Last updated: 2022-08-12

Checks: 6 1

Knit directory: GitHub-with-RStudio-LICAE/

This reproducible R Markdown analysis was created with workflowr (version 1.7.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

R Markdown file: uncommitted changes

The R Markdown file has unstaged changes. To know which version of the R Markdown file created these results, you’ll want to first commit it to the Git repo. If you’re still working on the analysis, you can ignore this warning. When you’re finished, you can run wflow_publish to commit the R Markdown file and build the HTML.

Environment: empty

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

Seed: set.seed(20220715)

The command set.seed(20220715) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Session information: recorded

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Cache: none

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

File paths: relative

Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.

Repository version: ceab820

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version ceab820. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated: 


Ignored files:
    Ignored:    .Rproj.user/

Unstaged changes:
    Modified:   analysis/PCA.Rmd
    Modified:   analysis/about.Rmd
    Modified:   analysis/index.Rmd
    Modified:   analysis/license.Rmd
    Modified:   analysis/pre-requisitos.Rmd
    Modified:   analysis/using-this-material.Rmd

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/using-this-material.Rmd) and HTML (docs/using-this-material.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File Version Author Date Message
Rmd 89b7811 WevertonGomesCosta 2022-08-12 Update
html 7bf6676 WevertonGomesCosta 2022-08-06 Update
Rmd b1c0b81 WevertonGomesCosta 2022-08-06 Update

Pré-requisitos

  1. Você precisa instalar R, Rstudio e pacotes R relevantes com antecedência.

As instruções estão na próxima seção.

  1. Você precisa conhecer pelo menos alguma sintaxe do R. Links para recursos de aprendizagem também são fornecidos em uma seção abaixo. Se você nunca usou R antes, terá problemas para seguir os aspectos de codificação deste manual.

Instalar software e pacotes

Pacotes R, Rstudio, R

install.packages(c("tidyverse","workflowr"))

Crie uma conta no GitHub

Gostaríamos de ensinar a você uma abordagem reproduzível e de acesso aberto para ciência de dados e seleção genômica.

Para começar, acesse https://github.com/ e crie uma conta gratuita, caso ainda não tenha uma.

Git

Os três possíveis aplicativos de emulador do Linux que os colegas me recomendaram para usuários do Windows:

1. Subsistema Windows para Linux: https://docs.microsoft.com/en-us/windows/wsl/install

2. Git BASH para Windows: https://gitforwindows.org/

3. Cygwin: https://www.cygwin.com/

Aconcelho a instalar o Git BASH para o Windowns

Aprendendo R e mais

Teclas de atalho

Muito importante aprender alguns deles, especialmente estes:

  • ctrl+alt+I = criar bloco
  • Shift+ctrl+M = operador pipe %>%
  • ctrl+Enter = enviar (executar) linhas de código em seu script Rmd ou R para o console.

sessionInfo()
R version 4.1.3 (2022-03-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)

Matrix products: default

locale:
[1] LC_COLLATE=Portuguese_Brazil.1252  LC_CTYPE=Portuguese_Brazil.1252   
[3] LC_MONETARY=Portuguese_Brazil.1252 LC_NUMERIC=C                      
[5] LC_TIME=Portuguese_Brazil.1252    

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

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.9       rstudioapi_0.13  whisker_0.4      knitr_1.39      
 [5] magrittr_2.0.3   workflowr_1.7.0  R6_2.5.1         rlang_1.0.4     
 [9] fastmap_1.1.0    fansi_1.0.3      stringr_1.4.0    tools_4.1.3     
[13] xfun_0.31        utf8_1.2.2       cli_3.3.0        git2r_0.30.1    
[17] jquerylib_0.1.4  htmltools_0.5.3  rprojroot_2.0.3  yaml_2.3.5      
[21] digest_0.6.29    tibble_3.1.8     lifecycle_1.0.1  later_1.3.0     
[25] sass_0.4.2       vctrs_0.4.1      promises_1.2.0.1 fs_1.5.2        
[29] cachem_1.0.6     glue_1.6.2       evaluate_0.16    rmarkdown_2.14  
[33] stringi_1.7.6    bslib_0.4.0      compiler_4.1.3   pillar_1.8.0    
[37] jsonlite_1.8.0   httpuv_1.6.5     pkgconfig_2.0.3