demo/MongoDB-IO.R

In opm: Analysing Phenotype Microarray and Growth Curve Data

#' # Analysing phenotype microarray data: `MongoDB` I/O

#' `MongoDB` is a popular document-oriented database. The **RMongo** package can
#' be used in conjunction with **opm** to store and receive phenotype microarray
#' data in such a database. `OPMX` objects fit nicely to such a pattern because
#' they do not impose a certain structure on the metadata, much like `MongoDB`
#' is able to store any kinds of data structures. The same holds for the options
#' parts of the `aggr_settings` and `disc_settings` entries of `OPMX` objects.
#' So the only work that needs to be done is to convert between `OPMX` objects
#' and `JSON` strings.
#'
#' See the documentation of `MongoDB` and **RMongo** for further details.
#'
#' Author: *Markus Goeker*


library(RMongo)
library(opm)


#' ## Define helper function

#' In our case, **RMongo** unfortunately returns a data frame with one plate per
#' row and raw `JSON` strings per field. But the following short function is
#' able to convert all such results. Note that `opms` also takes care of names
#' converted by `to_yaml`, if any (see below).
#'
mongo2opm <- function(x) {
  x <- split(x, seq_len(nrow(x)))
  x <- rapply(x, rjson::fromJSON, "character", NULL, "replace")
  opms(x, precomputed = FALSE, skip = FALSE, group = TRUE)
}


#' ## Create `MongoDB` connection

#' Connect to database `test`, which comes with `MongoDB`. We will use the
#' collection `pmdata` to store `JSON` representations of `OPM` objects.
#'
conn <- mongoDbConnect("test", "localhost", 27017)
coll <- "pmdata"


#' ## Insert plates

#' We insert each plate separately to be able to query them separately. Note
#' that under these settings, `to_yaml` takes care of removing names with dots,
#' which are disallowed in `MongoDB`.
#'
result <- vapply(plates(vaas_4), function(plate) {
  dbInsertDocument(conn, coll, to_yaml(plate, json = TRUE, nodots = TRUE))
}, "")
stopifnot(result == "ok")
print(result)


#' ## Search for plates with *E. coli* as species entry in the metadata

got <- dbGetQuery(conn, coll, '{"metadata.Species": "Escherichia coli"}')
stopifnot(is.data.frame(got), dim(got) > 0)


#' ## Convert to list of `OPMX` objects

#' Conversion necessary. See comments to `mongo2opm` above.
#'
got <- mongo2opm(got)

#' Yields list with one element per plate type (only one plate type here).
#' Some checks:
#'
stopifnot(is.list(got), length(got) == 1, names(got) == plate_type(vaas_4))
got <- got[[1]]
stopifnot(is(got, "OPMS"), has_disc(got), dim(got) == c(2, dim(vaas_4)[-1]))
print(got)


#' ## Remove plates again

result <- dbRemoveQuery(conn, coll,
  '{$and: [{"csv_data": {$exists: true}}, {"measurements": {$exists: true}}]}')
stopifnot(result == "ok")
print(result)


#' ## Check whether some plates are left over

empty <- dbGetQuery(conn, coll, '{"metadata.Species": "Escherichia coli"}')
stopifnot(is.data.frame(empty), dim(empty) == 0)


#' ## Close connection

dbDisconnect(conn)
rm(conn)


#' ## Tidy up

detach("package:RMongo", unload = TRUE)