Final changes for Bioc submission (#40)

* up

* up

* Fix links in ?MGnifyR

* up

* up

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: MGnifyR
 Type: Package
-Version: 0.99.26
+Version: 0.99.27
 Authors@R:
     c(person(given = "Tuomas", family = "Borman", role = c("aut", "cre"),
              email = "[email protected]",
@@ -12,11 +12,11 @@ Authors@R:
              comment = c(ORCID = "0000-0001-5537-637X")))
 Title: R interface to EBI MGnify metagenomics resource
 Description:
-    Utility package to facilitate integration and analysis of EBI Mgnify data in R.
-    The package can be used to import microbial data for instance into
+    Utility package to facilitate integration and analysis of EBI MGnify data
+    in R. The package can be used to import microbial data for instance into
     TreeSummarizedExperiment (TreeSE). In TreeSE format, the data is directly
     compatible with miaverse framework.
-biocViews: PackageTypeData, ExperimentData, MicrobiomeData, SequencingData
+biocViews: Software, Infrastructure, DataImport, MicrobiomeData, SequencingData, Metagenomics
 License: Artistic-2.0 | file LICENSE
 Encoding: UTF-8
 Depends:

R/MGnifyR.R

@@ -2,9 +2,9 @@
 #'
 #' \code{MGnifyR} implements an interface to the EBI MGnify database.
 #' See the vignette for a general introduction to this package.
-#' [About MGnify](https://www.ebi.ac.uk/metagenomics/about) for general MGnify
+#' \href{https://www.ebi.ac.uk/metagenomics/about}{About MGnify} for general MGnify
 #' information, and
-#' [API documentation](https://emg-docs.readthedocs.io/en/latest/api.html) for
+#' \href{https://emg-docs.readthedocs.io/en/latest/api.html}{API documentation} for
 #' details about the JSONAPI implementation.
 #' @name MGnifyR-package
 #' @aliases MGnifyR

vignettes/MGnifyR.Rmd

@@ -45,7 +45,7 @@ cutting-edge tools in microbiome down-stream analytics.
 `BiocManager`.
 
 ```{r install, eval=FALSE}
-BiocManager::install(MGnifyR)
+BiocManager::install("MGnifyR")
 ```
 
 # Load `MGnifyR` package
@@ -68,6 +68,9 @@ mg <- MgnifyClient(useCache = TRUE)
 mg
 ```
 
+The `MgnifyClient` object contains slots for each of the previously mentioned
+settings.
+
 # Functions for fetching the data
 
 ## Search data
@@ -92,10 +95,6 @@ samples <- vignette_MGnifyR[["samples"]]
 The result is a table containing accession IDs and description -- in this case
 -- on samples.
 
-```{r search_studies3}
-head(samples)
-```
-
 ## Find relevent **analyses** accessions
 
 Now we want to find analysis accessions. Each sample might have multiple
@@ -110,12 +109,8 @@ analyses_accessions <- searchAnalysis(mg, "samples", samples$accession)
 analyses_accessions <- vignette_MGnifyR[["analyses_accessions"]]
 ```
 
-By running the `searchAnalysis()` function, we get analysis IDs of samples that
-we fed as an input.
-
-```{r convert_to_analyses3}
-head(analyses_accessions)
-```
+By running the `searchAnalysis()` function, we get a vector of analysis IDs of
+samples that we fed as an input.
 
 ## Fetch metadata
 
@@ -130,12 +125,8 @@ analyses_metadata <- getMetadata(mg, analyses_accessions)
 analyses_metadata <- vignette_MGnifyR[["analyses_metadata"]]
 ```
 
-Metadata includes for example information on how analysis was conducted and
-what kind of samples were analyzed.
-
-```{r get_metadata3}
-head(analyses_metadata)
-```
+The returned value is a `data.frame` that includes metadata includes for example
+information on how analysis was conducted and what kind of samples were analyzed.
 
 ## Fetch microbiome data
 

vignettes/MGnifyR_long.Rmd

@@ -53,7 +53,7 @@ book that offers valuable guidance and support.
 `devtools`. `MGnifyR` should be built using the following snippet.
 
 ```{r install, eval=FALSE}
-BiocManager::install(MGnifyR)
+BiocManager::install("MGnifyR")
 ```
 
 # Load `MGnifyR` package