Closed Sim1Pall8a closed 6 years ago
Hi @Sim1Pall8a
Thanks for submitting your package. We are taking a quick look at it and you will hear back from us soon.
The DESCRIPTION file for this package is:
Package: RGMQL
Type: Package
Title: GMQL function
Version: 0.99.0
Author: Simone Pallotta, Marco Masseroli
Maintainer: Simone Pallotta <simonepallotta@hotmail.com>
Description: This package brings GMQL functionalities into R environemnt.
GMQL stands for Genometric Query Language for extracting regions of interest from
experiments and for computing their properties,
with high-level operations for manipulating regions and for measuring their distances
This package offers flexible, robust, high performance functions to perform GMQL queries.
It provides two different approaches in writing GMQL queries:
a) REST based GMQL calls
b) standard R APIs
The REST approach allows user to manage remote big genomic dataset hosted in complex cluster based infrastructure.
Multiple REST invocation can run concurrently on remote infrastructure allowing user to test progress of every call.
The R APIs allow user to works with local data using batch-like approach where single invocation must be invoked sequentially
The REST approach allows to perform text-based GMQL queries while standard APIs implement distinct function for every GMQL operation.
The package provides a rich set of ancillary classes used by R APIs that allows sophisticated input/output management and sorting.
License: Artistic-2.0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: rscala(>= 2.4.0), httr, GenomicRanges, rtracklayer, data.table, utils, plyr, xml2, methods, S4Vectors, dplyr, stats
Depends: R(>= 3.3.2)
VignetteBuilder: knitr
Suggests: BiocStyle, knitr, rmarkdown
biocViews: Software,Infrastructure,DataImport
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Hi, @mtmorgan @LiNk-NY
This package need a manual installation of specific version of scala (2.11.8) and javaSE 8 and settings for JAVA_HOME and SCALA_HOME as environment variable for working correctly. how can I specify additional settings to be performed as a pre-install phase?
Bioconductor already offers this functionality in terms of SummarizedExperiment, RaggedExperiment, MultiAssayExperiment, GenomicRanges, etc. This API is not idiomatic from the R perspective, and has problematic dependencies on Java/Scala. So I'm worried that users will struggle to integrate this with their workflows. It would be great to see a scalable compute engine underneath our existing APIs.
@lawremi Thank you Michael for your fast answer. Can you elaborate it a bit more to better clarify it to us?
The RGMQL package has the aim to make available to R/Bioconductor users the powerful functionalities of GMQL (http://www.bioinformatics.deib.polimi.it/GMQL/), an innovative query language (as simple as SQL, but applicable to genomic data and metadata in text files) which allows through simple scripts the processing and evaluation of genomic region data of interest from big data of typically Next Generation Sequencing experiments.
Thanks to the new API of GMQL, the RGMQL package enables the user to apply the powerful GMQL functionalities through simple statements, either on data on user's computer or on a remote cluster where GMQL is installed (we provide public access to such a cluster, where public data from ENCODE and TCGA are available to be processed by GMQL). Furthermore, thanks to RGMQL, GMQL computation results are seamless provided within typical R structures (GRanges) for their easy management and processing with all the many function available in R.
To the best of our knowledge the functionalities that RGMQL offers are not currently available in Bioconductor.
Being developed for cloud computing, GMQL API are coded in Scala; for this reason we used the Rscala package and some settings listed above; if they are not idiomatic from the R perspective, please support us in how changing them to make the RGMQL package conform to Bioconductor. Other packages that use java libraries have been recently accepted and made available in Bioconductor. Thank you.
It would be good to clarify, e.g., in the vignette, what this does offer beyond the current capabilities in Bioconductor. Regardless, GMQL needs a better embedding in R. For example, the select()
function is going to conflict with the widely used dplyr package, and passing the expression as a string in another language is obviously not idiomatic. The cryptically named extend()
function seems analogous to stats::transform()
or dplyr::mutate()
. Etc.
A general problem with GMQL after my cursory inspection is that the flat structure of the data model makes it unclear whether the data are being restricted by sample, feature, or assay. It's important to carry those semantics through the API.
Sure, we can follow your advice and improve the package, but we would like before to solve the issues of the dependencies which prevent passing the automatic checking (particularly in windows environment). If these are not overcome, there is no point in working on the others. Can you help us to solve them? Thanks a lot.
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