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Merge pull request #32 from alexmccreight/master
fixed citations + wording
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‎README.md‎

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The methods are based on a new model for sparse multiple regression,
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which we call the "Sum of Single Effects" (SuSiE) model. This model,
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which will be described in a manuscript in preparation (Wang et al),
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lends itself to a particularly simple and intuitive fitting procedure
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-- effectively a Bayesian modification of simple forward selection,
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which we call "Iterative Bayesian Step-wise Selection".
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which is described in [Wang et al. (2020)](https://doi.org/10.1111/rssb.12388), lends itself to a particularly simple and intuitive fitting
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procedure -- effectively a Bayesian modification of simple forward
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selection, which we call "Iterative Bayesian Step-wise Selection".
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The output of the fitting procedure is a number of "Credible Sets"
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(CSs), which are each designed to have high probability to contain a
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can be confident that one of the variables has a non-zero coefficient,
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but they are too correlated to be sure which one.
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The package is developed by Gao Wang, Peter Carbonetto, Yuxin Zou,
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Kaiqian Zhang, and Matthew Stephens from the
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The package was initially developed by Gao Wang, Peter Carbonetto,
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Yuxin Zou, Kaiqian Zhang, and Matthew Stephens from the
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[Stephens Lab](https://stephenslab.uchicago.edu) at the University of
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Chicago.
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Chicago. It was later extended with new methods and implementations by
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Alexander McCreight from the [StatFunGen Lab](https://wanggroup.org/) at
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Columbia University.
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Please
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[post issues](https://github.com/stephenslab/susieR/issues) to ask
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## Citing this work
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If you find the `susieR` package or any of the source code in this
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repository useful for your work, please cite:
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repository useful for your work, please cite both:
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> G. Wang, G., Sarkar, A., Carbonetto, P. & Stephens, M. (2020). A
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> Wang, G., Sarkar, A., Carbonetto, P. & Stephens, M. (2020). A
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> simple new approach to variable selection in regression, with
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> application to genetic fine mapping. *Journal of the Royal
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> Statistical Society, Series B* **82**, 1273–1300.
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> https://doi.org/10.1111/rssb.12388
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If you use any of the summary data methods such as `susie_suff_stat`
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or `susie_rss`, please also cite:
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> McCreight, A., Cho, Y., Nachun, D., Li, R., Gan, H-Y., Stephens,
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> M., Carbonetto, P., Denault, W.R.P. & Wang, G. (2025). SuSiE 2.0:
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> improved methods and implementations for genetic fine-mapping and
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> phenotype prediction. Submitting to *Genome Biology*.
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If you use any of the summary data methods such as `susie_ss` or
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`susie_rss`, please also cite:
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> Zou, Y., Carbonetto, P., Wang, G. & Stephens, M. (2022). Fine-mapping
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> from summary data with the "Sum of Single Effects" model. *PLoS
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> Genetics* **18**, e1010299. https://doi.org/10.1371/journal.pgen.1010299
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If you use the Servin-Stephens prior on residual variance estimates
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(`estimate_residual_method = "Servin_Stephens"`), please also cite:
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> Denault, W.R.P., Carbonetto, P., Li, R., Consortium, A.D.F.G., Wang,
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> G. & Stephens, M. (2025). Accounting for uncertainty in residual
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> variances improves calibration of the "Sum of Single Effects" model
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> for small sample sizes. *bioRxiv*, 2025-05. Under review for *Nature
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> Methods*.
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If you use infinitesimal effects modeling (`unmappable_effects = "inf"`),
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please also cite:
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> Cui, R., Elzur, R.A., Kanai, M. et al. (2024). Improving fine-mapping
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> by modeling infinitesimal effects. *Nature Genetics* **56**, 162–169.
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> https://doi.org/10.1038/s41588-023-01597-3
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## Developer notes
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‎inst/CITATION‎

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citHeader("To cite the susieR package, please use:")
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citHeader("To cite the susieR package, please use both:")
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bibentry(bibtype = "Article",
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title = paste("A simple new approach to variable selection in",
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"regression, with application to genetic fine",
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"mapping"),
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author = c(person("Gao","Wang"),
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person("Abhishek","Sarkar"),
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person("Peter","Carbonetto"),
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person("Peter","Carbonetto"),
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person("Matthew","Stephens")),
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journal = "Journal of the Royal Statistical Society, Series B",
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year = "2020",
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volume = "82",
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pages = "1273-1300",
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bibentry(bibtype = "Article",
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title = paste("SuSiE 2.0: improved methods and implementations for",
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author = c(person("Alexander", "McCreight"),
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person("Ruixi", "Li"),
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person("Matthew", "Stephens"),
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journal = "Submitting to Genome Biology",
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"improved methods and implementations for genetic fine-mapping and",
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"phenotype prediction. Submitting to Genome Biology."))
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bibentry(header = "If susie_suff_stat or susie_rss is used, please also cite:",
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bibtype = "Article",
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title = paste('Fine-mapping from summary data with the',
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author = c(person("Yuxin","Zou"),
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person("Peter","Carbonetto"),
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person("Peter","Carbonetto"),
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person("Gao","Wang"),
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person("Matthew","Stephens")),
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journal = "PLoS Genetics",
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volume = "18",
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year = "2022",
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pages = "e1010299",
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doi = "10.1371/journal.pgen.1010299",
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'https://doi.org/10.1371/journal.pgen.1010299'))
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bibentry(header = paste("If estimate_residual_method = 'Servin_Stephens' is used,",
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"please also cite:"),
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bibtype = "Article",
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title = paste("Accounting for uncertainty in residual variances",
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"improves calibration of the 'Sum of Single Effects'",
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"model for small sample sizes"),
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author = c(person("William", "R.P. Denault"),
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person("Peter", "Carbonetto"),
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person("Ruixi", "Li"),
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person("A.D.F.G.", "Consortium"),
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person("Gao", "Wang"),
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person("Matthew", "Stephens")),
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journal = "bioRxiv",
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year = "2025",
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note = "Under review for Nature Methods",
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textVersion =
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paste("Denault, W.R.P., Carbonetto, P., Li, R., Consortium, A.D.F.G.,",
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"Effects' model for small sample sizes. bioRxiv, 2025-05.",
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"Under review for Nature Methods."))
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bibentry(header = paste("If unmappable_effects = 'inf' is used,",
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"please also cite:"),
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bibtype = "Article",
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title = "Improving fine-mapping by modeling infinitesimal effects",
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author = c(person("Rui", "Cui"),
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person("R.A.", "Elzur"),
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person("M.", "Kanai"),
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person(c("et", "al."))),
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journal = "Nature Genetics",
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year = "2024",
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"Improving fine-mapping by modeling infinitesimal effects.",
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"https://doi.org/10.1038/s41588-023-01597-3"))

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