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limpa is available as part of Bioconductor, see: https://bioconductor.org/packages/limpa. Please install limpa from Bioconductor, which always has the latest official version.

Questions about limpa can be sent to the Bioconductor support forum at https://support.bioconductor.org.

This repository is now used to host limpa documentation rather than to distribute code. The following vignettes and example analyses using limpa are available:

References

Li M, Cobbold SA, Smyth GK (2025). Quantification and differential analysis of mass spectrometry proteomics data with probabilistic recovery of information from missing values. bioRxiv https://doi.org/10.1101/2025.04.28.651125.

Li M, Smyth GK (2023). Neither random nor censored: estimating intensity-dependent probabilities for missing values in label-free proteomics. Bioinformatics 39(5), btad200. https://doi.org/10.1093/bioinformatics/btad200.

Huang AS#, Lieschke E#, Baldoni PL#, Thomas AF, Marchingo JM, Whelan L, Khuu G, La Marca E, Milevskiy M, Ross A, Johanson T, Potts M, Gibson L, Vaibhav V, Dagley L, Balihodcik A, Dengler M, Liu Z, Li K, Smyth GK*, Kelly G*, Strasser A* (2026). Pre-existing levels of pro-survival proteins and induction of BCL-XL dictate cell fate after p53 activation. bioRxiv https://doi.org/10.64898/2026.07.01.735749.

Corso LD, River IS, Al Halawani A, Gerak CAN, Gannon D, Ozaydin O, Li M, Thyagarajan K, Niezabitowski L, Chua NK, Tan W, Wudy SI, McLysaght A, Smyth GK, Shakeel S, Feltham R, Vervoort SJ (2026). INTS12 bridges Integrator and NELF to prevent the release of non-processive RNA polymerase II complexes. bioRxiv https://doi.org/10.64898/2026.01.16.699819.

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Documentation for the limpa Bioconductor package, which implements quantification and differential analysis of mass-spectrometry proteomics data, with probabilistic recovery of information from missing values using the detection probability curve.

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