I'm interested in plotting KM curves for my expression data of genes. The data was normalized, log-transformed, z-score transformed, and batch-corrected. Therefore, I'm bifurcating the whole data into mid, low, and high groups for predicitng the KM survival curves based on expression value of genes. Is my approach correct?

library(survival)
library(survminer)
library(dplyr)
library(survMisc)
library(GGally)
library(survcomp)
library(RegParallel)

JMS <- read.delim(file = "LUAD_SURVIVAL.txt")

highExpr <- 1.96
lowExpr <- -1.96

JMS$LRRK2<- ifelse(JMS$LRRK2 >= highExpr, 'High', ifelse(JMS$LRRK2 <= lowExpr, 'Low', 'Mid'))
JMS$SNCA<- ifelse(JMS$SNCA >= highExpr, 'High', ifelse(JMS$SNCA <= lowExpr, 'Low', 'Mid'))
JMS$TDRKH<- ifelse(JMS$TDRKH >= highExpr, 'High', ifelse(JMS$TDRKH <= lowExpr, 'Low', 'Mid'))


JMS$LRRK2 <- factor(JMS$LRRK2, levels = c('Mid', 'Low', 'High'))
JMS$SNCA <- factor(JMS$SNCA, levels = c('Mid', 'Low', 'High'))
JMS$TDRKH <- factor(JMS$TDRKH, levels = c('Mid', 'Low', 'High'))

ggsurvplot(survfit(Surv(Time, Status) ~ LRRK2, data = JMS), data = JMS, risk.table = TRUE, pval = TRUE, break.time.by = 500, ggtheme = theme_minimal(), risk.table.y.text.col = TRUE, risk.table.y.text = FALSE)


ggsurvplot(survfit(Surv(Time, Status) ~ SNCA, data = JMS), data = JMS, risk.table = TRUE, pval = TRUE, break.time.by = 500, ggtheme = theme_minimal(), risk.table.y.text.col = TRUE, risk.table.y.text = FALSE)


ggsurvplot(survfit(Surv(Time, Status) ~ TDRKH, data = JMS), data = JMS, risk.table = TRUE, pval = TRUE, break.time.by = 500, ggtheme = theme_minimal(), risk.table.y.text.col = TRUE, risk.table.y.text = FALSE)

My data looks like this as stored in LUAD_SURVIVAL.txt:

Sample               Status  Time           LRRK2          SNCA  TDRKH         sex  stage
TCGA.38.4625.01A    0   2973    -0.383829368    -0.219402428    0.6500694   2   Stage I
TCGA.38.4627.01A    1   1147    -1.45793859 -0.022231288    -0.5830916  2   Stage II
TCGA.38.4632.01A    1   1357    -1.316342217    -0.162383739    1.146363    1   Stage IV
TCGA.44.2655.01A    0   1324    0.046189981 -0.773276551    2.024474    2   Stage I
TCGA.44.2657.01A    0   1351    -0.975033238    -0.256492538    0.171917    2   Stage I
TCGA.44.2661.01A    0   1159    -0.78239234 0.327366323 0.1126025   2   Stage I
TCGA.44.2662.01A    0   1280    -0.758485389    -1.437559471    1.273534    1   Stage I
TCGA.44.2665.01A    0   1301    -0.999667232    -0.440681708    0.009561531 2   Stage II
TCGA.44.2668.01A    1   761 -0.644422547    -1.445774753    0.9272611   1   Stage I
TCGA.44.3396.01A    0   1130    -1.245042532    -0.395511449    -0.1383681  2   Stage III
TCGA.44.6145.01A    0   595 -0.200550603    -1.307112908    1.290406    2   Stage I
TCGA.44.6147.01A    0   845 -0.297408216    -0.358287055    0.6861114   2   Stage I
TCGA.44.6776.01A    0   2616    0.668204053 -1.045513127    0.3604824   2   Stage I
TCGA.44.6777.01A    1   987 0.774933934 0.120296574 1.095746    2   Stage I
TCGA.44.6778.01A    0   1864    0.395187563 0.209133034 0.2749578   1   Stage I
TCGA.49.4490.01A    1   385 -1.751088203    -1.655575684    0.03521947  2   Stage III
TCGA.49.4512.01A    1   905 0.332495541 -0.456119236    1.154696    2   Stage III
TCGA.49.6743.01A    0   1621    -0.641826568    -0.79901757 1.403125    2   Stage III
TCGA.49.6744.01A    0   1683    -0.403411305    0.006217842 0.300926    2   Stage II
TCGA.49.6745.01A    0   522 0.046500089 -0.621497979    0.228453    1   Stage III
TCGA.49.6761.01A    0   354 -0.857810394    -2.056883586    1.437622    2   Stage III
TCGA.50.5930.01A    1   282 -0.87400339 0.093055616 1.570507    1   Stage III
TCGA.50.5931.01A    1   434 -2.277003104    -0.995236158    0.3775715   2   Stage I
TCGA.50.5932.01A    1   1235    -0.475064449    -2.294646772    1.211618    1   Stage II
TCGA.50.5933.01A    1   2393    -0.635493519    -0.647664896    1.576859    1   Stage III
TCGA.50.5935.01A    1   653 0.144475137 -1.286987274    2.029953    2   Stage I
TCGA.50.5939.01A    1   460 -0.217287921    -0.297524684    -0.1612658  1   Stage I
TCGA.50.6595.01A    1   189 -2.074430113    -1.31726386 -1.05404    2   Stage III
TCGA.55.6968.01A    1   1293    -1.510117962    -0.110645011    1.025638    1   Stage IV
TCGA.55.6970.01A    1   464 0.493536516 -0.785224767    0.8346801   2   Stage III
TCGA.55.6971.01A    0   1400    0.208688847 -0.399653744    0.9952134   2   Stage I
TCGA.55.6972.01A    1   1632    -1.125136651    -2.586160697    1.663106    1   Stage I
TCGA.55.6975.01A    1   118 -2.092639366    -0.831491754    -0.08286432 1   Stage II
TCGA.55.6978.01A    1   176 -1.239634382    -0.579709271    -0.248721   1   Stage II
TCGA.55.6979.01A    1   237 -0.591083585    -0.795370819    0.4372139   2   Stage II
TCGA.55.6980.01A    0   2109    -0.752056711    -0.697417076    0.7107928   1   Stage I
TCGA.55.6981.01A    1   1379    -1.439636573    -1.162752821    0.7467579   2   Stage III
TCGA.55.6982.01A    1   995 -0.559143952    -0.923362752    0.2045792   2   Stage II
TCGA.55.6984.01A    1   760 -0.991059081    -2.752376513    -0.6147963  2   Stage II
TCGA.55.6985.01A    0   1233    -0.503782815    -0.359211612    0.2640623   2   Stage I
TCGA.55.6986.01A    0   3261    -0.057757299    -0.395037493    0.161682    2   Stage I
TCGA.73.4676.01A    1   281 -0.938051892    -1.009113608    1.945119    1   Stage II
TCGA.91.6828.01A    0   323 -0.246057181    -0.825642817    1.327468    1   Stage I
TCGA.91.6829.01A    1   1258    -1.300016577    0.383268015 1.390523    1   Stage I
TCGA.91.6831.01A    0   310 -1.5698444  -1.168399177    0.8284916   1   Stage I
TCGA.91.6835.01A    0   79  -0.651069358    -0.390002878    1.839444    2   Stage I
TCGA.91.6836.01A    0   417 -1.78515033 -1.364946704    3.60664         2      Stage I
TCGA.91.6847.01A    0   842 -3.538866094    -0.87741001 0.9409349   2   Stage I
TCGA.91.6849.01A    0   35  -0.202941284    0.13610892  1.131687    2   Stage III

Plot of one of the genes LRRK2 is as below: