In sbalci/histopathology-template: Template of R Codes Used in Histopathology Research.

Cross Tables

Codes for cross tables.^[See childRmd/_12crossTables.Rmd file for other codes]

library(finalfit)

# dependent <- c("dependent1",
#                "dependent2"
#               )

# explanatory <- c("explanatory1",
#                  "explanatory2"
#                  )

dependent <- "PreinvasiveComponent"

explanatory <- c("Sex", "Age", "Grade", "TStage")

Change column = TRUE argument to get row or column percentages.

source(here::here("R", "gc_table_cross.R"))

CreateTableOne(vars = myVars, strata = "columnname", data = pbc, factorVars = catVars)

print(tab, nonnormal = biomarkers, exact = "exactVariable", smd = TRUE)

write2html(
  knitr::kable(head(mockstudy)), paste0(tmpdir, "/test.kable.keep.rmd.html"),
  quiet = TRUE, # passed to rmarkdown::render
  keep.rmd = TRUE
)

ctable(tobacco$gender, tobacco$smoker, style = 'rmarkdown')

print(ctable(tobacco$gender, tobacco$smoker), method = 'render')
print(ctable(tobacco$smoker, tobacco$diseased, prop = "r"), method = "render")
with(tobacco, 
     print(ctable(smoker, diseased, prop = 'n', totals = FALSE, chisq = TRUE),
           headings = FALSE, method = "render"))

# devtools::install_github("ewenharrison/summarizer")
# library(summarizer)
# data(colon_s)
explanatory = c("age", "age.factor", "sex.factor", "obstruct.factor")
dependent = "perfor.factor"
colon_s %>%
  summary.factorlist(dependent, explanatory, p=TRUE) %>% 
    knitr::kable(row.names=FALSE, align=c("l", "l", "r", "r", "r"))

explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
  summary.factorlist(dependent, explanatory) %>% 
    knitr::kable(row.names=FALSE, align=c("l", "l", "r", "r", "r"))

library(DT)
datatable(mtcars, rownames = FALSE, filter="top", options = list(pageLength = 5, scrollX=T) )

chi-square posthoc pairwise

rmngb

library("rmngb")
# rmngb::pairwise.chisq.test(mydata$StageGr2, mydata$Ki67Gr)
rmngb::pairwise.fisher.test(mydata$StageGr2, mydata$Ki67Gr)

# rmngb::pairwise.chisq.test(mydata$LiverDistantMets, mydata$Ki67Gr, p.adj = "BH")
rmngb::pairwise.fisher.test(mydata$LiverDistantMets, mydata$Ki67Gr, p.adj = "BH")

# rmngb::pairwise.chisq.test(mydata$PNI, mydata$Ki67Gr, p.adj = "BH")
rmngb::pairwise.fisher.test(mydata$PNI, mydata$Ki67Gr, p.adj = "BH")

# rmngb::pairwise.chisq.test(mydata$LVI, mydata$Ki67Gr, p.adj = "BH")
rmngb::pairwise.fisher.test(mydata$LVI, mydata$Ki67Gr, p.adj = "BH")

RVAideMemoire

MBStudy <- 
tibble::tribble(
           ~Grup,                           ~Diagnosis,   ~Number,
   "\"Grup1\"",           "\"Diseased\"", 1383L,
  "\"Grup2A\"",           "\"Diseased\"",   58L,
  "\"Grup2B\"",           "\"Diseased\"",  349L,
   "\"Grup3\"",           "\"Diseased\"", 5217L,
   "\"Grup1\"", "\"Stromal   Diseased\"",   13L,
  "\"Grup2A\"", "\"Stromal   Diseased\"",    2L,
  "\"Grup2B\"", "\"Stromal   Diseased\"",   47L,
   "\"Grup3\"", "\"Stromal   Diseased\"",  476L,
   "\"Grup1\"",   "\"Inflammation fibrosis\"",   56L,
  "\"Grup2A\"",   "\"Inflammation fibrosis\"",   52L,
  "\"Grup2B\"",   "\"Inflammation fibrosis\"",  267L,
   "\"Grup3\"",   "\"Inflammation fibrosis\"", 1387L
  )

MBStudy <- 
  tibble::tribble(
    ~Grup,                           ~Diagnosis,   ~Number,
    "\"Grup1\"",           "\"Diseased\"", 1383L,
    "\"Grup2A\"",           "\"Diseased\"",   58L,
    "\"Grup2B\"",           "\"Diseased\"",  349L,
    "\"Grup3\"",           "\"Diseased\"", 5217L,
    "\"Grup1\"", "\"Stromal   Diseased\"",   13L,
    "\"Grup2A\"", "\"Stromal   Diseased\"",    2L,
    "\"Grup2B\"", "\"Stromal   Diseased\"",   47L,
    "\"Grup3\"", "\"Stromal   Diseased\"",  476L,
    "\"Grup1\"",   "\"Inflammation fibrosis\"",   56L,
    "\"Grup2A\"",   "\"Inflammation fibrosis\"",   52L,
    "\"Grup2B\"",   "\"Inflammation fibrosis\"",  267L,
    "\"Grup3\"",   "\"Inflammation fibrosis\"", 1387L
  )


MBStudy <- 
data.frame(
  stringsAsFactors = FALSE,
                V1 = c("\"Grup1\"","\"Grup2A\"",
                       "\"Grup2B\"","\"Grup3\"","\"Grup1\"","\"Grup2A\"",
                       "\"Grup2B\"","\"Grup3\"","\"Grup1\"","\"Grup2A\"",
                       "\"Grup2B\"","\"Grup3\""),
                V2 = c("\"Diseased\"",
                       "\"Diseased\"","\"Diseased\"","\"Diseased\"",
                       "\"Stromal   Diseased\"","\"Stromal   Diseased\"",
                       "\"Stromal   Diseased\"",
                       "\"Stromal   Diseased\"","\"Inflammation fibrosis\"",
                       "\"Inflammation fibrosis\"","\"Inflammation fibrosis\"",
                       "\"Inflammation fibrosis\""),
                V3 = c(1383L,58L,349L,5217L,13L,
                       2L,47L,476L,56L,52L,267L,1387L)
)

MBStudy <- matrix(c(
1383L,                    13L,                    56L,
58L,                     2L,                    52L,
349L,                    47L,                   267L,
5217L,                   476L,                  1387L
  ), byrow = TRUE, nrow = 4, dimnames = list(c("Grup1", "Grup2A", "Grup2B", "Grup3"), c("Diseased", "Stromal Diseased", "Inflammation")))


RVAideMemoire::chisq.multcomp(MBStudy)

\newpage \blandscape

MBStudy

MB_table <- RVAideMemoire::fisher.multcomp(tab.cont = MBStudy)

MB_table$p.value %>% 
  as.data.frame() %>%
  tibble::rownames_to_column(var = "Grup") %>% 
  gt::gt(.) %>% 
  gt::fmt_number(., columns = dplyr::contains("Diseased"), decimals = 4)

\elandscape

rmngb::pairwise.fisher.test.table(MBStudy)

MBStudy2 <- matrix(c(
13L,    53L,
9L, 5L,
3L, 26L),
byrow = TRUE,
nrow = 3,
dimnames = list(
c("Diseased", "Inflammation", "Fibrosis"),
c("sw", "cds")
))

MBStudy2

MBStudy2_analysis <-  RVAideMemoire::fisher.multcomp(tab.cont = t(MBStudy2))

MBStudy2_analysis$p.value

sbalci/histopathology-template documentation built on June 29, 2023, 5:52 a.m.