https://sciordia.r-universe.devRecent package updates in sciordiaR-universehttps://github.com/sciordia.pnghttps://sciordia.r-universe.devSun, 18 Oct 2026 18:26:30 GMTsciordia@gmail.com (Sergio Ciordia)Provides an end-to-end workflow for differential abundance analysis of protein quantification data, with particular attention to missing values in data-independent acquisition (DIA) proteomics. Quantification reports exported from Spectronaut, DIA-NN and Proteome Discoverer for TMT and label-free experiments (DDA/DIA) are converted into a common data structure, normalised, optionally batch-corrected, imputed and analysed using limma or limpa. The package includes individual and two-stage imputation strategies that treat values assumed to be missing at random and missing not at random separately. Data-driven functions evaluate and rank normalisation and imputation workflows using simulated missingness or spike-in datasets with known ground truth, allowing method selection to be justified for each dataset. Results can be explored through interactive Highcharts visualisations, static ggplot2 and ComplexHeatmap figures, and sortable tables.https://github.com/r-universe/biocstaging/actions/runs/39165795464Sun, 18 Oct 2026 18:26:30 GMTNADIA0.99.3successhttps://biocstaging.r-universe.devhttps://github.com/BiocStaging/NADIANADIA.RmdNADIA.htmlAn introduction to NADIA2026-07-30 20:37:352026-10-17 20:11:02batch-correction.Rmdbatch-correction.htmlBatch correction: diagnose, correct, verify2026-07-30 20:37:352026-10-17 20:11:02benchmarking.Rmdbenchmarking.htmlBenchmarking with a spike-in: scoring against known truth2026-07-30 20:37:352026-10-17 20:11:02choosing-methods.Rmdchoosing-methods.htmlChoosing normalization and imputation methods2026-07-30 20:37:352026-10-17 20:11:02input-formats.Rmdinput-formats.htmlInput formats: reports and SummarizedExperiment objects2026-07-30 20:37:352026-10-17 20:11:02missing-values.Rmdmissing-values.htmlMissing values: what they mean and how to fill them2026-07-30 20:37:352026-10-17 20:11:02pattern-profiler.Rmdpattern-profiler.htmlPattern Profiler: identifying shared protein profiles2026-07-30 20:37:352026-10-17 20:11:02results-and-export.Rmdresults-and-export.htmlResults and export: sharing and preserving an analysis2026-07-30 20:37:352026-10-17 20:11:02visualization.Rmdvisualization.htmlVisualization: exploring and presenting results2026-07-30 20:37:352026-10-17 20:11:02sciordia@cnb.csic.es (Sergio Ciordia)Provides a set of functions for data manipulation with list objects, including mapping, filtering, grouping, sorting, updating, searching, and other useful functions. Most functions are designed to be pipeline friendly so that data processing with lists can be chained.https://github.com/r-universe/sciordia/actions/runs/38406291672Wed, 31 Dec 2025 00:40:07 GMTrlist0.4.6.2successhttps://sciordia.r-universe.devhttps://github.com/sciordia/rlist