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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "ProteinPCA" in publications use:'
type: software
license: GPL-3.0-only
title: 'ProteinPCA: Principal Component Analysis (PCA) Tool on Protein Expression
  Data'
version: 0.1.0
doi: 10.32614/CRAN.package.ProteinPCA
abstract: Analysis of protein expression data can be done through Principal Component
  Analysis (PCA), and this R package is designed to streamline the analysis. This
  package enables users to perform PCA and it generates biplot and scree plot for
  advanced graphical visualization. Optionally, it supports grouping/clustering visualization
  with PCA loadings and confidence ellipses. With this R package, researchers can
  quickly explore complex protein datasets, interpret variance contributions, and
  visualize sample clustering through intuitive biplots. For more details, see Jolliffe
  (2001) <https://doi.org/10.1007/b98835>, Gabriel (1971) <https://doi.org/10.1093/biomet/58.3.453>,
  Zhang et al. (2024) <https://doi.org/10.1038/s41467-024-53239-9>, and Anandan et
  al. (2022) <https://doi.org/10.1038/s41598-022-07781-5>.
authors:
- family-names: Manlapaz
  given-names: Paul Angelo C.
  email: pacmanlapaz@gmail.com
  orcid: https://orcid.org/0000-0002-1203-2064
repository: https://piey27.r-universe.dev
commit: 3ecd7337a7b56d134d8ddd8146f00287929209dd
date-released: '2025-04-12'
contact:
- family-names: Manlapaz
  given-names: Paul Angelo C.
  email: pacmanlapaz@gmail.com
  orcid: https://orcid.org/0000-0002-1203-2064