Package: spqrp 0.1.0
spqrp: Sample Provenance Quality Resolver in Proteomics
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.
Authors:
spqrp_0.1.0.tar.gz
spqrp_0.1.0.zip(r-4.7)spqrp_0.1.0.zip(r-4.6)spqrp_0.1.0.zip(r-4.5)
spqrp_0.1.0.tgz(r-4.6-any)spqrp_0.1.0.tgz(r-4.5-any)
spqrp_0.1.0.tar.gz(r-4.7-any)spqrp_0.1.0.tar.gz(r-4.6-any)
spqrp_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
spqrp/json (API)
NEWS
| # Install 'spqrp' in R: |
| install.packages('spqrp', repos = c('https://fhradilak.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/fhradilak/spqrp_r/issues
- cohort_a_ranking - Protein-importance ranking for plasma cohort "A"
Last updated from:c97b401a13. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 200 | ||
| source / vignettes | OK | 274 | ||
| linux-release-x86_64 | OK | 196 | ||
| macos-release-arm64 | OK | 160 | ||
| macos-oldrel-arm64 | OK | 177 | ||
| windows-devel | OK | 168 | ||
| windows-release | OK | 133 | ||
| windows-oldrel | OK | 121 | ||
| wasm-release | OK | 144 |
Exports:by_isolation_forestcheck_input_data_formatfilter_by_occurrencelog_transformnormalize_medianintensityoptimize_parametersperform_distance_evaluation_on_ranked_proteinsplate_correct_residuals_by_proteinremove_outlier_samplesretrieve_rankingrun_clusteringspqrp_example_dataspqrp_example_pathtrain_pairwise_balanced_rand_foresttrain_with_normalise
Dependencies:clicodetoolscpp11data.tabledigestdplyrfarverfuturefuture.applygenericsggplot2globalsgluegtableigraphisobandlabelinglatticelgrlifecyclelistenvmagrittrMatrixparallellypillarpkgconfigpROCpurrrR6randomForestrangerRColorBrewerRcppRcppEigenrlangS7scalessolitudestringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
