#loading library
# Install and load BiocManager
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
library(BiocManager)
# Install and load required Bioconductor packages
BiocManager::install("DESeq2")## Bioconductor version 3.18 (BiocManager 1.30.22), R 4.3.2 (2023-10-31 ucrt)## Warning: package(s) not installed when version(s) same as or greater than current; use
## `force = TRUE` to re-install: 'DESeq2'## Installation paths not writeable, unable to update packages
## path: C:/Program Files/R/R-4.3.2/library
## packages:
## cluster, foreign, lattice, MASS, Matrix, mgcv, nlme, rpartBiocManager::install("Geno
micRanges")## Bioconductor version 3.18 (BiocManager 1.30.22), R 4.3.2 (2023-10-31 ucrt)## Installing package(s) 'Geno
##
## micRanges'## Warning: package 'Geno
##
##
##
##
##
## micRanges' is not available for Bioconductor version '3.18'
##
## A version of this package for your version of R might be available elsewhere,
## see the ideas at
## https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages## Installation paths not writeable, unable to update packages
## path: C:/Program Files/R/R-4.3.2/library
## packages:
## cluster, foreign, lattice, MASS, Matrix, mgcv, nlme, rpartreading gene read data
gene_reads_data <- read.table("C:/Users/DELL/Downloads/gene_reads_2017-06-05_v8_brain_frontal_cortex_ba9.gct/gene_reads_brain_frontal_cortex_ba9.gct", header = TRUE, skip = 2 ,sep = "\t")# Calculate row means for each gene
gene_reads_data$row_means <- rowMeans(gene_reads_data[, -c(1:3)], na.rm = TRUE)
# Sort genes based on row means
sorted_genes <- gene_reads_data[order(gene_reads_data$row_means, decreasing = TRUE), ]
# Select the top 100 genes
top_100_genes <- head(sorted_genes, 100)
# Print the top 100 genes with gene names
print(top_100_genes[, c(1:3)])## id Name Description
## 56167 56166 ENSG00000210082.2 MT-RNR2
## 56179 56178 ENSG00000198804.2 MT-CO1
## 56191 56190 ENSG00000198886.2 MT-ND4
## 56182 56181 ENSG00000198712.1 MT-CO2
## 56186 56185 ENSG00000198938.2 MT-CO3
## 56173 56172 ENSG00000198763.3 MT-ND2
## 56169 56168 ENSG00000198888.2 MT-ND1
## 56185 56184 ENSG00000198899.2 MT-ATP6
## 56198 56197 ENSG00000198727.2 MT-CYB
## 56165 56164 ENSG00000211459.2 MT-RNR1
## 56195 56194 ENSG00000198786.2 MT-ND5
## 47072 47071 ENSG00000197971.14 MBP
## 44851 44850 ENSG00000131095.12 GFAP
## 56188 56187 ENSG00000198840.2 MT-ND3
## 23276 23275 ENSG00000120885.21 CLU
## 33913 33912 ENSG00000155980.11 KIF5A
## 56190 56189 ENSG00000212907.2 MT-ND4L
## 50083 50082 ENSG00000132639.12 SNAP25
## 38065 38064 ENSG00000198668.10 CALM1
## 56196 56195 ENSG00000198695.2 MT-ND6
## 13117 13116 ENSG00000152583.12 SPARCL1
## 30180 30179 ENSG00000110436.11 SLC1A2
## 56184 56183 ENSG00000228253.1 MT-ATP8
## 51050 51049 ENSG00000087460.24 GNAS
## 3811 3810 ENSG00000135821.17 GLUL
## 37 36 ENSG00000248527.1 MTATP6P1
## 20076 20075 ENSG00000075624.13 ACTB
## 55382 55381 ENSG00000010404.17 IDS
## 32299 32298 ENSG00000154146.12 NRGN
## 16600 16599 ENSG00000070808.15 CAMK2A
## 49076 49075 ENSG00000160014.16 CALM3
## 38392 38391 ENSG00000080824.18 HSP90AA1
## 9945 9944 ENSG00000168309.16 FAM107A
## 36733 36732 ENSG00000165795.23 NDRG2
## 20432 20431 ENSG00000180354.15 MTURN
## 51527 51526 ENSG00000142192.20 APP
## 54725 54724 ENSG00000123560.13 PLP1
## 8892 8891 ENSG00000130294.15 KIF1A
## 32632 32631 ENSG00000111640.14 GAPDH
## 18688 18687 ENSG00000156508.17 EEF1A1
## 38433 38432 ENSG00000166165.12 CKB
## 47352 47351 ENSG00000167658.15 EEF2
## 18363 18362 ENSG00000096384.19 HSP90AB1
## 41733 41732 ENSG00000149925.17 ALDOA
## 3347 3346 ENSG00000018625.14 ATP1A2
## 5805 5804 ENSG00000143933.16 CALM2
## 30888 30887 ENSG00000133318.13 RTN3
## 49187 49186 ENSG00000087086.14 FTL
## 16953 16952 ENSG00000145920.14 CPLX2
## 7814 7813 ENSG00000128656.13 CHN1
## 39418 39417 ENSG00000166963.12 MAP1A
## 5308 5307 ENSG00000163032.11 VSNL1
## 28261 28260 ENSG00000197746.13 PSAP
## 15339 15338 ENSG00000131711.14 MAP1B
## 50306 50305 ENSG00000101439.8 CST3
## 45886 45885 ENSG00000184009.9 ACTG1
## 14057 14056 ENSG00000109472.13 CPE
## 40821 40820 ENSG00000127585.11 FBXL16
## 40030 40029 ENSG00000067225.17 PKM
## 14163 14162 ENSG00000150625.16 GPM6A
## 34250 34249 ENSG00000067715.13 SYT1
## 32232 32231 ENSG00000109971.13 HSPA8
## 21270 21269 ENSG00000170027.6 YWHAG
## 33538 33537 ENSG00000135472.8 FAIM2
## 52756 52755 ENSG00000128245.14 YWHAH
## 26937 26936 ENSG00000107130.9 NCS1
## 42393 42392 ENSG00000103034.14 NDRG4
## 8344 8343 ENSG00000078018.19 MAP2
## 607 606 ENSG00000162545.5 CAMK2N1
## 34880 34879 ENSG00000089220.4 PEBP1
## 37535 37534 ENSG00000139970.16 RTN1
## 26873 26872 ENSG00000197694.15 SPTAN1
## 27052 27051 ENSG00000130558.19 OLFM1
## 8669 8668 ENSG00000135916.15 ITM2C
## 26853 26852 ENSG00000106976.20 DNM1
## 5894 5893 ENSG00000115310.17 RTN4
## 14884 14883 ENSG00000079215.13 SLC1A3
## 32665 32664 ENSG00000111674.8 ENO2
## 7498 7497 ENSG00000168280.16 KIF5C
## 1061 1060 ENSG00000020129.15 NCDN
## 12471 12470 ENSG00000154277.12 UCHL1
## 3351 3350 ENSG00000162734.12 PEA15
## 53727 53726 ENSG00000156298.12 TSPAN7
## 23235 23234 ENSG00000277586.2 NEFL
## 49228 49227 ENSG00000104888.9 SLC17A7
## 15389 15388 ENSG00000171617.13 ENC1
## 5886 5885 ENSG00000115306.15 SPTBN1
## 55538 55537 ENSG00000203879.11 GDI1
## 26822 26821 ENSG00000136854.19 STXBP1
## 38268 38267 ENSG00000214548.14 MEG3
## 26106 26105 ENSG00000148053.15 NTRK2
## 24394 24393 ENSG00000164924.17 YWHAZ
## 303 302 ENSG00000171603.16 CLSTN1
## 48854 48853 ENSG00000105409.16 ATP1A3
## 43185 43184 ENSG00000108953.16 YWHAE
## 2513 2512 ENSG00000163399.15 ATP1A1
## 53965 53964 ENSG00000102003.10 SYP
## 44076 44075 ENSG00000109107.13 ALDOC
## 50583 50582 ENSG00000260032.1 NORAD
## 762 761 ENSG00000117632.22 STMN1gene_names <- top_100_genes[, 3]
print(gene_names)## [1] "MT-RNR2" "MT-CO1" "MT-ND4" "MT-CO2" "MT-CO3" "MT-ND2"
## [7] "MT-ND1" "MT-ATP6" "MT-CYB" "MT-RNR1" "MT-ND5" "MBP"
## [13] "GFAP" "MT-ND3" "CLU" "KIF5A" "MT-ND4L" "SNAP25"
## [19] "CALM1" "MT-ND6" "SPARCL1" "SLC1A2" "MT-ATP8" "GNAS"
## [25] "GLUL" "MTATP6P1" "ACTB" "IDS" "NRGN" "CAMK2A"
## [31] "CALM3" "HSP90AA1" "FAM107A" "NDRG2" "MTURN" "APP"
## [37] "PLP1" "KIF1A" "GAPDH" "EEF1A1" "CKB" "EEF2"
## [43] "HSP90AB1" "ALDOA" "ATP1A2" "CALM2" "RTN3" "FTL"
## [49] "CPLX2" "CHN1" "MAP1A" "VSNL1" "PSAP" "MAP1B"
## [55] "CST3" "ACTG1" "CPE" "FBXL16" "PKM" "GPM6A"
## [61] "SYT1" "HSPA8" "YWHAG" "FAIM2" "YWHAH" "NCS1"
## [67] "NDRG4" "MAP2" "CAMK2N1" "PEBP1" "RTN1" "SPTAN1"
## [73] "OLFM1" "ITM2C" "DNM1" "RTN4" "SLC1A3" "ENO2"
## [79] "KIF5C" "NCDN" "UCHL1" "PEA15" "TSPAN7" "NEFL"
## [85] "SLC17A7" "ENC1" "SPTBN1" "GDI1" "STXBP1" "MEG3"
## [91] "NTRK2" "YWHAZ" "CLSTN1" "ATP1A3" "YWHAE" "ATP1A1"
## [97] "SYP" "ALDOC" "NORAD" "STMN1"#write.csv(gene_names, file = "gene_names.csv", row.names = FALSE)
#cat("Gene names have been saved to gene_names.csv\n")# Get the current working directory
#current_directory <- getwd()
# List files in the current working directory
#files_in_directory <- list.files(current_directory)
# Print the current working directory and the list of files
#print("Current Working Directory:")
#print(current_directory)
#print("Files in Current Working Directory:")
#print(files_in_directory)#install.packages("igraph")
#install.packages("tidyverse")
#library(igraph)
#library(tidyverse)network_data <- read.table("C:/Users/DELL/Downloads/network.csv", header = TRUE, sep = ",")
network_data## commonName isLinker module name nodeLabel nodeToolTip nodeType
## 1 HSP90AB1 false NA HSP90AB1 HSP90AB1 HSP90AB1 Gene
## 2 NTRK2 false NA NTRK2 NTRK2 NTRK2 Gene
## 3 MAPK8 true NA MAPK8 MAPK8 MAPK8 Gene
## 4 FAIM2 false NA FAIM2 FAIM2 FAIM2 Gene
## 5 BCL2 true NA BCL2 BCL2 BCL2 Gene
## 6 SPTAN1 false NA SPTAN1 SPTAN1 SPTAN1 Gene
## 7 INS true NA INS INS INS Gene
## 8 CLU false NA CLU CLU CLU Gene
## 9 EP300 true NA EP300 EP300 EP300 Gene
## 10 MAPK1 true NA MAPK1 MAPK1 MAPK1 Gene
## 11 STXBP1 false NA STXBP1 STXBP1 STXBP1 Gene
## 12 VAMP2 true NA VAMP2 VAMP2 VAMP2 Gene
## 13 CPE false NA CPE CPE CPE Gene
## 14 HSPA8 false NA HSPA8 HSPA8 HSPA8 Gene
## 15 SNAP25 false NA SNAP25 SNAP25 SNAP25 Gene
## 16 ATP1A3 false NA ATP1A3 ATP1A3 ATP1A3 Gene
## 17 SNCA true NA SNCA SNCA SNCA Gene
## 18 UBA52 true NA UBA52 UBA52 UBA52 Gene
## 19 KLHL8 true NA KLHL8 KLHL8 KLHL8 Gene
## 20 APP false NA APP APP APP Gene
## 21 ITM2C false NA ITM2C ITM2C ITM2C Gene
## 22 YWHAE false NA YWHAE YWHAE YWHAE Gene
## 23 YWHAZ false NA YWHAZ YWHAZ YWHAZ Gene
## 24 ACTB false NA ACTB ACTB ACTB Gene
## 25 RHOJ true NA RHOJ RHOJ RHOJ Gene
## 26 PEBP1 false NA PEBP1 PEBP1 PEBP1 Gene
## 27 NRAS true NA NRAS NRAS NRAS Gene
## 28 ETS1 true NA ETS1 ETS1 ETS1 Gene
## 29 CPLX2 false NA CPLX2 CPLX2 CPLX2 Gene
## 30 MT-ND6 false NA MT-ND6 MT-ND6 MT-ND6 Gene
## 31 MT-ND3 false NA MT-ND3 MT-ND3 MT-ND3 Gene
## 32 NDRG2 false NA NDRG2 NDRG2 NDRG2 Gene
## 33 TAF8 true NA TAF8 TAF8 TAF8 Gene
## 34 MT-ND4 false NA MT-ND4 MT-ND4 MT-ND4 Gene
## 35 MT-ND1 false NA MT-ND1 MT-ND1 MT-ND1 Gene
## 36 MT-ND2 false NA MT-ND2 MT-ND2 MT-ND2 Gene
## 37 SLC1A3 false NA SLC1A3 SLC1A3 SLC1A3 Gene
## 38 USF2 true NA USF2 USF2 USF2 Gene
## 39 SYT1 false NA SYT1 SYT1 SYT1 Gene
## 40 NEFL false NA NEFL NEFL NEFL Gene
## 41 DISC1 true NA DISC1 DISC1 DISC1 Gene
## 42 MT-ND5 false NA MT-ND5 MT-ND5 MT-ND5 Gene
## 43 ALDOC false NA ALDOC ALDOC ALDOC Gene
## 44 ALDOA false NA ALDOA ALDOA ALDOA Gene
## 45 NDRG4 false NA NDRG4 NDRG4 NDRG4 Gene
## 46 HSP90AA1 false NA HSP90AA1 HSP90AA1 HSP90AA1 Gene
## 47 HTT true NA HTT HTT HTT Gene
## 48 EGFR true NA EGFR EGFR EGFR Gene
## 49 GNB1 true NA GNB1 GNB1 GNB1 Gene
## 50 GNAS false NA GNAS GNAS GNAS Gene
## 51 RTN3 false NA RTN3 RTN3 RTN3 Gene
## 52 RTN4 false NA RTN4 RTN4 RTN4 Gene
## 53 KIF5C false NA KIF5C KIF5C KIF5C Gene
## 54 GRIA2 true NA GRIA2 GRIA2 GRIA2 Gene
## 55 ACTG1 false NA ACTG1 ACTG1 ACTG1 Gene
## 56 PSAP false NA PSAP PSAP PSAP Gene
## 57 ESR1 true NA ESR1 ESR1 ESR1 Gene
## 58 EEF1A1 false NA EEF1A1 EEF1A1 EEF1A1 Gene
## 59 CALM3 false NA CALM3 CALM3 CALM3 Gene
## 60 NRGN false NA NRGN NRGN NRGN Gene
## 61 MT-CYB false NA MT-CYB MT-CYB MT-CYB Gene
## 62 YWHAH false NA YWHAH YWHAH YWHAH Gene
## 63 YWHAG false NA YWHAG YWHAG YWHAG Gene
## 64 MBP false NA MBP MBP MBP Gene
## 65 CKB false NA CKB CKB CKB Gene
## 66 KIF5A false NA KIF5A KIF5A KIF5A Gene
## 67 PKM false NA PKM PKM PKM Gene
## 68 ARL6IP5 true NA ARL6IP5 ARL6IP5 ARL6IP5 Gene
## 69 PAFAH1B1 true NA PAFAH1B1 PAFAH1B1 PAFAH1B1 Gene
## 70 ZFYVE27 true NA ZFYVE27 ZFYVE27 ZFYVE27 Gene
## 71 SYP false NA SYP SYP SYP Gene
## 72 TSPAN7 false NA TSPAN7 TSPAN7 TSPAN7 Gene
## 73 ATP1A2 false NA ATP1A2 ATP1A2 ATP1A2 Gene
## 74 GDI1 false NA GDI1 GDI1 GDI1 Gene
## 75 GPM6A false NA GPM6A GPM6A GPM6A Gene
## 76 CAMK2A false NA CAMK2A CAMK2A CAMK2A Gene
## 77 ATP1A1 false NA ATP1A1 ATP1A1 ATP1A1 Gene
## 78 MAP1A false NA MAP1A MAP1A MAP1A Gene
## 79 SLC17A7 false NA SLC17A7 SLC17A7 SLC17A7 Gene
## 80 OLFM1 false NA OLFM1 OLFM1 OLFM1 Gene
## 81 GAPDH false NA GAPDH GAPDH GAPDH Gene
## 82 UCHL1 false NA UCHL1 UCHL1 UCHL1 Gene
## 83 DYNC1H1 true NA DYNC1H1 DYNC1H1 DYNC1H1 Gene
## 84 ENO2 false NA ENO2 ENO2 ENO2 Gene
## 85 SPTBN1 false NA SPTBN1 SPTBN1 SPTBN1 Gene
## 86 PLP1 false NA PLP1 PLP1 PLP1 Gene
## 87 TRAF6 true NA TRAF6 TRAF6 TRAF6 Gene
## 88 MT-CO1 false NA MT-CO1 MT-CO1 MT-CO1 Gene
## 89 MT-CO3 false NA MT-CO3 MT-CO3 MT-CO3 Gene
## 90 MT-CO2 false NA MT-CO2 MT-CO2 MT-CO2 Gene
## 91 MT-ND4L false NA MT-ND4L MT-ND4L MT-ND4L Gene
## 92 MT-RNR2 false NA MT-RNR2 MT-RNR2 MT-RNR2 Gene
## 93 DNM1 false NA DNM1 DNM1 DNM1 Gene
## 94 SPARCL1 false NA SPARCL1 SPARCL1 SPARCL1 Gene
## 95 CLSTN1 false NA CLSTN1 CLSTN1 CLSTN1 Gene
## 96 GFAP false NA GFAP GFAP GFAP Gene
## 97 MAP1B false NA MAP1B MAP1B MAP1B Gene
## 98 FBXL16 false NA FBXL16 FBXL16 FBXL16 Gene
## 99 MAP2 false NA MAP2 MAP2 MAP2 Gene
## 100 MT-ATP6 false NA MT-ATP6 MT-ATP6 MT-ATP6 Gene
## 101 MT-ATP8 false NA MT-ATP8 MT-ATP8 MT-ATP8 Gene
## 102 ATP5F1B true NA ATP5F1B ATP5F1B ATP5F1B Gene
## 103 PEA15 false NA PEA15 PEA15 PEA15 Gene
## 104 CHN1 false NA CHN1 CHN1 CHN1 Gene
## 105 EEF2 false NA EEF2 EEF2 EEF2 Gene
## 106 PI4KB true NA PI4KB PI4KB PI4KB Gene
## 107 NCS1 false NA NCS1 NCS1 NCS1 Gene
## 108 FTL false NA FTL FTL FTL Gene
## 109 FAM107A false NA FAM107A FAM107A FAM107A Gene
## 110 ENC1 false NA ENC1 ENC1 ENC1 Gene
## 111 CST3 false NA CST3 CST3 CST3 Gene
## 112 GLUL false NA GLUL GLUL GLUL Gene
## 113 SLC1A2 false NA SLC1A2 SLC1A2 SLC1A2 Gene
## 114 MTURN false NA MTURN MTURN MTURN Gene
## 115 KIF1A false NA KIF1A KIF1A KIF1A Gene
## sampleNumber samples selected shared.name
## 1 NA NA false HSP90AB1
## 2 NA NA false NTRK2
## 3 NA NA false MAPK8
## 4 NA NA false FAIM2
## 5 NA NA false BCL2
## 6 NA NA false SPTAN1
## 7 NA NA true INS
## 8 NA NA false CLU
## 9 NA NA false EP300
## 10 NA NA false MAPK1
## 11 NA NA false STXBP1
## 12 NA NA false VAMP2
## 13 NA NA false CPE
## 14 NA NA false HSPA8
## 15 NA NA false SNAP25
## 16 NA NA false ATP1A3
## 17 NA NA false SNCA
## 18 NA NA false UBA52
## 19 NA NA false KLHL8
## 20 NA NA false APP
## 21 NA NA false ITM2C
## 22 NA NA false YWHAE
## 23 NA NA false YWHAZ
## 24 NA NA false ACTB
## 25 NA NA false RHOJ
## 26 NA NA false PEBP1
## 27 NA NA false NRAS
## 28 NA NA false ETS1
## 29 NA NA false CPLX2
## 30 NA NA false MT-ND6
## 31 NA NA false MT-ND3
## 32 NA NA false NDRG2
## 33 NA NA false TAF8
## 34 NA NA false MT-ND4
## 35 NA NA false MT-ND1
## 36 NA NA false MT-ND2
## 37 NA NA false SLC1A3
## 38 NA NA false USF2
## 39 NA NA false SYT1
## 40 NA NA false NEFL
## 41 NA NA false DISC1
## 42 NA NA false MT-ND5
## 43 NA NA false ALDOC
## 44 NA NA false ALDOA
## 45 NA NA false NDRG4
## 46 NA NA false HSP90AA1
## 47 NA NA false HTT
## 48 NA NA false EGFR
## 49 NA NA false GNB1
## 50 NA NA false GNAS
## 51 NA NA false RTN3
## 52 NA NA false RTN4
## 53 NA NA false KIF5C
## 54 NA NA false GRIA2
## 55 NA NA false ACTG1
## 56 NA NA false PSAP
## 57 NA NA false ESR1
## 58 NA NA false EEF1A1
## 59 NA NA false CALM3
## 60 NA NA false NRGN
## 61 NA NA false MT-CYB
## 62 NA NA false YWHAH
## 63 NA NA false YWHAG
## 64 NA NA false MBP
## 65 NA NA false CKB
## 66 NA NA false KIF5A
## 67 NA NA false PKM
## 68 NA NA false ARL6IP5
## 69 NA NA false PAFAH1B1
## 70 NA NA false ZFYVE27
## 71 NA NA false SYP
## 72 NA NA false TSPAN7
## 73 NA NA false ATP1A2
## 74 NA NA false GDI1
## 75 NA NA false GPM6A
## 76 NA NA false CAMK2A
## 77 NA NA false ATP1A1
## 78 NA NA false MAP1A
## 79 NA NA false SLC17A7
## 80 NA NA false OLFM1
## 81 NA NA false GAPDH
## 82 NA NA false UCHL1
## 83 NA NA false DYNC1H1
## 84 NA NA false ENO2
## 85 NA NA false SPTBN1
## 86 NA NA false PLP1
## 87 NA NA false TRAF6
## 88 NA NA false MT-CO1
## 89 NA NA false MT-CO3
## 90 NA NA false MT-CO2
## 91 NA NA false MT-ND4L
## 92 NA NA false MT-RNR2
## 93 NA NA false DNM1
## 94 NA NA false SPARCL1
## 95 NA NA false CLSTN1
## 96 NA NA false GFAP
## 97 NA NA false MAP1B
## 98 NA NA false FBXL16
## 99 NA NA false MAP2
## 100 NA NA false MT-ATP6
## 101 NA NA false MT-ATP8
## 102 NA NA false ATP5F1B
## 103 NA NA false PEA15
## 104 NA NA false CHN1
## 105 NA NA false EEF2
## 106 NA NA false PI4KB
## 107 NA NA false NCS1
## 108 NA NA false FTL
## 109 NA NA false FAM107A
## 110 NA NA false ENC1
## 111 NA NA false CST3
## 112 NA NA false GLUL
## 113 NA NA false SLC1A2
## 114 NA NA false MTURN
## 115 NA NA false KIF1A#network_graph <- graph_from_data_frame(network_data, directed = FALSE)
#plot(network_graph)
#degree_centrality <- degree(network_graph)
#degree_centrality
#betweenness_centrality <- betweenness(network_graph)
#betweenness_centrality
#closeness_centrality <- #closeness(network_graph)
#closeness_centrality
#clustering_coefficient <- #transitivity(network_graph, type = "undirected")
#clustering_coefficient
#local_clustering_coefficient <- transitivity(network_graph, type = "localundirected")
#local_clustering_coefficient