Publications by Nasir Mahmood Abbasi
L6_vs_L7_Enrichment
1. load libraries 2. Perform DE analysis using Malignant_CD4Tcells_vs_Normal_CD4Tcells genes Malignant_CD4Tcells_vs_Normal_CD4Tcells <- read.csv("comparison_L6_vs_L7_with_mean_expression_filtered.csv", header = T) 3. Create the EnhancedVolcano plot library(ggplot2) library(EnhancedVolcano) library(dplyr) # Define the output directory output_di...
18641 sym R (17139 sym/48 pcs) 11 img
L1_vs_Control_Enrichment
1. load libraries 2. Perform DE analysis using Malignant_CD4Tcells_vs_Normal_CD4Tcells genes Malignant_CD4Tcells_vs_Normal_CD4Tcells <- read.csv("Filtered_DE_Results_L1_with_MeanExpr.csv", header = T) 3. Create the EnhancedVolcano plot library(ggplot2) library(EnhancedVolcano) library(dplyr) # Define the output directory output_dir <- "L1_vs_C...
18696 sym R (13863 sym/38 pcs) 12 img
P1_vs_P2_Enrichment
1. load libraries 2. Perform DE analysis using Malignant_CD4Tcells_vs_Normal_CD4Tcells genes Malignant_CD4Tcells_vs_Normal_CD4Tcells <- read.csv("comparison_P1_vs_P2_with_mean_expression_filtered.csv", header = T) 3. Create the EnhancedVolcano plot library(ggplot2) library(EnhancedVolcano) library(dplyr) # Define the output directory output_di...
18775 sym R (13415 sym/29 pcs) 12 img
P1_vs_P3_Enrichment
1. load libraries 2. Perform DE analysis using Malignant_CD4Tcells_vs_Normal_CD4Tcells genes Malignant_CD4Tcells_vs_Normal_CD4Tcells <- read.csv("comparison_P1_vs_P3_with_mean_expression_filtered.csv", header = T) 3. Create the EnhancedVolcano plot library(ggplot2) library(EnhancedVolcano) library(dplyr) # Define the output directory output_di...
18632 sym R (13818 sym/38 pcs) 12 img
P2_vs_P3_Enrichment
1. load libraries 2. Perform DE analysis using Malignant_CD4Tcells_vs_Normal_CD4Tcells genes Malignant_CD4Tcells_vs_Normal_CD4Tcells <- read.csv("comparison_P2_vs_P3_with_mean_expression_filtered.csv", header = T) 3. Create the EnhancedVolcano plot library(ggplot2) library(EnhancedVolcano) library(dplyr) # Define the output directory output_di...
18632 sym R (13981 sym/40 pcs) 10 img
L3_vs_L4_Enrichment
1. load libraries 2. Perform DE analysis using Malignant_CD4Tcells_vs_Normal_CD4Tcells genes Malignant_CD4Tcells_vs_Normal_CD4Tcells <- read.csv("comparison_L3_vs_L4_with_mean_expression_filtered.csv", header = T) 3. Create the EnhancedVolcano plot library(ggplot2) library(EnhancedVolcano) library(dplyr) # Define the output directory output_di...
18630 sym R (14136 sym/40 pcs) 8 img
L1_vs_L2_Enrichment
1. load libraries 2. Perform DE analysis using Malignant_CD4Tcells_vs_Normal_CD4Tcells genes Malignant_CD4Tcells_vs_Normal_CD4Tcells <- read.csv("comparison_L1_vs_L2_with_mean_expression_filtered.csv", header = T) 3. Create the EnhancedVolcano plot library(ggplot2) library(EnhancedVolcano) library(dplyr) # Define the output directory output_di...
18636 sym R (13819 sym/38 pcs) 12 img
after_filtering_on_MeanExpression
1. load libraries 2. Perform DE analysis using Malignant_CD4Tcells_vs_Normal_CD4Tcells genes markers <- read.csv("../1-MAST_with_SCT_batch_patient_cellline_as_Covariate_with_meanExpression.csv", header = T) 3. Summarize Markers summarize_markers <- function(markers) { num_pval0 <- sum(markers$p_val_adj == 0) num_pval1 <- sum(markers$p_val_a...
6894 sym R (4318 sym/11 pcs) 2 img
Differential Expression Analysis of Malignant CD4Tcells vs Control(Normal CD4 Tcells)-GSEA-after_filtering
1. load libraries 2. Perform DE analysis using Malignant_CD4Tcells_vs_Normal_CD4Tcells genes markers <- read.csv("../1-MAST_with_SCT_batch_patient_cellline_as_Covariate_with_meanExpression.csv", header = T) 3. Summarize Markers summarize_markers <- function(markers) { num_pval0 <- sum(markers$p_val_adj == 0) num_pval1 <- sum(markers$p_val_a...
6894 sym R (4318 sym/11 pcs) 2 img
P1 vs P2
1. load libraries 2. Perform DE analysis using Malignant_CD4Tcells_vs_Normal_CD4Tcells genes Malignant_CD4Tcells_vs_Normal_CD4Tcells <- read.csv("comparison_P1_vs_P2_with_mean_expression_filtered.csv", header = T) 3. Create the EnhancedVolcano plot EnhancedVolcano(Malignant_CD4Tcells_vs_Normal_CD4Tcells, lab = Malignant_CD4Tcell...
23801 sym R (17376 sym/41 pcs) 16 img