@@ -63,7 +63,7 @@ We have developed [Docker images](https://hub.docker.com/repository/docker/ruana
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@@ -63,7 +63,7 @@ We have developed [Docker images](https://hub.docker.com/repository/docker/ruana
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In this modeling framework, counts denoted as $K_{ij}$ for gene i and sample j are generated using a negative binomial distribution. The negative binomial distribution considers a fitted mean $\mu_{ij}$ and a gene-specific dispersion parameter $\alpha_i$.
In this modeling framework, counts denoted as $`K_{ij}`$ for gene i and sample j are generated using a negative binomial distribution. The negative binomial distribution considers a fitted mean $`\mu_{ij}`$ and a gene-specific dispersion parameter $`\alpha_i`$.
The fitted mean $\mu_{ij}$ is determined by a parameter, qij, which is proportionally related to the sum of all effects specified using `init_variable()` or `add_interaction()`. If basal gene expressions are provided, the $\mu_{ij}$ values are scaled accordingly using the gene-specific basal expression value ($bexpr_i$).
The fitted mean $\mu_{ij}$ is determined by a parameter, qij, which is proportionally related to the sum of all effects specified using `init_variable()` or `add_interaction()`. If basal gene expressions are provided, the $\mu_{ij}$ values are scaled accordingly using the gene-specific basal expression value ($bexpr_i$).
