> For the complete documentation index, see [llms.txt](https://www.parapathology.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.parapathology.com/carcinogenesis-hallmarks-of-cancer/what-is-cancer.md).

# What is Cancer?

  

## What is Cancer?

***

### Replication Crisis

<https://en.wikipedia.org/wiki/Replication\\_crisis>

***

### Replication Crisis Excel Version

***

## RStudio ile proje oluştur

***

## R Notebook

### R Notebook dökümanı oluşturma

***

### R Notebook'tan html, pdf ve word oluşturma

***

### RNotebook vs RMarkdown

<https://youtu.be/zNzZ1PfUDNk>

***

## R Markdown

### Hem kendi kodları hem de html kodları yazılabilir

<https://rmarkdown.rstudio.com>

[What is R Markdown?](https://vimeo.com/178485416) from [RStudio, Inc.](https://vimeo.com/rstudioinc) on [Vimeo](https://vimeo.com).

***

### R Markdown: The Definitive Guide

<https://bookdown.org/yihui/rmarkdown/>

***

### R Markdown syntax

<https://gist.github.com/MinhasKamal/7fdebb7c424d23149140>

***

### Remedy Package

***

#### Remedy

***

### R Markdown paket ve şablonları

<https://bookdown.org/yihui/rmarkdown/document-templates.html>

***

### Render Markdown via code

*inside R*

```
markdown::markdownToHTML('markdown_example.md', 
'markdown_example.html')
```

*command line*

```
R -e "markdown::markdownToHTML('markdown_example.md',
'markdown_example.html')"
```

***

### pandoc Rstudio integration

*command line*

```
export PATH=$PATH:/Applications/RStudio.app/Contents/MacOS/pandoc
```

```
R -e "rmarkdown::render('markdown_example.md')"
```

***

## RMarkdown `chunk` içinde `R` kodlarını çalıştırma

```
{r, results='asis'}
 iris %>%
  tibble::as_tibble() %>%
  details::details(summary = 'tibble')
```

***

## Metin arasında `R` kodlarını çalıştırma

***

## Chunk Options

### Global Options

```
{r global_options, include=FALSE}
knitr::opts_chunk$set(fig.width = 12,
                      fig.height = 8,
                      fig.path = 'Figs/',
                      echo = FALSE,
                      warning = FALSE,
                      message = FALSE,
                      error = FALSE,
                      eval = TRUE,
                      tidy = TRUE,
                      comment = NA)
```

***

### Other Code Languages

[![](https://d33wubrfki0l68.cloudfront.net/162347ef5afe219da22fb7d7d9a5989f2c3e5a85/59316/lesson-images/languages-1-demos.png)](https://rmarkdown.rstudio.com/lesson-5.html)

***

## R Markdown kod örneği

```
{r}
data("cancer")
cancer
foreign::write.foreign(df = cancer,
                        datafile = "data/cancer.sav",
                        codefile = "data/cancer.spo",
                        package = "SPSS"
                        )
```

***

## R Markdown Paket Çağırma 📦

```
{r}
suppressPackageStartupMessages(library("tidyverse"))
suppressPackageStartupMessages(library("survival"))
```

***

### Sık kullandığım paketler 📦

{tidyverse} {tidylog}

{lubridate} {janitor}

{readxl} {foreign}

{summarytools} {ggstatsplot} {tangram} {finalfit} {psycho} {jmv}

{survival} {survminer}

{report} {kableExtra}

***

## R Markdown Veri Yükleme SPSS

***

## R Markdown Veri Yükleme Excel

***

## Veri Görüntüleme

```
{r}
View(mydata)
glimpse(mydata)
```

***

## Veri Düzenleme

```
{r}
mydata <- janitor::clean_names(mydata)
```

```
{r}
mydata$sontarih <- janitor::excel_numeric_to_date(
  as.numeric(mydata$olum_tarihi)
  )
```

***

## Recode

```
{r}
mydata$Outcome <- "Dead"
mydata$Outcome[mydata$olum_tarihi == "yok"] <- "Alive"
```

```
{r}
## Recoding mydata$cinsiyet into mydata$Cinsiyet
mydata$Cinsiyet <- recode(mydata$cinsiyet,
               "K" = "Kadin",
               "E" = "Erkek")
mydata$Cinsiyet <- factor(mydata$Cinsiyet)
```

***

## Recode regular expression

```
{r recode TNM stage}
#pT2N0Mx -> 2
mydata$Tstage <- stringr::str_match(
  mydata$patolojik_evre, 
  paste('(.+)', "N", sep=''))[,2]
)
```

***

## Recode regular expression case\_when

```
{r recode TNM2}
mydata <- mydata %>% 
    mutate(
        T_stage = case_when(
            grepl(pattern = "T1", x = .$Tstage) == TRUE ~ "T1",
            grepl(pattern = "T2", x = .$Tstage) == TRUE ~ "T2",
            grepl(pattern = "T3", x = .$Tstage) == TRUE ~ "T3",
            grepl(pattern = "T4", x = .$Tstage) == TRUE ~ "T4",
            TRUE ~ "Tx"
        )
    )
```

***

## Recode regular expression case\_when

```
{r}
mydata <- mydata %>% 
    mutate(
TumorPDL1gr1 = case_when(
        t_pdl1 < 1 ~ "kucuk1",
        t_pdl1 >= 1 ~ "buyukesit1"
    )
    )
```

***

## R Markdown Tanımlayıcı İstatistikler

```
{r}
library(summarytools)
view(dfSummary(colon_s))
```

***

A beginner kit for #rstats The Landscape of R Packages for Automated Exploratory Data Analysis <https://journal.r-project.org/archive/2019/RJ-2019-033/>

@article{RJ-2019-033, author = {Mateusz Staniak and Przemysław Biecek}, title = {{The Landscape of R Packages for Automated Exploratory Data Analysis}}, year = {2019}, journal = {{The R Journal}}, doi = {10.32614/RJ-2019-033}, url = {<https://journal.r-project.org/archive/2019/RJ-2019-033/index.html}> }

***

### Table One

```
{r, results='asis'}
# cat(names(mydata), sep = " + \n")
library(arsenal)
tab1 <- tableby(~ Cinsiyet + 
Yas + 
TumorYerlesimi
                ,
                data = mydata)
summary(tab1)
```

***

### The Grammar of Tables

[tangram: The Grammar of Tables](https://cran.r-project.org/web/packages/tangram/)

[A grammar of tables](https://github.com/leeper/tttable)

[Grammar of Tables?](https://gist.github.com/leeper/f9cfbe6bd185763762e126a4d8d7c286)

[Easily generate information-rich, publication-quality tables from R](https://gt.rstudio.com)

***

### Kategorik Veriler

```
{r}
mydata %>% 
  janitor::tabyl(Categorical) %>%
  adorn_pct_formatting(rounding = 'half up',
                       digits = 1) %>%
  knitr::kable()
```

```
{r crosstable}
mydata %>%
    summary_factorlist(dependent = dependent, 
                       explanatory = explanatory,
                       total_col = TRUE,
                       p = TRUE,
                       add_dependent_label = TRUE) -> table
knitr::kable(table, row.names = FALSE, align = c('l', 'l', 'r', 'r', 'r'))
```

***

### Kategorik Veriler için Grafikler

```
{r ggstatplot, layout='l-page'}
mydata %>% 
    ggstatsplot::ggbarstats(data = .,
                            main = Categorical_variable,
                            condition =  dependent_variable
                            )
```

***

### Continious Variables

```
{r}
mydata %>% 
jmv::descriptives(
    data = .,
    vars = c(yas),
    hist = TRUE,
    dens = TRUE,
    box = TRUE,
    violin = TRUE,
    dot = TRUE,
    mode = TRUE,
    sd = TRUE,
    variance = TRUE,
    skew = TRUE,
    kurt = TRUE,
    quart = TRUE)
```

***

## R Markdown örneği Çapraz Tablolar

```
{r crosstable}
library(finalfit)
mydata %>%
    summary_factorlist(dependent = dependent, 
                       explanatory = explanatory,
                       column = TRUE,
                       total_col = TRUE,
                       p = TRUE,
                       add_dependent_label = TRUE,
                       na_include=FALSE
                       # catTest = catTestfisher
                       ) -> table
knitr::kable(table,
             row.names = FALSE,
             align = c('l', 'l', 'r', 'r', 'r'))
```

***

## R Markdown örneği Sağkalım

* Drawing Survival Curves Using ggplot2\
  <https://rpkgs.datanovia.com/survminer/reference/ggsurvplot.html>

### Sağkalım için veriyi düzenleme

```
{r define survival time}
mydata$int <- lubridate::interval(
  lubridate::ymd(mydata$CerrahiTarih),
  lubridate::ymd(mydata$SonTarih)
  )
mydata$OverallTime <- lubridate::time_length(mydata$int, "month")
mydata$OverallTime <- round(mydata$OverallTime, digits = 1)
```

```
{r}
## Recoding mydata$Outcome into mydata$Outcome2
mydata$Outcome2 <- recode(mydata$Outcome,
               "Alive" = "0",
               "Dead" = "1")
mydata$Outcome2 <- as.numeric(mydata$Outcome2)
```

***

### Kaplan-Meier

```
{r Kaplan-Meier}
mydata %>%
  finalfit::surv_plot(dependent,
                      explanatory,
                      xlab='Time (months)',
                      pval=TRUE,
                      legend = 'none',
                      break.time.by = 12,
                      xlim = c(0,60),
                      legend.labs = c('a','b')
)
```

***

### Sağkalım Tabloları

```
{r}
km_fit <- survfit(dependent ~ explanatory,
                  data = mydata)
km_fit
```

```
{r, eval=FALSE, include=FALSE}
library(survival)
km <- with(mydata, Surv(OverallTime, Outcome2))
# head(km,80)
# plot(km)
```

```
{r 1-3-5-yr}
summary(km_fit, times = c(12,36,60))
```

***

### Pairwise comparison

```
{r}
survminer::pairwise_survdiff(formula = Surv(time, Outcome) ~ Group, 
                             data = mydata,
                             p.adjust.method = "BH")
```

***

### Multivariate Analysis Survival

```
{r Multivariate Analysis, eval=FALSE, include=FALSE}
library(finalfit)
library(survival)
explanatoryMultivariate <- explanatoryKM
dependentMultivariate <- dependentKM
mydata %>%
  finalfit(dependentMultivariate, explanatoryMultivariate) -> tMultivariate
knitr::kable(tMultivariate, row.names=FALSE, align=c("l", "l", "r", "r", "r", "r"))
```

***

## jamovi

### jamovi ve R entegrasyonu

[Rj Editor – Analyse your data with R in jamovi](https://blog.jamovi.org/2018/07/30/rj.html)

***

### {jmv} paket kodları

[jamovi syntax mode](https://www.jamovi.org/user-manual.html#syntax-mode)

***

## Güncellemeler olunca kodlar çalışacak mı?

***

### Paket Kütüphaneleri

* packrat / renv

<https://environments.rstudio.com>

***

### Docker

* docker

***

#### The Rocker Project

Docker Containers for the R Environment

```
docker run --rm -ti rocker/r-base
```

Or get started with an RStudio® instance:

```
docker run -e PASSWORD=yourpassword --rm -p 8787:8787 rocker/rstudio
```

and point your browser to <localhost:8787> Log in with user/password rstudio/yourpassword

***

[Managing containers](https://www.rocker-project.org/use/managing_containers/)

***

### Yeni R sürümleri

* RSwitch

<https://rud.is/rswitch/>

* Using RSwitch

<https://rud.is/rswitch/guide/>

![: scale 30%](https://rud.is/rswitch/guide/menu-info.png)

***

## Yedeklemeyi nasıl yapacağız

### Projeyi düzgün organize edin

* pdf
* R
* images
* bib

```
{r load library}
source(file = here::here("R", "loadLibrary.R"))
```

***

### Save Final Data

```
{r}
saved data after analysis to `mydata.xlsx`.

save.image(file = here::here("data", "mydata_work_space.RData"))

readr::write_rds(x = mydata, path = here::here("data", "mydata_afteranalysis.rds"))

saveRDS(object = mydata, file = here::here("data", "mydata.rds"))

writexl::write_xlsx(mydata, here::here("data", "mydata.xlsx"))

paste0(rownames(file.info(here::here("data", "mydata.xlsx"))), " : ", file.info(here::here("data", "mydata.xlsx"))$ctime)

```

***

### GitHub Yedekleme

***

## Her dökümanın sonuna kullandığınız kütüphaneler için atıf yazdırabilirsiniz

```
{r}
citation()
```

***

### Libraries Used

```r
citation()
```

```

To cite R in publications use:

  R Core Team (2019). R: A language and environment for
  statistical computing. R Foundation for Statistical Computing,
  Vienna, Austria. URL https://www.R-project.org/.

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2019},
    url = {https://www.R-project.org/},
  }

We have invested a lot of time and effort in creating R, please
cite it when using it for data analysis. See also
'citation("pkgname")' for citing R packages.
```

***

### Bu oturuma spesifik kullanılan paketler

***

### Tek tek paket atıfları

```
{r library citations}
citation("tidyverse")
citation("readxl")
citation("janitor")
citation("report")
citation("finalfit")
citation("ggstatplot")
```

***

### Jamovi ve R için atıf örneği

* The jamovi project (2019). jamovi. (Version 0.9) \[Computer Software]. Retrieved from <https://www.jamovi.org>.
* R Core Team (2018). R: A Language and envionment for statistical computing. \[Computer software]. Retrieved from <https://cran.r-project.org/>.
* Fox, J., & Weisberg, S. (2018). car: Companion to Applied Regression. \[R package]. Retrieved from <https://cran.r-project.org/package=car>.

***

## Her dökümanın sonuna oturum detaylarınızı yazdırabilirsiniz

```
{r session info, echo=TRUE}
sessionInfo()
```

***

### Session Info

```r
sessionInfo()
```

```
R version 3.6.0 (2019-04-26)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS  10.15

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] compiler_3.6.0   magrittr_1.5     formatR_1.7      htmltools_0.4.0 
 [5] tools_3.6.0      yaml_2.2.0       Rcpp_1.0.2       codetools_0.2-16
 [9] stringi_1.4.3    rmarkdown_1.16   rmdshower_2.1.1  knitr_1.25      
[13] stringr_1.4.0    xfun_0.10        digest_0.6.21    rlang_0.4.1     
[17] evaluate_0.14   
```

***

## Sonraki Konular

* RStudio ile GitHub kullanımı
* ...

***

## Önerilen Kaynaklar

* [Reproducible Templates for Analysis and Dissemination](https://www.coursera.org/learn/reproducible-templates-analysis/home/info)
* [Happy Git and GitHub for the useR](https://happygitwithr.com/)

***

## Sunum Linkleri

<https://sbalci.github.io/MyRCodesForDataAnalysis/R-Markdown.nb.html> <https://sbalci.github.io/MyRCodesForDataAnalysis/R-Markdown.html>

<https://forms.gle/UqGJBiAjB8uLPRon8>

***

## Geri Bildirim

* Geri bildirim için tıklayınız: [*Geri bildirim formu*](https://goo.gl/forms/YjGZ5DHgtPlR1RnB3)

***

\
/\*\*

* RECOMMENDED CONFIGURATION VARIABLES: EDIT AND UNCOMMENT THE SECTION BELOW TO INSERT DYNAMIC VALUES FROM YOUR PLATFORM OR CMS.
* LEARN WHY DEFINING THESE VARIABLES IS IMPORTANT: <https://disqus.com/admin/universalcode/#configuration-variables\\*/> /\* var disqus\_config = function () { this.page.url = PAGE\_URL; // Replace PAGE\_URL with your page's canonical URL variable this.page.identifier = PAGE\_IDENTIFIER; // Replace PAGE\_IDENTIFIER with your page's unique identifier variable }; \*/ (function() { // DON'T EDIT BELOW THIS LINE var d = document, s = d.createElement('script'); s.src = '<https://https-sbalci-github-io.disqus.com/embed.js>'; s.setAttribute('data-timestamp', +new Date()); (d.head || d.body).appendChild(s); })();

Please enable JavaScript to view the [comments powered by Disqus.](https://disqus.com/?ref_noscript)

***

## İletişim

Completed on 2019-11-01.

Serdar Balci, MD, Pathologist\
<drserdarbalci@gmail.com>

<https://rpubs.com/sbalci/CV\\>
<https://sbalci.github.io/\\>
<https://github.com/sbalci\\>
<https://twitter.com/serdarbalci>