typo (f47c313c) · Commits · github_fork / Presto 20250701

R/glmm.R

+25 −27

Original line number	Diff line number	Diff line
		@@ -303,34 +303,38 @@ presto.presto <- function(


		#' @export
		correct_counts <- function (object, effects_remove, umi_common, verbose = 0)
		{
		correct_counts <- function(object, effects_remove, umi_common, verbose=0) {

		if (missing(umi_common)) {
		umi_common <- mean(log(Matrix::colSums(object$response)))
		# umi_common <- exp(mean(object$meta_data$EXPOSURE))
		}
		effects_remove <- setdiff(effects_remove, "EXPOSURE")

		## read depth should not be removed but equalized
		effects_remove <- setdiff(effects_remove, 'EXPOSURE')
		idx_keep <- object$betanames_df %>%
		tibble::rowid_to_column("idx") %>%
		# subset(!grepl(paste(effects_remove, collapse = "\|"), grpvar)) %>%
		subset(!grpvar %in% effects_remove) %>%
		tibble::rowid_to_column('idx') %>%
		subset(!grepl(paste(effects_remove, collapse = '\|'), grpvar)) %>%
		with(idx)

		if (verbose > 0) {
		message("remove")
		object$betanames_df[-idx_keep, ] %>% with(unique(grpvar)) %>%
		print()
		message("preserve")
		object$betanames_df[idx_keep, ] %>% with(unique(grpvar)) %>%
		print()
		message('remove')
		object$betanames_df[-idx_keep, ] %>% with(unique(grpvar)) %>% print()
		message('preserve')
		object$betanames_df[idx_keep, ] %>% with(unique(grpvar)) %>% print()
		}

		# b1 <- object$beta[which(object$betanames_df$grpvar == 'EXPOSURE'), ]

		design_keep <- object$design[idx_keep, ]
		design_keep["EXPOSURE", ] <- umi_common
		effect_keep <- exp(Matrix::crossprod(design_keep, object$beta[idx_keep,
		]))
		design_keep['EXPOSURE', ] <- umi_common

		effect_keep <- exp(Matrix::crossprod(design_keep, object$beta[idx_keep, ]))
		object$corrected <- Matrix::t(effect_keep + object$epsilon)
		object$corrected <- as(object$corrected, class(object$response)[[1]])
		colnames(object$corrected) <- colnames(object$response)
		row.names(object$corrected) <- row.names(object$response)

		return(object)
		}

		@@ -434,8 +438,7 @@ toptable.presto <- function(
		) %>%
		dplyr::mutate(
		wald = beta / sigma,
		pval = -2 * pnorm(abs(beta / sigma), log.p = TRUE)
		# pval = 2 * (1 - pnorm(abs(beta / sigma)))
		pval = 2 * (1 - pnorm(abs(beta / sigma)))
		) %>%
		dplyr::mutate(fdr = p.adjust(pval, 'BH')) %>%
		subset(pval < max_pval & beta > min_beta & beta < max_beta & fdr < max_fdr)
		@@ -491,12 +494,7 @@ effects.presto <- function(object, effects) {
		suppressMessages({
		object$effect <- dplyr::full_join(beta_tidy, sigma_tidy) %>%
		dplyr::left_join(object$log_mu) %>%

		dplyr::mutate(
		wald = beta/sigma,
		pval = -2 * pnorm(abs(beta / sigma), log.p = TRUE)
		# pval = 2 * (1 - pnorm(abs(beta/sigma)))
		) %>%
		dplyr::mutate(wald = beta/sigma, pval = 2 * (1 - pnorm(abs(beta/sigma)))) %>%
		dplyr::mutate(fdr = p.adjust(pval, "BH"))
		})
		return(object)
		@@ -535,11 +533,11 @@ contrasts.presto <- function(object, contrast_mat, one_tailed=TRUE, check_for_ou
		terms <- colnames(contrast_mat)

		## contrast beta
		beta <- x$beta
		rownames(beta) <- with(x$betanames_df, as.character(glue::glue('{grpvar}.{grp}.{term}')))
		beta <- object$beta
		rownames(beta) <- with(object$betanames_df, as.character(glue::glue('{grpvar}.{grp}.{term}')))
		beta_contrast <- contrast_mat %*% beta[terms, ]

		sigma_contrast <- apply(x$covmat[terms, terms, ], 3, function(.x) {
		sigma_contrast <- apply(object$covmat[terms, terms, ], 3, function(.x) {
		if (check_for_outliers) {
		sigma_diag <- diag(.x)
		sigma_med <- median(sigma_diag)

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