Publications by Nasir Mahmood Abbasi
Filtering and Visualization(MAST, LR and negbinom on SCT)
1. Load Libraries 2. Load Data 2.1 Load CSV Files with Mean Expression # Load the CSV files with mean expression data markers_mast_SCT <- read.csv("../0-robj/1-MAST_with_SCT_batch_patient_cellline_as_Covariate_with_meanExpression.csv", row.names = 1) markers_LR_SCT <- read.csv("../0-robj/1-LR_with_SCT_batch_patient_cellline_as_Covariate_with_me...
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Filtering and Visualization(MAST on SCT and RNA) on cell_line and default_minpct_logfc
1. Load Libraries 2. Load Data 2.1 Load CSV Files with Mean Expression # Load the CSV files with mean expression data markers_mast_SCT <- read.csv("../0-robj/RNA_SCT_test_default_pct_fc_parameters/1-MAST_with_SCT_batch_cellline_as_Covariate_with_meanExpression.csv", row.names = 1) markers_mast_RNA <- read.csv("../0-robj/RNA_SCT_test_default_pct...
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Filtering and Visualization(MAST on SCT and RNA)
1. Load Libraries 2. Load Data 2.1 Load CSV Files with Mean Expression # Load the CSV files with mean expression data markers_mast_SCT <- read.csv("../0-robj/1-MAST_with_SCT_batch_patient_cellline_as_Covariate_with_meanExpression.csv", row.names = 1) markers_mast_RNA <- read.csv("../0-robj/2-MAST_with_RNA_batch_patient_cellline_as_Covariate_wit...
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MAST on SCT and RNA assay and its comparison to see which is better with default settings
1. Load Libraries 2. load seurat object #Load Seurat Object L7 load("../0-robj/5-Harmony_Integrated_All_samples_Merged_CD4Tcells_final_Resolution_Selected_0.8_ADT_Normalized_cleaned_mt.robj") All_samples_Merged An object of class Seurat 62900 features across 49305 samples within 6 assays Active assay: SCT (26176 features, 3000 variable features...
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Filtering and Visualization(MAST on SCT and RNA
1. Load Libraries 2. Load Data 2.1 Load CSV Files with Mean Expression # Load the CSV files with mean expression data markers_mast_SCT <- read.csv("../0-robj/1-MAST_with_SCT_batch_patient_cellline_as_Covariate_with_meanExpression.csv", row.names = 1) markers_mast_RNA <- read.csv("../0-robj/2-MAST_with_RNA_batch_patient_cellline_as_Covariate_wit...
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Filtering and Visualization(MAST on SCT and RNA
1. Load Libraries 2. Load Data 2.1 Load CSV Files with Mean Expression # Load the CSV files with mean expression data markers_mast_SCT <- read.csv("../0-robj/1-MAST_with_SCT_batch_patient_cellline_as_Covariate_with_meanExpression.csv", row.names = 1) markers_mast_RNA <- read.csv("../0-robj/2-MAST_with_RNA_batch_patient_cellline_as_Covariate_wit...
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MAST on SCT and RNA assay and its comparison to see which is better
1. Load Libraries 2. load seurat object #Load Seurat Object L7 load("../0-robj/5-Harmony_Integrated_All_samples_Merged_CD4Tcells_final_Resolution_Selected_0.8_ADT_Normalized_cleaned_mt.robj") All_samples_Merged 3. Set Up Identifiers for Clustering # Assign cluster identities to the Seurat object Idents(All_samples_Merged) <- "seurat_clusters" D...
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Sézary Syndrome Cell Line Analysis
In this we have comapred cell_lines using MAST but using cell_line ident not clusters and its seem if you use cluster you get better results with MAST 1. load libraries #Differential Expression Analysis 2. load seurat object #Load Seurat Object L7 load("../0-robj/5-Harmony_Integrated_All_samples_Merged_CD4Tcells_final_Resolution_Selected_0.8_ADT_...
31040 sym R (245538 sym/168 pcs) 29 img
VolcanoPlot_Malignant_vs_normal
1. Load Libraries 2. Load Data 2.1 Load CSV Files with Mean Expression # Load the CSV files with mean expression data markers_mast_batch <- read.csv("1-MAST_with_batch_as_Covariate_with_meanExpression.csv", row.names = 1) 3. Volcano Plots for All Genes 3.1 Volcano Plot for MAST with Batch Correction EnhancedVolcano(markers_mast_batch, ...
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Sézary Syndrome Cell Line derived from each patient DE comparison
In this notebook we will be using clusters for each patient to comapre and we will be using MAST to see if that could improve results or we similar results as Wilcox. 1. load libraries #Differential Expression Analysis 2. load seurat object #Load Seurat Object L7 load("../0-robj/5-Harmony_Integrated_All_samples_Merged_CD4Tcells_final_Resolution_S...
22470 sym R (140289 sym/75 pcs) 26 img