Table 1. Summary of SuSiE and SuSiE-RSS, the different data they accept, and the corresponding likelihoods.

In the “likelihood” column, $\tilde{\mathit{z}}≔{\mathit{D}}_z^{1/2}\widehat{\mathit{z}}$ is the vector of adjusted z-scores; see (17). In this summary, we assume X, y are standardized, which is common practice in genetic association studies. Note that when SuSiE-RSS is applied to sufficient statistics and σ² is estimated (second row), the likelihood is identical to the likelihood for SuSiE applied the individual-level data (first row). See https://stephenslab.github.io/susieR/articles/susie_rss.html for an illustration of how these methods are invoked in the R package susieR.

method	data type	data	σ 2	likelihood	algorithm
SuSiE	individual	X, y	fit	ℓ(b, σ2) = ℓ(b, σ2; X, y)	IBSS
SuSiE-RSS	sufficient	$\mathit{R},\widehat{\mathit{z}},N$	fit	$\ell (\mathit{b},{\sigma }^2)={\ell }_{\text{ss}}(\mathit{b},{\sigma }^2;\mathit{R},\tilde{\mathit{z}}/\sqrt{N},1,N)$	IBSS-ss
SuSiE-RSS	summary	$\widehat{\mathit{R}},\widehat{\mathit{z}},N$	1	$\ell \left(\mathit{b}\right)={\ell }_{\text{ss}}(\mathit{b},1;\widehat{\mathit{R}},\tilde{\mathit{z}}/\sqrt{N},1,N)$	IBSS-ss