Loading R/glmm.R +4 −1 Original line number Diff line number Diff line Loading @@ -18,7 +18,7 @@ find_markers_glmm_single_gene <- function(dge_formula, design, y, main_effect, n res$ranef <- lme4::ranef(glmer_res, condVar=TRUE) %>% as.data.frame() %>% dplyr::select(-term) res$fixef <- data.frame(beta = fixef(glmer_res)) %>% res$fixef <- data.frame(beta = lme4::fixef(glmer_res)) %>% tibble::rownames_to_column('effect') ## get betas and SDs Loading Loading @@ -59,6 +59,9 @@ find_markers_glmm <- function( }) names(lres) <- features ## in case some glmer models failed lres <- lres[!is.na(lres)] # Then aggregate the three lists together common_el <- purrr::reduce(map(lres, names), intersect) res <- map(common_el, function(name) { Loading Loading
R/glmm.R +4 −1 Original line number Diff line number Diff line Loading @@ -18,7 +18,7 @@ find_markers_glmm_single_gene <- function(dge_formula, design, y, main_effect, n res$ranef <- lme4::ranef(glmer_res, condVar=TRUE) %>% as.data.frame() %>% dplyr::select(-term) res$fixef <- data.frame(beta = fixef(glmer_res)) %>% res$fixef <- data.frame(beta = lme4::fixef(glmer_res)) %>% tibble::rownames_to_column('effect') ## get betas and SDs Loading Loading @@ -59,6 +59,9 @@ find_markers_glmm <- function( }) names(lres) <- features ## in case some glmer models failed lres <- lres[!is.na(lres)] # Then aggregate the three lists together common_el <- purrr::reduce(map(lres, names), intersect) res <- map(common_el, function(name) { Loading
