mi4p-package

mi4p: Multiple Imputation for Proteomics

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. package

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

Useful links:

• https://mariechion.github.io/mi4p/
• https://github.com/mariechion/mi4p/
• Report bugs at https://github.com/mariechion/mi4p/issues/

Author(s)

Maintainer : Frederic Bertrand frederic.bertrand@utt.fr (ORCID)

Authors:

• Marie Chion mariechion@protonmail.com (ORCID)
• Christine Carapito ccarapito@unistra.fr (ORCID)

Other contributors:

• Gordon Smyth [contributor]
• Davis McCarthy [contributor]
• Hélène Borges [contributor]
• Thomas Burger [contributor]
• Quentin Giai-Gianetto [contributor]
• Samuel Wieczorek [contributor]