Publications by Nasir Mahmood Abbasi
L7
Cell Line L7 Analysis Cell Line L7 Analysis 1. load libraries 2. Load Seurat Object 3. QC 4. Normalize data 5. Perform PCA 6. Clustering 7. Azimuth Annotation 8. Cell type annotation using ProjectTils 9.Cell type annotation using SingleR 10. clusTree 11.Save the Seurat object as an Robj file ...
1102 sym Python (27352 sym/173 pcs) 43 img
L2_Notebook
1. load libraries 2. Load Seurat Object #Load Seurat Object L2 load("../Documents/1-SS-STeps/4-Analysis_and_Robj_Marie/analyse juillet 2023/ObjetsR/L2.Robj") L2 An object of class Seurat 36629 features across 5935 samples within 2 assays Active assay: RNA (36601 features, 0 variable features) 2 layers present: counts, data 1 other assay pres...
20077 sym R (88520 sym/117 pcs) 43 img
L1
Cell Line L1 Analysis Cell Line L1 Analysis 1. load libraries 2. Load Seurat Object 3. QC 4. Normalize data 5. Perform PCA 6. Clustering 7. Azimuth Annotation 8. Cell type annotation using ProjectTils 9.Cell type annotation using SingleR 10. clusTree 11.Save the Seurat object as an Robj file ...
1097 sym Python (27529 sym/172 pcs) 43 img
L2
Cell Line L2 Analysis Cell Line L2 Analysis 1. load libraries 2. Load Seurat Object 3. QC 4. Normalize data 5. Perform PCA 6. Clustering 7. Azimuth Annotation 8. Cell type annotation using ProjectTils 9.Cell type annotation using SingleR 10. clusTree 11.Save the Seurat object as an Robj file ...
1096 sym Python (27205 sym/171 pcs) 43 img
L1_notebook
1. load libraries 2. Load Seurat Object #Load Seurat Object L1 load("../Documents/1-SS-STeps/4-Analysis_and_Robj_Marie/analyse juillet 2023/ObjetsR/L1.Robj") L1 3. QC # Set identity classes to an existing column in meta data Idents(object = L1) <- "cell_line" L1[["percent.rb"]] <- PercentageFeatureSet(L1, pattern = "^RP[SL]") VlnPlot(L1, feat...
20074 sym R (88447 sym/114 pcs) 43 img
cell-cell communication using CellChat
1. load libraries 2. Load Seurat Object #Load Seurat Object Integrated Object load("ARSIM0only_corrected.Robj") ARSIM0only An object of class Seurat 39604 features across 32273 samples within 3 assays Active assay: integrated (2996 features, 2996 variable features) 2 layers present: data, scale.data 2 other assays present: RNA, ADT 3 dimens...
22207 sym R (58120 sym/94 pcs) 48 img
Document-Harmony-Integration
1. load libraries 2. Load Seurat Object #Load Seurat Object merged from cell lines and a control(PBMC) after filtration SS_All_samples_Merged <- load("All_Normal-PBMC_Abnormal-cellLines_T_cells_Merged_Annotated_UMAP_on_Clusters_to_USE.Robj") All_samples_Merged An object of class Seurat 62625 features across 46976 samples within 6 assays Active...
11039 sym Python (14028 sym/66 pcs) 19 img
Integration by Harmony_on_logNormalization
1. load libraries 2. Load Seurat Object merged_seurat_filtered An object of class Seurat 36724 features across 49193 samples within 5 assays Active assay: RNA (36601 features, 0 variable features) 2 layers present: counts, data 4 other assays present: ADT, prediction.score.celltype.l1, prediction.score.celltype.l2, prediction.score.celltype.l...
14369 sym R (58051 sym/87 pcs) 16 img
Integration by Harmony_on_SCTransform_DATA
1. load libraries 2. Load Seurat Object All_samples_Merged An object of class Seurat 62625 features across 46976 samples within 6 assays Active assay: SCT (25901 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, predictio...
4083 sym Python (6951 sym/20 pcs) 7 img
1-Harmony Integration_on_SCTransform
1. load libraries 2. Load Seurat Object All_samples_Merged An object of class Seurat 62625 features across 46976 samples within 6 assays Active assay: SCT (25901 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, predictio...
4125 sym 7 img