Last updated: 2022-12-14
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.
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.
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.
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.
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The results in this page were generated with repository version 95b0cf2. 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
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). workflowr only checks the R Markdown
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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/_site.yml
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 | 06cdd23 | WevertonGomesCosta | 2022-08-12 | Update |
html | 06cdd23 | WevertonGomesCosta | 2022-08-12 | Update |
html | 2c52bea | WevertonGomesCosta | 2022-08-12 | Update |
Rmd | 512947f | WevertonGomesCosta | 2022-08-12 | Update |
html | 512947f | WevertonGomesCosta | 2022-08-12 | Update |
Rmd | 89b7811 | WevertonGomesCosta | 2022-08-12 | Update |
html | 7bf6676 | WevertonGomesCosta | 2022-08-06 | Update |
Rmd | b1c0b81 | WevertonGomesCosta | 2022-08-06 | Update |
As instruções estão na próxima seção.
Instale R e Rstudio
Instalar pacotes
tidyverse
(inclui dplyr
,
tidyr
, ggplot2
, magrittr
e outros
realmente úteis)workflowr
install.packages(c("tidyverse","workflowr"))
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.
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
R for Data Science (https://r4ds.had.co.nz/):
Como a equipe do Rstudio / Tidyverse recomenda aqui (https://www.tidyverse.org/learn/), este livro é “o
melhor lugar para começar a aprender o arrumado”. Quase qualquer pessoa
deve ser capaz de (1) ler a breve introdução e (2) examinar o índice e
encontrar rapidamente um ponto de partida que atenda ao seu nível /
interesse.
Laboratório de desafio de dados (https://datalab.stanford.edu/challenge-lab)
Onde os alunos desenvolvem suas habilidades de dados resolvendo
uma progressão de desafios cada vez mais difíceis. Acabei de descobrir
isso. Há muito aqui que eu acho que é útil. Especialmente entre o
“Conteúdo Aberto” (https://dcl-docs.stanford.edu/home/). Por exemplo:
Disputa de dados
https://dcl-wrangle.stanford.edu/manip-basics.html
Programação Funcional
https://dcl-prog.stanford.edu/
https://dcl-prog.stanford.edu/purrr-mutate.html (me
disseram que meus loops usando funções do pacote purrr são confusos.. .
Veja isso).
Também:https://dcl-prog.stanford.edu/purrr-parallel.html
Aprenda o tidyverse https://www.tidyverse.org/learn/
https://www.tidyverse.org/packages/
APS 135: Introdução à Análise Exploratória de Dados com
R
(https://dzchilds.github.io/eda-for-bio/)
Tem algumas seções de introdução úteis sobre o básico do R e do Rstudio,
parece ter saído de um departamento de ciência de plantas, então existe
isso.
Stat545: organização, exploração e análise de dados com
R
https://stat545.com/
workflowR
%>%
Muito importante aprender alguns deles, especialmente estes:
ctrl+alt+I
= criar blocoShift+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_0.14 whisker_0.4 knitr_1.40
[5] magrittr_2.0.3 workflowr_1.7.0 R6_2.5.1 rlang_1.0.6
[9] fastmap_1.1.0 fansi_1.0.3 stringr_1.4.1 tools_4.1.3
[13] xfun_0.32 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_1.0.3 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_0.17 rmarkdown_2.17
[33] stringi_1.7.6 bslib_0.4.0 compiler_4.1.3 pillar_1.8.1
[37] jsonlite_1.8.0 httpuv_1.6.5 pkgconfig_2.0.3