R Observatory: Metrics for spqrp version 0.1.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

spqrp

0.1.0Package record

Sample Provenance Quality Resolver in Proteomics

0packages depend

863downloads / year

71.4%test coverage

13/13flavors OK

Overview

About

Maintained by Franziska HradilakCRAN page ↗GitHub ↗Issues ↗

Detect sample-provenance inconsistencies and potential mix-ups in mass-spectrometry-based plasma-proteome cohorts. Provides a clustering-based approach (build a nearest-neighbour graph in a dimensionality-reduced space and iteratively split large components by edge weight), a threshold-based approach (classify sample pairs as belonging or not-belonging from a pairwise distance cutoff), parameter optimization over distance metrics and cutoffs, and a pairwise random-forest classifier for protein importance ranking. This is a native R port of the author's Python package 'spqrp' (https://github.com/fhradilak/spqrp), implementing methods from an associated manuscript currently in preparation.

Changes in 0.1.0

Initial CRAN-targeted release. Native R port of the Python spqrp

package.

Features

**Clustering pipeline** (run_clustering()) -- kNN graph in a PCA/UMAP/MDS embedding, optional iterative split of large components, ggplot visualization with patient-hue colouring and legend.
**Threshold-based evaluation** (perform_distance_evaluation_on_ranked_proteins()) -- pairwise sample classification from a percentile cutoff on pairwise distances, with FN/FP/percentile-overlay histogram.
**Protein ranking** (train_with_normalise()) -- pairwise random- forest classifier with three selectable backends; randomForest is the default (closest behaviour to Python's imblearn.BalancedRandomForestClassifier). Importance values are normalised to sum to 1.0, matching sklearn's clf.feature_importances_ convention.

Show all changes in 0.1.0Hide the rest of the changes in 0.1.0

**Isolation-forest outlier filtering** (remove_outlier_samples()) -- pure-R via the solitude package; default outlier_threshold calibrated empirically for solitude's anomaly-score scale.

Verbosity

All functions are silent by default. Pass quiet = FALSE to any

function that emits status output to see progress messages, per-call

summaries, save-path hints, and cluster listings. Warnings about

genuine data issues -- e.g. samples dropped from analysis -- fire

regardless of quiet.

Documentation

See articles/numerical-divergence.md for known cross-language divergences (UMAP, random-forest backends, isolation-forest scales, MDS solvers) and recommendations for cross-language comparison.
See vignette("spqrp-mock-data") for a worked example on a small bundled cohort.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("spqrp", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("fhradilak/spqrp_r")

Development version from fhradilak/spqrp_r. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-spqrp

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-spqrp

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-spqrp

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 2.3 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-04
NOTE12 OK, 1 NOTE2026-08-01
OK7 OK2026-06-18

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.1.0

READMEYes · 542 wordsVignettesYes · 1 · dynamicNEWSYes · 67% structured · mentions 0.1.0Citation fileYes · software entry onlyWebsitenot declared in DESCRIPTION

Help pages: 32 (15 internal)includes a package overview page
Examples that run: 44%7 run in a plain check · 9 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 100%
Documented parameters: 97%
Return-value docs: 100%
Help pages citing references: 0%

Vignettes (1)

spqrp on mock data HTML

How these are measured

Downloads

863

CRAN downloads in the past year

Rank #24,105 · ~2/day · ~72/mo

Releases R versions

Daily download trend is not available in this view yet.

18230 days

52690 days

8631 year

Compare downloads with other packages →

Also on18 r2u

How downloads are counted

Repository

fhradilak/spqrp_r ↗Account: fhradilak

0Stars

0Forks

0Open issues

0Open PRs

1Releases

3Commits

1Commit identities

3 commits · Last activity 2026-06-22

Responsiveness

not measured

Releases over time

2026-06-09 · 12026-07-07 · 1

How these are measured

PracticesBeta

4 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/fhradilak/spqrp_r on 2026-10-21.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Reproducibility and dev environment (1)

data-raw/

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies

22 external dependencies (excludes base and recommended)

Installing spqrp adds 44 packages (24 with compiled code, 45 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.

Depends (1)

R >= 4.5.0

Imports (15)

cli dplyr ggplot2 igraph lgr pROC randomForest ranger rlang solitudestatstibble tidyrutilswithr

LinkingTo (0)

none

Suggests (9)

knitr plotly recipes rmarkdown smacof testthat themis uwot vdiffr

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (1)

Franziska Hradilak

Author, Maintainer since 0.1.0 (2026)

Releases (1)

0.1.0Latest
record
2026-06-17 · current release
R
R 4.6.0 released · 2026-04-24

Package metadata

First published: 2026-06-17
Total releases: 1 / 1 yrs
License: GPL-3 OSI
Minimum R: ≥ 4.5.0
Bundled data: 9.6 KB / 1 file
Download size: 230 KB

Cite

Cite this package

Run in R for the authors' entry:

citation("spqrp")

The package provides a citation file, so citation() returns the authors' own entry.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for spqrp version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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