Learn R Programming

mi4p (version 1.3)

mi4p-package: mi4p: Multiple Imputation for Proteomics

Description

logo

A framework for multiple imputation for proteomics is proposed by Marie Chion, Christine Carapito and Frederic Bertrand (2021) tools:::Rd_expr_doi("10.1371/journal.pcbi.1010420"). It is dedicated to dealing with multiple imputation for proteomics.

Arguments

Author

Maintainer: Frederic Bertrand frederic.bertrand@lecnam.net (ORCID)

Authors:

Other contributors:

  • Gordon Smyth [contributor]

  • Davis McCarthy [contributor]

  • Hélène Borges [contributor]

  • Thomas Burger [contributor]

  • Quentin Giai-Gianetto [contributor]

  • Samuel Wieczorek [contributor]

References

M. Chion, Ch. Carapito and F. Bertrand (2021). Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics. tools:::Rd_expr_doi("doi:10.1371/journal.pcbi.1010420")

M. Chion, Ch. Carapito, F. Bertrand. Towards a more accurate differential analysis of multiple imputed proteomics data with mi4limma. Statistical Analysis of Proteomic Data: Methods and Tools, 2022. tools:::Rd_expr_doi("doi:10.1007/978-1-0716-1967-4_7")

See Also