segregatr

segregatr-package

An implementation of the full-likelihood Bayes factor (FLB) for evaluating segregation evidence in clinical medical genetics. The method was introduced by Thompson et al. (2003) tools:::Rd_expr_doi("10.1086/378100"). This implementation supports custom penetrance values and liability classes, and allows visualisations and robustness analysis as presented in Ratajska et al. (2023) tools:::Rd_expr_doi("10.1002/mgg3.2107"). See also the online app 'shinyseg', <a href="https://chrcarrizosa.shinyapps.io/shinyseg">https://chrcarrizosa.shinyapps.io/shinyseg</a>, which offers interactive segregation analysis with many additional features (Carrizosa et al. (2024) tools:::Rd_expr_doi("10.1093/bioinformatics/btae201")).

internal

An implementation of the full-likelihood Bayes factor (FLB)
for evaluating segregation evidence in clinical medical genetics. The
method was introduced by Thompson et al. (2003) <doi:10.1086/378100>.
This implementation supports custom penetrance values and liability
classes, and allows visualisations and robustness analysis as
presented in Ratajska et al. (2023) <doi:10.1002/mgg3.2107>. See also the
online app 'shinyseg', <https://chrcarrizosa.shinyapps.io/shinyseg>, which
offers interactive segregation analysis with many additional features
(Carrizosa et al. (2024) <doi:10.1093/bioinformatics/btae201>).

Magnus Vigeland

Segregation Analysis for Variant Interpretation

Magnus Dehli Vigeland

Christian Carrizosa

segregatr-package function

Maintainer: Magnus Dehli Vigeland <a href="/link/m.d.vigeland%40medisin.uio.no?package=segregatr&version=0.5.0" data-mini-rdoc="segregatr::m.d.vigeland@medisin.uio.no">m.d.vigeland@medisin.uio.no</a> (<a href="https://orcid.org/0000-0002-9134-4962">ORCID</a>)
Authors:<ul>
<li>Christian Carrizosa (<a href="https://orcid.org/0000-0002-3919-0011">ORCID</a>)</li>
</ul>

Author

An implementation of the full-likelihood Bayes factor (FLB) for evaluating segregation evidence in clinical medical genetics. The method was introduced by Thompson et al. (2003) tools:::Rd_expr_doi("10.1086/378100"). This implementation supports custom penetrance values and liability classes, and allows visualisations and robustness analysis as presented in Ratajska et al. (2023) tools:::Rd_expr_doi("10.1002/mgg3.2107"). See also the online app 'shinyseg', <a href='https://chrcarrizosa.shinyapps.io/shinyseg'>https://chrcarrizosa.shinyapps.io/shinyseg</a>, which offers interactive segregation analysis with many additional features (Carrizosa et al. (2024) tools:::Rd_expr_doi("10.1093/bioinformatics/btae201")).

segregatr: Segregation Analysis for Variant Interpretation — segregatr-package

Maintainer: Magnus Dehli Vigeland <a href='mailto:m.d.vigeland@medisin.uio.no'>m.d.vigeland@medisin.uio.no</a> (<a href='https://orcid.org/0000-0002-9134-4962'>ORCID</a>)
Authors:<ul>
<li>Christian Carrizosa (<a href='https://orcid.org/0000-0002-3919-0011'>ORCID</a>)</li>
</ul>

segregatr-package: segregatr: Segregation Analysis for Variant Interpretation

Description

Arguments

Author

See Also