The R API is very similar to PyKaka. It loads data from the database Kaka using its RESTful API.
Kaka runs using docker. The docker installation includes a Pyrat (Jupyter notebook) instance on port 8888. rkaka is pre-installed on that pyrat instance.
If you are on the above mentioned Kaka Pyrat instance just call library("rkaka"). Otherwise use:
devtools::install_github("hdzierz/rkaka")
The syntax for the API is as follows:
kaka.qry(realm='some_realm', qry='some_query')
Whereby:
"realm" can currrently be:
"qry":
This is a pql query. For more info see: pql
"mode":
Return value:
The return value is an R data frame.
Example:
To obtain data from Kaka you run which loads an example data set:
dat <- kaka.qry('genotype', experiment=='Gene Expression')
dat
Or more complicated:
dat <- kaka.qry('genotype', "experiment=='Gene Expression' and gene==regex('^AT1G029.*')")
dat
Gene expression data (any data really) can be supplemented with exprimental design information similar to the old micro array targets file:
dat <- kaka.qry('design', "experiment=='Gene Expression'")
dat
phenotype condition typ
1 PFD1001L3R1 treated paired-end
2 PFD1001L3R2 treated paired-end
3 PFD1001L4R1 treated paired-end
4 PFD1001L4R2 treated paired-end
5 PFD1002L3R1 untreated paired-end
6 PFD1002L3R2 untreated paired-end
7 PFD1002L4R1 untreated paired-end
8 PFD1002L4R2 untreated paired-end
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