Publications by Nasir Mahmood Abbasi
Merged All samples with PBMC_10x and removed non CD4 T cells from Control and B cells from L4 and ILC, NK, CD14 Mono didnt regress nCount and nFeature and apply SCT
1. load libraries 2. Load Seurat Object #Load Seurat Object merged from cell lines and a control(PBMC) after filtration load("0-imp_Robj/SS_CD4_Tcells_Azimuth_Annotated_PBMC10x_excluding_nonCD4_cells_from_Control_Bcells_from_L4_and_ILC_NK_just_oneCell_CD14Mono.robj") All_samples_Merged <- filtered_seurat Summarizing Seurat Object # Load necess...
24517 sym R (14980 sym/16 pcs)
Merged All samples with PBMC_10x and removed non CD4 T cells from Control and B cells from L4 and ILC, NK, CD14 Mono and regress nCountRNA and nFeatureRNA and apply SCT
1. load libraries Loading required package: SeuratObject Loading required package: sp Attaching package: 'SeuratObject' The following objects are masked from 'package:base': intersect, t ── Installed datasets ──────────────────────────────── SeuratData v0.2.2.9001 ── ✔ ...
24713 sym R (35770 sym/174 pcs) 36 img
Merged All samples with PBMC_10x and removed non CD4 T cells from Control and B cells from L4 and ILC and NK just one Cell and regress batch and apply SCT
1. load libraries Loading required package: SeuratObject Loading required package: sp Attaching package: 'SeuratObject' The following objects are masked from 'package:base': intersect, t ── Installed datasets ──────────────────────────────── SeuratData v0.2.2.9001 ── ✔ ...
24639 sym R (37088 sym/177 pcs) 36 img
Harmony integrations of PBMC10x by cell_line-theta-0.5
1. load libraries 2. Load Seurat Object # Check original UMAP before integration p1 <- DimPlot(All_samples_Merged, reduction = "umap", group.by = "cell_line", label = TRUE, label.box = TRUE) + ggtitle("Before Harmony - By Cell Line") p2 <- DimPlot(All_samples_Merged, ...
11746 sym R (9132 sym/24 pcs) 15 img
use Annotated Robj including PBMC10x to remove ILC and NK-just one Cell
#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_SCT_HPC_without_harmony_integration_removed_nonCD4cells_from_control_and_Bcells_from_L4.robj") All_samp...
5247 sym R (10766 sym/16 pcs) 1 img
Merged All samples with PBMC_10x and removed non CD4 T cells from Control and B cells from L4 and apply SCT
1. load libraries Loading required package: SeuratObject Loading required package: sp Attaching package: 'SeuratObject' The following objects are masked from 'package:base': intersect, t ── Installed datasets ──────────────────────────────── SeuratData v0.2.2.9001 ── ✔ ...
24105 sym R (35941 sym/171 pcs) 36 img
Merged All samples with PBMC_10x and removed non CD4 T cells from Control apply SCT
1. load libraries Loading required package: SeuratObject Loading required package: sp Attaching package: 'SeuratObject' The following objects are masked from 'package:base': intersect, t ── Installed datasets ──────────────────────────────── SeuratData v0.2.2.9001 ── ✔ ...
23813 sym R (30221 sym/145 pcs) 32 img
use Annotated Robj including PBMC10x to remove NonCD4Tcells from Control and B cells from L4
#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_Merged An object of class Seurat 36752 features across 59355 samples within 5 assay...
6213 sym Python (14178 sym/14 pcs) 1 img
Merged All samples with PBMC_10x and removed non CD4 T cells from Control apply SCT
1. load libraries Loading required package: SeuratObject Loading required package: sp Attaching package: 'SeuratObject' The following objects are masked from 'package:base': intersect, t ── Installed datasets ──────────────────────────────── SeuratData v0.2.2.9001 ── ✔ ...
23654 sym R (35759 sym/170 pcs) 36 img
CD4Tcells in PBMC(Ready to Normalize)
#In this script I will I will remove Non T cells from PBMC 1. load libraries 2. Load Seurat Object All_samples_Merged An 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, p...
5883 sym R (14557 sym/16 pcs) 1 img