Could not find CD45RO in the default search locations, found in ‘ADT’ assay insteadWarning: Could not find CD95 in the default search locations, found in ‘ADT’ assay instead

FeaturePlot(All_samples_Merged, features = c("IL7R", "CCR7", "CD45RO", "TCF7"), reduction = "umap.harmony")
Warning: Could not find CD45RO in the default search locations, found in ‘ADT’ assay instead

FeaturePlot(All_samples_Merged, features = c("KLHL42", "TOX", "DNM3", "PGM2L1", "SESN3"), reduction = "umap.harmony")

FeaturePlot(All_samples_Merged, features = c("CD3", "CD26", "CD7", "CD5", "CD70"), reduction = "umap.harmony")
Warning: Could not find CD3 in the default search locations, found in ‘ADT’ assay insteadWarning: Could not find CD26 in the default search locations, found in ‘ADT’ assay instead

FeaturePlot(All_samples_Merged, features = c("THEMIS", "LAIR1"), reduction = "umap.harmony")

FeaturePlot(All_samples_Merged, features = c("CD164", "CD274", "CD279", "KIR3DL2", "CD158k", "PD1" ), reduction = "umap.harmony")
Warning: Could not find PD1 in the default search locations, found in ‘ADT’ assay insteadWarning: The following requested variables were not found: CD279, CD158k

FeaturePlot(All_samples_Merged, features = c("CD183", "CD194", "CD196", "CCR10", "CD158k", "PD1" ), reduction = "umap.harmony")
Warning: Could not find PD1 in the default search locations, found in ‘ADT’ assay insteadWarning: The following requested variables were not found: CD183, CD194, CD196, CD158k

FeaturePlot(All_samples_Merged, features = c("BIRC3", "PIM2", "NPM1", "PRDX1", "DUSP4", "CCND2", "CCND3", "TNFRSF4" ), reduction = "umap.harmony")

FeaturePlot(All_samples_Merged, features = c("CD160", "TIGIT", "LAG3", "HAVCR2", "CTLA4", "PDCD1" ), reduction = "umap.harmony")

Save the Seurat object as an Robj file
# save(All_samples_Merged, file = "/home/bioinfo/0-imp_Robj/All_Samples_Merged_NormalizedADT_Margin2.Robj")
LS0tCnRpdGxlOiAiUHJlLUFuYWx5c2lzIHVzaW5nIEZlYXR1cmVQbG90IgphdXRob3I6IE5hc2lyIE1haG1vb2QgQWJiYXNpCmRhdGU6ICJgciBTeXMuRGF0ZSgpYCIKb3V0cHV0OgogICMgcGRmX2RvY3VtZW50OiBkZWZhdWx0CiAgIyB3b3JkX2RvY3VtZW50OiBkZWZhdWx0CiAgIyBodG1sX2RvY3VtZW50OiBkZWZhdWx0CiAgI3JtZGZvcm1hdHM6OnJlYWR0aGVkb3duCiAgaHRtbF9ub3RlYm9vazoKICAgIHRvYzogdHJ1ZQogICAgdG9jX2Zsb2F0OiB0cnVlCiAgICB0b2NfY29sbGFwc2VkOiB0cnVlCi0tLQoKIyAxLiBsb2FkIGxpYnJhcmllcwpgYGB7ciBzZXR1cCwgaW5jbHVkZT1GQUxTRX0KCmxpYnJhcnkoU2V1cmF0KQpsaWJyYXJ5KFNldXJhdE9iamVjdCkKbGlicmFyeShTZXVyYXREYXRhKQpsaWJyYXJ5KHBhdGNod29yaykKbGlicmFyeShybWFya2Rvd24pCmxpYnJhcnkodGlueXRleCkKbGlicmFyeShnZ3Bsb3QyKQpsaWJyYXJ5KGRwbHlyKQpsaWJyYXJ5KHRpZHlyKQoKYGBgCgoKIyAyLiBMb2FkIFNldXJhdCBPYmplY3QgCmBgYHtyIGxvYWRfc2V1cmF0fQoKI0xvYWQgU2V1cmF0IE9iamVjdCBtZXJnZWQgZnJvbSBjZWxsIGxpbmVzIGFuZCBhIGNvbnRyb2woUEJNQykgYWZ0ZXIgZmlsdHJhdGlvbgpTU19BbGxfc2FtcGxlc19NZXJnZWQgPC0gbG9hZCgiL2hvbWUvYmlvaW5mby8wLWltcF9Sb2JqL0hhcm1vbnlfaW50ZWdyYXRlZF9BbGxfc2FtcGxlc19NZXJnZWRfd2l0aF9QQk1DMTB4X3dpdGhfaGFybW9ueV9jbHVzdGVyaW5nLlJvYmoiKQoKQWxsX3NhbXBsZXNfTWVyZ2VkCgpEaW1QbG90KEFsbF9zYW1wbGVzX01lcmdlZCwgZ3JvdXAuYnkgPSAiY2VsbF9saW5lIiwgbGFiZWwgPSBULCBsYWJlbC5ib3ggPSBUKQpgYGAKCgoKIyAzLiBQcmUtQW5hbHlzaXMgdXNpbmcgRmVhdHVyZVBsb3QKYGBge3IgRmVhdHVyZVBsb3QsIGZpZy5oZWlnaHQ9OCwgZmlnLndpZHRoPTEyfQoKQWxsX3NhbXBsZXNfTWVyZ2VkIDwtIE5vcm1hbGl6ZURhdGEoQWxsX3NhbXBsZXNfTWVyZ2VkLCBub3JtYWxpemF0aW9uLm1ldGhvZCA9ICJDTFIiLCBtYXJnaW4gPSAxLCBhc3NheSA9ICJBRFQiKQpGZWF0dXJlUGxvdChBbGxfc2FtcGxlc19NZXJnZWQsIGZlYXR1cmVzID0gYygiUFJGMSIsICJHWk1CIiwgIk5LRzciKSwgcmVkdWN0aW9uID0gInVtYXAuaGFybW9ueSIpCgpGZWF0dXJlUGxvdChBbGxfc2FtcGxlc19NZXJnZWQsIGZlYXR1cmVzID0gYygiQ0NSNyIsICJDQ1I0IiwgIkNEMjciLCAiQ0Q2MkwiLCAiU0VMTCIsICJDRDQ1UkEiLCAiQ0Q0NVJPIiwgIkNEOTUiKSwgcmVkdWN0aW9uID0gInVtYXAuaGFybW9ueSIpCgpGZWF0dXJlUGxvdChBbGxfc2FtcGxlc19NZXJnZWQsIGZlYXR1cmVzID0gYygiSUw3UiIsICJDQ1I3IiwgIkNENDVSTyIsICJUQ0Y3IiksIHJlZHVjdGlvbiA9ICJ1bWFwLmhhcm1vbnkiKQoKRmVhdHVyZVBsb3QoQWxsX3NhbXBsZXNfTWVyZ2VkLCBmZWF0dXJlcyA9IGMoIktMSEw0MiIsICJUT1giLCAiRE5NMyIsICJQR00yTDEiLCAiU0VTTjMiKSwgcmVkdWN0aW9uID0gInVtYXAuaGFybW9ueSIpCgoKRmVhdHVyZVBsb3QoQWxsX3NhbXBsZXNfTWVyZ2VkLCBmZWF0dXJlcyA9IGMoIkNEMyIsICJDRDI2IiwgIkNENyIsICJDRDUiLCAiQ0Q3MCIpLCByZWR1Y3Rpb24gPSAidW1hcC5oYXJtb255IikKCgpGZWF0dXJlUGxvdChBbGxfc2FtcGxlc19NZXJnZWQsIGZlYXR1cmVzID0gYygiVEhFTUlTIiwgIkxBSVIxIiksIHJlZHVjdGlvbiA9ICJ1bWFwLmhhcm1vbnkiKQoKRmVhdHVyZVBsb3QoQWxsX3NhbXBsZXNfTWVyZ2VkLCBmZWF0dXJlcyA9IGMoIkNEMTY0IiwgIkNEMjc0IiwgIkNEMjc5IiwgIktJUjNETDIiLCAiQ0QxNThrIiwgIlBEMSIgKSwgcmVkdWN0aW9uID0gInVtYXAuaGFybW9ueSIpCgpGZWF0dXJlUGxvdChBbGxfc2FtcGxlc19NZXJnZWQsIGZlYXR1cmVzID0gYygiQ0QxODMiLCAiQ0QxOTQiLCAiQ0QxOTYiLCAiQ0NSMTAiLCAiQ0QxNThrIiwgIlBEMSIgKSwgcmVkdWN0aW9uID0gInVtYXAuaGFybW9ueSIpCgpGZWF0dXJlUGxvdChBbGxfc2FtcGxlc19NZXJnZWQsIGZlYXR1cmVzID0gYygiQklSQzMiLCAiUElNMiIsICJOUE0xIiwgIlBSRFgxIiwgIkRVU1A0IiwgIkNDTkQyIiwgIkNDTkQzIiwgIlRORlJTRjQiICksIHJlZHVjdGlvbiA9ICJ1bWFwLmhhcm1vbnkiKQoKRmVhdHVyZVBsb3QoQWxsX3NhbXBsZXNfTWVyZ2VkLCBmZWF0dXJlcyA9IGMoIkNEMTYwIiwgIlRJR0lUIiwgIkxBRzMiLCAiSEFWQ1IyIiwgIkNUTEE0IiwgIlBEQ0QxIiApLCByZWR1Y3Rpb24gPSAidW1hcC5oYXJtb255IikKCmBgYAoKCgojIyBTYXZlIHRoZSBTZXVyYXQgb2JqZWN0IGFzIGFuIFJvYmogZmlsZQpgYGB7ciBzYXZlUk9CSl8yfQoKIyBzYXZlKEFsbF9zYW1wbGVzX01lcmdlZCwgZmlsZSA9ICIvaG9tZS9iaW9pbmZvLzAtaW1wX1JvYmovQWxsX1NhbXBsZXNfTWVyZ2VkX05vcm1hbGl6ZWRBRFRfTWFyZ2luMi5Sb2JqIikKCgoKYGBgCgo=