genesysr tutorial

.gitignore

@@ -5,3 +5,4 @@
 man
 README.Rmd
 cran-comments.md
+inst/doc

DESCRIPTION

@@ -15,3 +15,6 @@ License: Apache License 2.0
 RoxygenNote: 6.0.1
 URL: https://gitlab.croptrust.org/genesys-pgr/genesysr
 BugReports: https://gitlab.croptrust.org/genesys-pgr/genesysr/issues
+Suggests: knitr,
+    rmarkdown
+VignetteBuilder: knitr

vignettes/tutorial.Rmd

+---
+title: "genesysr"
+author: "Nora Castaneda & Matija Obreza"
+date: "`r Sys.Date()`"
+output: rmarkdown::html_vignette
+vignette: >
+  %\VignetteIndexEntry{Vignette Title}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+---
+
+Genesys data download
+=====================
+Genesys provides data primarily through the `fetch_accessions` function. Data download using **genesysr** is equivalent to downloading data from www.genesys-pgr.org, with the advantage that **genesysr** ensures reproducibility.
+
+Filters to query Genesys are:
+
+- `fetch_accessions(filters = list(taxonomy.genus = c('Musa')))` - Retrieve all accession data for genus *Musa*
+- `fetch_accessions(list(institute.code = c('BEL084')))` - Retrieve all accession data for the Musa International Transit Center, Bioversity International
+- `fetch_accessions(list(institute.code = c('BEL084','COL003')))` - Retrieve all accession data for the Musa International Transit Center, Bioversity International (BEL084) and the International Center for Tropical Agriculture (COL003)
+
+And also by using [Multi-Crop Passport Descriptors (MCPD)](https://www.genesys-pgr.org/doc/0/basics#mcpd) definitions:
+
+- `fetch_accessions(mcpd_filter(ORIGCTY = c("DEU", "SVN")))` - Retrieve data by country of origin (MCPD)
+
+# Selecting columns for data download
+Genesys fetches all accession data by data. One can reduce the amount of data fetched by selecting only the columns of interest:
+
+- `fetch_accessions(list(taxonomy.genus = c('Musa')), selector = function(x) {list(id = x$id, acceNumb = x$acceNumb, instCode = x$institute$code)`- Fetch only **id**, **acceNumb** and **instCode** for *Musa* data.
+
+# Processing fetched data
+Fetched data is provided as a deeply nested list. To flatten such list, we recommend the following procedure:
+
+```r
+require(tidyverse)
+musa.flatten <- lapply(musa$content, unlist) #looks good
+musa.flatten <- musa.flatten %>% map_df(bind_rows)
+```
+Let's take a look of all the process:
+
+## Load genesysr
+
+```r
+library(genesysr)
+```
+
+## Setup using credentials
+```r
+setup_sandbox()
+user_login()
+```
+
+## Fetch data
+
+```r
+musa <- genesysr::fetch_accessions(list(taxonomy.genus = c('Musa')))
+```
+
+## Flatten data into data frame
+
+```r
+require(tidyverse)
+musa.flatten <- lapply(musa$content, unlist) #looks good
+musa.flatten <- musa.flatten %>% map_df(bind_rows)
+```
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