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cff-version: 1.2.0
message: 'To cite package "kgraph" in publications use:'
type: software
license: GPL-3.0-only
title: 'kgraph: Knowledge Graphs Constructions and Visualizations'
version: 1.0.0
doi: 10.32614/CRAN.package.kgraph
abstract: 'Knowledge graphs enable to efficiently visualize and gain insights into
large-scale data analysis results, as p-values from multiple studies or embedding
data matrices. The usual workflow is a user providing a data frame of association
studies results and specifying target nodes, e.g. phenotypes, to visualize. The
knowledge graph then shows all the features which are significantly associated with
the phenotype, with the edges being proportional to the association scores. As the
user adds several target nodes and grouping information about the nodes such as
biological pathways, the construction of such graphs soon becomes complex. The ''kgraph''
package aims to enable users to easily build such knowledge graphs, and provides
two main features: first, to enable building a knowledge graph based on a data frame
of concepts relationships, be it p-values or cosine similarities; second, to enable
determining an appropriate cut-off on cosine similarities from a complete embedding
matrix, to enable the building of a knowledge graph directly from an embedding matrix.
The ''kgraph'' package provides several display, layout and cut-off options, and
has already proven useful to researchers to enable them to visualize large sets
of p-value associations with various phenotypes, and to quickly be able to visualize
embedding results. Two example datasets are provided to demonstrate these behaviors,
and several live ''shiny'' applications are hosted by the CELEHS laboratory and
Parse Health, as the KESER Mental Health application
based on Hong C. (2021) .'
authors:
- family-names: Charlon
given-names: Thomas
email: charlon@protonmail.com
orcid: https://orcid.org/0000-0001-7497-0470
- name: CELEHS
website: https://celehs.hms.harvard.edu
- name: PARSE Health
website: https://parse-health.org
repository: https://thomaschln.r-universe.dev
repository-code: https://gitlab.com/thomaschln/kgraph
commit: 979c8d1cccd708d897a689394c1db14e258a4d49
url: https://gitlab.com/thomaschln/kgraph
contact:
- family-names: Charlon
given-names: Thomas
email: charlon@protonmail.com
orcid: https://orcid.org/0000-0001-7497-0470