From 5661eca4e63d9b9ab27724d07543e102ccc61817 Mon Sep 17 00:00:00 2001
From: Johanna Fleischman <71276903+johanna0321@users.noreply.github.com>
Date: Tue, 14 May 2024 10:38:12 -0700
Subject: [PATCH 1/9] Add zero centering and lm drift normalization functions

---
 DESCRIPTION                    |  2 +-
 R/mutate_mzroll_list.R         | 98 +++++++++++++++++++++++++++++++++-
 man/calicomics.Rd              | 17 ++++++
 man/normalize_peaks.Rd         | 18 +++++++
 man/nplug_compounds.Rd         |  2 +-
 man/nplug_mzroll_augmented.Rd  |  2 +-
 man/nplug_mzroll_normalized.Rd |  2 +-
 man/nplug_samples.Rd           |  4 +-
 8 files changed, 138 insertions(+), 7 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 1ae5581..1aef0e8 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -66,5 +66,5 @@ Suggests: dbplyr,
     testthat
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 VignetteBuilder: knitr
diff --git a/R/mutate_mzroll_list.R b/R/mutate_mzroll_list.R
index a066244..6fb90f2 100644
--- a/R/mutate_mzroll_list.R
+++ b/R/mutate_mzroll_list.R
@@ -183,12 +183,16 @@ fill_in_missing_peaks <- function(mzroll_list,
 #'     value
 #'     }
 #'   \item{\code{center batches}: batch centering}
+#'   \item{\code{center}: zero-center each compound}
 #'   \item{\code{reference sample}: compare to reference sample}
 #'   \item{\code{reference condition}: compare each sample to its specified
 #'     reference sample}
 #'   \item{\code{loess}: weighted smoothing of IC over time (adds
 #'     \code{.loess_fit} as a peaks variable in addition to
 #'     \code{norm_peak_varname})}
+#'   \item{\code{lm}: linear regression smoothing of IC over time (adds
+#'     \code{lm_estimate} as feature variable in addition to
+#'     \code{norm_peak_varname})}
 #'   }
 #' @param quant_peak_varname variable in measurements to use for abundance
 #' @param norm_peak_varname variable in measurements to add for normalized
@@ -269,7 +273,9 @@ normalize_peaks <- function(mzroll_list,
     "center batches", "normalize_peaks_batch_center",
     "reference sample", "normalize_peaks_reference_sample",
     "reference condition", "normalize_peaks_reference_condition",
-    "loess", "normalize_peaks_loess"
+    "loess", "normalize_peaks_loess",
+    "lm", "normalize_peaks_lm",
+    "center","normalize_peaks_center"
   )
   
   checkmate::assertChoice(
@@ -901,4 +907,94 @@ normalization_refloor <- function(normalized_peaks,
   }
   
   return(normalized_peaks)
+}
+
+#' @inheritParams normalize_peaks_batch_center
+#' @param time_col_varname variable in samples table to use for linear 
+#' correction
+#'
+#' @rdname normalize_peaks
+normalize_peaks_lm <- function (mzroll_list,
+                                quant_peak_varname,
+                                norm_peak_varname, 
+                                time_col_varname) 
+{
+  stopifnot(time_col_varname %in% colnames(mzroll_list$samples))
+  
+  time_col_varname_add <- mzroll_list$samples %>%
+    dplyr::select(c("sampleId", time_col_varname))
+  
+  lm_fit <- mzroll_list$measurements %>% 
+    dplyr::left_join(., time_col_varname_add, by = "sampleId") %>%
+    tidyr::nest(groupData = -groupId) %>% 
+    dplyr::mutate(lm_fits = purrr::map(groupData,
+                                       fit_lm, 
+                                       quant_peak_varname = quant_peak_varname, 
+                                       norm_peak_varname = norm_peak_varname,
+                                       time_col_varname = time_col_varname)) %>% 
+    dplyr::select(-groupData) %>% 
+    tidyr::unnest(lm_fits)
+  
+  lm_fit_measurements <- lm_fit %>% 
+    dplyr::select(!!!rlang::syms(c(colnames(mzroll_list$measurements), norm_peak_varname)))
+  
+  lm_fit_features <- lm_fit %>%
+    dplyr::select(groupId, lm_estimate) %>%
+    unique() %>%
+    dplyr::left_join(mzroll_list$features, ., by = "groupId")
+  
+  mzroll_list <- romic::update_tomic(mzroll_list, lm_fit_measurements)
+  mzroll_list <- romic::update_tomic(mzroll_list, lm_fit_features)
+  
+  return(mzroll_list)
+  
+}
+
+fit_lm <- function (groupData, 
+                    time_col_varname,
+                    quant_peak_varname, 
+                    norm_peak_varname,
+                    order = 1) 
+{
+  
+  lm_data <- groupData %>%
+    dplyr::mutate(val_var = !!rlang::sym(quant_peak_varname),
+                  dri_var = !!rlang::sym(time_col_varname)) 
+  
+  lm_predict <- lm_data %>%
+    tidyr::drop_na(val_var)
+  
+  # Run model
+  lm_model <- stats::lm(val_var ~ poly(dri_var, degree = order), data = lm_predict)
+  
+  # Compute corrected values
+  lm_apply <- lm_data %>%
+    dplyr::mutate(median_value = median(.data$val_var, na.rm = T)) %>%
+    dplyr::mutate(`:=`(!!rlang::sym(norm_peak_varname), 
+                       .data$val_var - .env$predict(lm_model, newdata = lm_data) + .data$median_value)) %>%
+                    dplyr::mutate(lm_estimate = summary(.env$lm_model)$coefficient[2,1]) %>%
+                    dplyr::select(-c(val_var, dri_var, median_value))
+                  
+  return(lm_apply)
+  
+}
+
+
+#' @inheritParams normalize_peaks_center
+#'
+#' @rdname normalize_peaks
+normalize_peaks_center <- function(mzroll_list,
+                                   quant_peak_varname,
+                                   norm_peak_varname) 
+{
+  
+  updated_measurements <- mzroll_list$measurements %>%
+    dplyr::group_by(groupId) %>%
+    dplyr::mutate(!!rlang::sym(norm_peak_varname) :=
+        scale(!!rlang::sym(quant_peak_varname), scale = F, center = T))
+  
+  mzroll_list <- romic::update_tomic(mzroll_list, updated_measurements)
+  
+  return(mzroll_list)
+  
 }
\ No newline at end of file
diff --git a/man/calicomics.Rd b/man/calicomics.Rd
index 229a27a..8b98604 100644
--- a/man/calicomics.Rd
+++ b/man/calicomics.Rd
@@ -2,6 +2,8 @@
 % Please edit documentation in R/claman.R
 \docType{package}
 \name{calicomics}
+\alias{claman}
+\alias{claman-package}
 \alias{calicomics}
 \title{\code{claman} package}
 \description{
@@ -11,3 +13,18 @@ can then be modified through normalization, signal flooring, and filtering.
 Differential abundance analysis of metabolites can then be performed along
 with a variety of visualizations.
 }
+\author{
+\strong{Maintainer}: Sean Hackett \email{sean@calicolabs.com} (\href{https://orcid.org/0000-0002-9553-4341}{ORCID})
+
+Authors:
+\itemize{
+  \item Phil Seitzer \email{phillipseitzer@calicolabs.com}
+  \item Alireza Delfarah \email{delfarah@calicolabs.com}
+}
+
+Other contributors:
+\itemize{
+  \item Calico Life Sciences LLC [copyright holder, funder]
+}
+
+}
diff --git a/man/normalize_peaks.Rd b/man/normalize_peaks.Rd
index d5fb822..6d13c1b 100644
--- a/man/normalize_peaks.Rd
+++ b/man/normalize_peaks.Rd
@@ -8,6 +8,8 @@
 \alias{normalize_peaks_reference_sample}
 \alias{normalize_peaks_reference_condition}
 \alias{normalize_peaks_loess}
+\alias{normalize_peaks_lm}
+\alias{normalize_peaks_center}
 \title{Normalize Peaks}
 \usage{
 normalize_peaks(
@@ -68,6 +70,15 @@ normalize_peaks_loess(
   weights_tribble = NULL,
   log2_floor_value = 12
 )
+
+normalize_peaks_lm(
+  mzroll_list,
+  quant_peak_varname,
+  norm_peak_varname,
+  time_col_varname
+)
+
+normalize_peaks_center(mzroll_list, quant_peak_varname, norm_peak_varname)
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
@@ -87,12 +98,16 @@ normalize_peaks_loess(
     value
     }
   \item{\code{center batches}: batch centering}
+  \item{\code{center}: zero-center each compound}
   \item{\code{reference sample}: compare to reference sample}
   \item{\code{reference condition}: compare each sample to its specified
     reference sample}
   \item{\code{loess}: weighted smoothing of IC over time (adds
     \code{.loess_fit} as a peaks variable in addition to
     \code{norm_peak_varname})}
+  \item{\code{lm}: linear regression smoothing of IC over time (adds
+    \code{lm_estimate} as feature variable in addition to
+    \code{norm_peak_varname})}
   }}
 
 \item{quant_peak_varname}{variable in measurements to use for abundance}
@@ -121,6 +136,9 @@ reference samples}
 
 \item{weights_tribble}{a table containing weights and sample variables to
 match them to.}
+
+\item{time_col_varname}{variable in samples table to use for linear 
+correction}
 }
 \value{
 a \code{mzroll_list} as generated by \code{\link{process_mzroll}}
diff --git a/man/nplug_compounds.Rd b/man/nplug_compounds.Rd
index b1e7434..aad9a39 100644
--- a/man/nplug_compounds.Rd
+++ b/man/nplug_compounds.Rd
@@ -21,9 +21,9 @@ A table of meta-data for all NPLUG features with variables:
 }
 \seealso{
 Other nplug: 
+\code{\link{nplug_mzroll}()},
 \code{\link{nplug_mzroll_augmented}},
 \code{\link{nplug_mzroll_normalized}},
-\code{\link{nplug_mzroll}()},
 \code{\link{nplug_samples}}
 }
 \concept{nplug}
diff --git a/man/nplug_mzroll_augmented.Rd b/man/nplug_mzroll_augmented.Rd
index ab63202..e8b9f64 100644
--- a/man/nplug_mzroll_augmented.Rd
+++ b/man/nplug_mzroll_augmented.Rd
@@ -17,8 +17,8 @@ nplug_mzroll_augmented
 \seealso{
 Other nplug: 
 \code{\link{nplug_compounds}},
-\code{\link{nplug_mzroll_normalized}},
 \code{\link{nplug_mzroll}()},
+\code{\link{nplug_mzroll_normalized}},
 \code{\link{nplug_samples}}
 }
 \concept{nplug}
diff --git a/man/nplug_mzroll_normalized.Rd b/man/nplug_mzroll_normalized.Rd
index a2e32f5..574bea8 100644
--- a/man/nplug_mzroll_normalized.Rd
+++ b/man/nplug_mzroll_normalized.Rd
@@ -20,8 +20,8 @@ nplug_mzroll_normalized
 \seealso{
 Other nplug: 
 \code{\link{nplug_compounds}},
-\code{\link{nplug_mzroll_augmented}},
 \code{\link{nplug_mzroll}()},
+\code{\link{nplug_mzroll_augmented}},
 \code{\link{nplug_samples}}
 }
 \concept{nplug}
diff --git a/man/nplug_samples.Rd b/man/nplug_samples.Rd
index 620afc6..494ec45 100644
--- a/man/nplug_samples.Rd
+++ b/man/nplug_samples.Rd
@@ -39,9 +39,9 @@ A table of meta-data for all NPLUG samples with variables:
 \seealso{
 Other nplug: 
 \code{\link{nplug_compounds}},
+\code{\link{nplug_mzroll}()},
 \code{\link{nplug_mzroll_augmented}},
-\code{\link{nplug_mzroll_normalized}},
-\code{\link{nplug_mzroll}()}
+\code{\link{nplug_mzroll_normalized}}
 }
 \concept{nplug}
 \keyword{datasets}

From 739137a1c99377c840181d4488070a398446d424 Mon Sep 17 00:00:00 2001
From: Johanna Fleischman <71276903+johanna0321@users.noreply.github.com>
Date: Thu, 16 May 2024 14:01:31 -0700
Subject: [PATCH 2/9] Modify median polish function

---
 R/mutate_mzroll_list.R | 51 +++++++++++++++++++++++++++++++++---------
 man/normalize_peaks.Rd |  4 ++++
 2 files changed, 44 insertions(+), 11 deletions(-)

diff --git a/R/mutate_mzroll_list.R b/R/mutate_mzroll_list.R
index 6fb90f2..adbdd1d 100644
--- a/R/mutate_mzroll_list.R
+++ b/R/mutate_mzroll_list.R
@@ -325,12 +325,16 @@ normalize_peaks <- function(mzroll_list,
 #'
 #' @inheritParams normalize_peaks
 #' @inheritParams floor_peaks
+#' @param filter_values groupIds on which to calculate the median polish scaling
+#' factor
 #'
 #' @rdname normalize_peaks
 normalize_peaks_median_polish <- function(mzroll_list,
                                           quant_peak_varname,
                                           norm_peak_varname,
+                                          filter_values = NULL,
                                           log2_floor_value = NA) {
+  
   stopifnot(length(log2_floor_value) == 1)
   if (!is.na(log2_floor_value)) {
     stopifnot(class(log2_floor_value) == "numeric")
@@ -351,7 +355,27 @@ normalize_peaks_median_polish <- function(mzroll_list,
     )
   }
   
-  sample_scaling_factors <- normalization_peaks %>%
+  if (!is.null(filter_values)){
+    if (!any(filter_values %in% unique(mzroll_list$features$groupId))){
+      
+      # If groupId filter values not in design,
+      # perform median polish on all compounds
+      warning("groupId filter values not found in design; performing median polish on all groupIds")
+      sample_scaling_factors <- normalization_peaks
+    } else {
+      
+      # If they are present, filter on these compounds
+      sample_scaling_factors <- normalization_peaks %>%
+        dplyr::filter(groupId %in% filter_values)
+    }
+  } else {
+    
+    # If not groupId filter values provided, 
+    # calculate scaling factor on all compounds
+    sample_scaling_factors <- normalization_peaks
+  }
+  
+  sample_scaling_factors <- sample_scaling_factors %>%
     dplyr::group_by(groupId) %>%
     dplyr::mutate(
       median_abund = stats::median(!!rlang::sym(quant_peak_varname))
@@ -361,7 +385,7 @@ normalize_peaks_median_polish <- function(mzroll_list,
       diff_to_median = !!rlang::sym(quant_peak_varname) - median_abund
     ) %>%
     dplyr::group_by(sampleId) %>%
-    dplyr::summarize(scaling_factor = stats::median(diff_to_median))
+    dplyr::summarize(median_polish_scaling_factor = stats::median(diff_to_median))
   
   missing_sample_scaling_factors <- mzroll_list$samples %>%
     dplyr::anti_join(sample_scaling_factors, by = "sampleId")
@@ -382,7 +406,7 @@ normalize_peaks_median_polish <- function(mzroll_list,
       dplyr::left_join(sample_scaling_factors, by = "sampleId") %>%
       dplyr::mutate(
         !!rlang::sym(norm_peak_varname) :=
-          !!rlang::sym(quant_peak_varname) - scaling_factor
+          !!rlang::sym(quant_peak_varname) - median_polish_scaling_factor
       ) %>%
       # measurements starting at limit of detection are reset to
       #   log2_floor_value
@@ -393,7 +417,7 @@ normalize_peaks_median_polish <- function(mzroll_list,
           ) %>%
           dplyr::mutate(!!rlang::sym(norm_peak_varname) := log2_floor_value)
       ) %>%
-      dplyr::select(-scaling_factor) %>%
+      dplyr::select(-median_polish_scaling_factor) %>%
       # measurements pushed below limit of detection are reset to
       #   log2_floor_value
       dplyr::mutate(
@@ -405,13 +429,18 @@ normalize_peaks_median_polish <- function(mzroll_list,
       dplyr::left_join(sample_scaling_factors, by = "sampleId") %>%
       dplyr::mutate(
         !!rlang::sym(norm_peak_varname) :=
-          !!rlang::sym(quant_peak_varname) - scaling_factor
+          !!rlang::sym(quant_peak_varname) - median_polish_scaling_factor
       ) %>%
-      dplyr::select(-scaling_factor)
+      dplyr::select(-median_polish_scaling_factor)
   }
   
   mzroll_list <- romic::update_tomic(mzroll_list, updated_measurements)
   
+  updated_samples <- mzroll_list$samples %>%
+    dplyr::left_join(., sample_scaling_factors, by = "sampleId")
+  
+  mzroll_list <- romic::update_tomic(mzroll_list, updated_samples)
+  
   return(mzroll_list)
 }
 
@@ -980,12 +1009,12 @@ fit_lm <- function (groupData,
 }
 
 
-#' @inheritParams normalize_peaks_center
+#' @inheritParams normalize_peaks_batch_center
 #'
 #' @rdname normalize_peaks
-normalize_peaks_center <- function(mzroll_list,
-                                   quant_peak_varname,
-                                   norm_peak_varname) 
+normalize_peaks_center <- function (mzroll_list,
+                                    quant_peak_varname,
+                                    norm_peak_varname) 
 {
   
   updated_measurements <- mzroll_list$measurements %>%
@@ -997,4 +1026,4 @@ normalize_peaks_center <- function(mzroll_list,
   
   return(mzroll_list)
   
-}
\ No newline at end of file
+}
diff --git a/man/normalize_peaks.Rd b/man/normalize_peaks.Rd
index 6d13c1b..614039b 100644
--- a/man/normalize_peaks.Rd
+++ b/man/normalize_peaks.Rd
@@ -24,6 +24,7 @@ normalize_peaks_median_polish(
   mzroll_list,
   quant_peak_varname,
   norm_peak_varname,
+  filter_values = NULL,
   log2_floor_value = NA
 )
 
@@ -117,6 +118,9 @@ abundance}
 
 \item{...}{additional arguments to pass to normalization methods}
 
+\item{filter_values}{groupIds on which to calculate the median polish scaling
+factor}
+
 \item{log2_floor_value}{minimum value to set for low abundance or
 missing peaks}
 

From 6186c8a0a261c2ed81dc336e7c70ff7bb0faebec Mon Sep 17 00:00:00 2001
From: Johanna Fleischman <71276903+johanna0321@users.noreply.github.com>
Date: Thu, 16 May 2024 14:05:17 -0700
Subject: [PATCH 3/9] Add romic parameter to test_mzroll_list

---
 R/utils.R | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/R/utils.R b/R/utils.R
index c3f02b3..c6aba85 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -2,6 +2,8 @@
 #'
 #' @param mzroll_list output of \link{process_mzroll} or
 #'   \link{process_mzroll_multi}
+#' @param fast_check if `TRUE` then skip some checks which are slow and that are 
+#' generally only needed when a `tomic` object is first created
 #'
 #' \itemize{
 #'   \item{features: one row per unique analyte (defined by a
@@ -10,8 +12,6 @@
 #'   \item{measurements: one row per peak (samples x peakgroups)}
 #'   }
 #'
-#' @inheritParams romic:::check_triple_omic
-#'
 test_mzroll_list <- function(mzroll_list, fast_check = TRUE) {
   checkmate::assertClass(mzroll_list, "tomic")
   checkmate::assertClass(mzroll_list, "mzroll")

From 5ef645ee235c5183df9844bb33855d3bfaf5d337 Mon Sep 17 00:00:00 2001
From: Johanna Fleischman <71276903+johanna0321@users.noreply.github.com>
Date: Thu, 16 May 2024 14:10:33 -0700
Subject: [PATCH 4/9] Update documentation and comments

---
 R/mutate_mzroll_list.R          | 5 +++++
 man/collapse_injections.Rd      | 9 +--------
 man/collapse_metabolites.Rd     | 9 +--------
 man/diffex_mzroll.Rd            | 9 +--------
 man/filter_groupIds.Rd          | 9 +--------
 man/find_pathway_enrichments.Rd | 9 +--------
 man/floor_peaks.Rd              | 9 +--------
 man/merge_compounds_tbl.Rd      | 9 +--------
 man/merge_samples_tbl.Rd        | 9 +--------
 man/normalize_peaks.Rd          | 9 +--------
 man/plot_barplot.Rd             | 9 +--------
 man/plot_compare_injection.Rd   | 9 +--------
 man/test_mzroll_list.Rd         | 5 ++++-
 13 files changed, 20 insertions(+), 89 deletions(-)

diff --git a/R/mutate_mzroll_list.R b/R/mutate_mzroll_list.R
index adbdd1d..4a57223 100644
--- a/R/mutate_mzroll_list.R
+++ b/R/mutate_mzroll_list.R
@@ -999,6 +999,11 @@ fit_lm <- function (groupData,
   # Compute corrected values
   lm_apply <- lm_data %>%
     dplyr::mutate(median_value = median(.data$val_var, na.rm = T)) %>%
+    
+    # Assign new normalized variable norm_peak_varname:
+    # Predict values from linear fit are subtracted from quant_peak_varname,
+    # which centers the data around zero
+    # Median value from quant_peak_varname is added back to maintain abundance value
     dplyr::mutate(`:=`(!!rlang::sym(norm_peak_varname), 
                        .data$val_var - .env$predict(lm_model, newdata = lm_data) + .data$median_value)) %>%
                     dplyr::mutate(lm_estimate = summary(.env$lm_model)$coefficient[2,1]) %>%
diff --git a/man/collapse_injections.Rd b/man/collapse_injections.Rd
index 1c48ccd..ea245c7 100644
--- a/man/collapse_injections.Rd
+++ b/man/collapse_injections.Rd
@@ -13,14 +13,7 @@ collapse_injections(
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
-  \link{process_mzroll_multi}
-
-\itemize{
-  \item{features: one row per unique analyte (defined by a
-    unique groupId)},
-  \item{samples: one row per unique sample (defined by a unique sampleId)},
-  \item{measurements: one row per peak (samples x peakgroups)}
-  }}
+\link{process_mzroll_multi}}
 
 \item{grouping_vars}{character vector of sample variables to use for
 grouping}
diff --git a/man/collapse_metabolites.Rd b/man/collapse_metabolites.Rd
index 3244c44..c068fee 100644
--- a/man/collapse_metabolites.Rd
+++ b/man/collapse_metabolites.Rd
@@ -12,14 +12,7 @@ collapse_metabolites(
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
-  \link{process_mzroll_multi}
-
-\itemize{
-  \item{features: one row per unique analyte (defined by a
-    unique groupId)},
-  \item{samples: one row per unique sample (defined by a unique sampleId)},
-  \item{measurements: one row per peak (samples x peakgroups)}
-  }}
+\link{process_mzroll_multi}}
 
 \item{preserve_distinct_methods}{if TRUE then collapse metabolites
 for each method separately. If FALSE, collapse over methods.}
diff --git a/man/diffex_mzroll.Rd b/man/diffex_mzroll.Rd
index 89319c2..3dd9da2 100644
--- a/man/diffex_mzroll.Rd
+++ b/man/diffex_mzroll.Rd
@@ -15,14 +15,7 @@ diffex_mzroll(
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
-  \link{process_mzroll_multi}
-
-\itemize{
-  \item{features: one row per unique analyte (defined by a
-    unique groupId)},
-  \item{samples: one row per unique sample (defined by a unique sampleId)},
-  \item{measurements: one row per peak (samples x peakgroups)}
-  }}
+\link{process_mzroll_multi}}
 
 \item{value_var}{measurement variable}
 
diff --git a/man/filter_groupIds.Rd b/man/filter_groupIds.Rd
index 2f17237..8d5810b 100644
--- a/man/filter_groupIds.Rd
+++ b/man/filter_groupIds.Rd
@@ -8,14 +8,7 @@ filter_groupIds(mzroll_list, groupIds, invert = FALSE)
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
-  \link{process_mzroll_multi}
-
-\itemize{
-  \item{features: one row per unique analyte (defined by a
-    unique groupId)},
-  \item{samples: one row per unique sample (defined by a unique sampleId)},
-  \item{measurements: one row per peak (samples x peakgroups)}
-  }}
+\link{process_mzroll_multi}}
 
 \item{groupIds}{groupIds to retain}
 
diff --git a/man/find_pathway_enrichments.Rd b/man/find_pathway_enrichments.Rd
index c24dd1c..fc7876d 100644
--- a/man/find_pathway_enrichments.Rd
+++ b/man/find_pathway_enrichments.Rd
@@ -17,14 +17,7 @@ find_pathway_enrichments(
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
-  \link{process_mzroll_multi}
-
-\itemize{
-  \item{features: one row per unique analyte (defined by a
-    unique groupId)},
-  \item{samples: one row per unique sample (defined by a unique sampleId)},
-  \item{measurements: one row per peak (samples x peakgroups)}
-  }}
+\link{process_mzroll_multi}}
 
 \item{regression_significance}{returned by \code{\link{diffex_mzroll}};
 a tibble of tests performed.}
diff --git a/man/floor_peaks.Rd b/man/floor_peaks.Rd
index 04babcf..ba1a2a4 100644
--- a/man/floor_peaks.Rd
+++ b/man/floor_peaks.Rd
@@ -8,14 +8,7 @@ floor_peaks(mzroll_list, log2_floor_value = 12, floor_var = "log2_abundance")
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
-  \link{process_mzroll_multi}
-
-\itemize{
-  \item{features: one row per unique analyte (defined by a
-    unique groupId)},
-  \item{samples: one row per unique sample (defined by a unique sampleId)},
-  \item{measurements: one row per peak (samples x peakgroups)}
-  }}
+\link{process_mzroll_multi}}
 
 \item{log2_floor_value}{minimum value to set for low abundance or
 missing peaks}
diff --git a/man/merge_compounds_tbl.Rd b/man/merge_compounds_tbl.Rd
index 1586e58..b6f3c97 100644
--- a/man/merge_compounds_tbl.Rd
+++ b/man/merge_compounds_tbl.Rd
@@ -8,14 +8,7 @@ merge_compounds_tbl(mzroll_list, compounds_tbl, by = "compoundName")
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
-  \link{process_mzroll_multi}
-
-\itemize{
-  \item{features: one row per unique analyte (defined by a
-    unique groupId)},
-  \item{samples: one row per unique sample (defined by a unique sampleId)},
-  \item{measurements: one row per peak (samples x peakgroups)}
-  }}
+\link{process_mzroll_multi}}
 
 \item{compounds_tbl}{Table of compound metadata}
 
diff --git a/man/merge_samples_tbl.Rd b/man/merge_samples_tbl.Rd
index fccc699..0338a30 100644
--- a/man/merge_samples_tbl.Rd
+++ b/man/merge_samples_tbl.Rd
@@ -8,14 +8,7 @@ merge_samples_tbl(mzroll_list, samples_tbl, id_strings, exact = FALSE)
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
-  \link{process_mzroll_multi}
-
-\itemize{
-  \item{features: one row per unique analyte (defined by a
-    unique groupId)},
-  \item{samples: one row per unique sample (defined by a unique sampleId)},
-  \item{measurements: one row per peak (samples x peakgroups)}
-  }}
+\link{process_mzroll_multi}}
 
 \item{samples_tbl}{Table of sample metadata}
 
diff --git a/man/normalize_peaks.Rd b/man/normalize_peaks.Rd
index 614039b..1c569bf 100644
--- a/man/normalize_peaks.Rd
+++ b/man/normalize_peaks.Rd
@@ -83,14 +83,7 @@ normalize_peaks_center(mzroll_list, quant_peak_varname, norm_peak_varname)
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
-  \link{process_mzroll_multi}
-
-\itemize{
-  \item{features: one row per unique analyte (defined by a
-    unique groupId)},
-  \item{samples: one row per unique sample (defined by a unique sampleId)},
-  \item{measurements: one row per peak (samples x peakgroups)}
-  }}
+\link{process_mzroll_multi}}
 
 \item{normalization_method}{Normalization method to apply
 \itemize{
diff --git a/man/plot_barplot.Rd b/man/plot_barplot.Rd
index cd96a86..2c1c30c 100644
--- a/man/plot_barplot.Rd
+++ b/man/plot_barplot.Rd
@@ -8,14 +8,7 @@ plot_barplot(mzroll_list, groupIds, grouping_vars, value_var, fill_var = NULL)
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
-  \link{process_mzroll_multi}
-
-\itemize{
-  \item{features: one row per unique analyte (defined by a
-    unique groupId)},
-  \item{samples: one row per unique sample (defined by a unique sampleId)},
-  \item{measurements: one row per peak (samples x peakgroups)}
-  }}
+\link{process_mzroll_multi}}
 
 \item{groupIds}{groupIds for compounds to plot}
 
diff --git a/man/plot_compare_injection.Rd b/man/plot_compare_injection.Rd
index a09aafe..4b78fa8 100644
--- a/man/plot_compare_injection.Rd
+++ b/man/plot_compare_injection.Rd
@@ -12,14 +12,7 @@ plot_compare_injection(
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
-  \link{process_mzroll_multi}
-
-\itemize{
-  \item{features: one row per unique analyte (defined by a
-    unique groupId)},
-  \item{samples: one row per unique sample (defined by a unique sampleId)},
-  \item{measurements: one row per peak (samples x peakgroups)}
-  }}
+\link{process_mzroll_multi}}
 
 \item{grouping_vars}{character vector of sample variables to use for
 grouping}
diff --git a/man/test_mzroll_list.Rd b/man/test_mzroll_list.Rd
index d630a5c..246fba6 100644
--- a/man/test_mzroll_list.Rd
+++ b/man/test_mzroll_list.Rd
@@ -8,7 +8,10 @@ test_mzroll_list(mzroll_list, fast_check = TRUE)
 }
 \arguments{
 \item{mzroll_list}{output of \link{process_mzroll} or
-  \link{process_mzroll_multi}
+\link{process_mzroll_multi}}
+
+\item{fast_check}{if `TRUE` then skip some checks which are slow and that are 
+generally only needed when a `tomic` object is first created
 
 \itemize{
   \item{features: one row per unique analyte (defined by a

From 859e9a760b3c455d3436517e6f324ce805887ba3 Mon Sep 17 00:00:00 2001
From: Johanna Fleischman <71276903+johanna0321@users.noreply.github.com>
Date: Thu, 16 May 2024 14:44:03 -0700
Subject: [PATCH 5/9] Update function documentation

---
 R/mutate_mzroll_list.R       | 16 ++++++++--------
 man/fill_in_missing_peaks.Rd |  8 ++++----
 man/impute_missing_peaks.Rd  |  8 ++++----
 3 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/R/mutate_mzroll_list.R b/R/mutate_mzroll_list.R
index 4a57223..b4224ca 100644
--- a/R/mutate_mzroll_list.R
+++ b/R/mutate_mzroll_list.R
@@ -58,10 +58,10 @@ floor_peaks <- function(mzroll_list,
 
 #' Impute missing peaks with provided feature-level imputation values
 #'
-#'@param mzroll_list: data in triple omic structure
-#'@param lod_values: a tibble that maps groupId to log2 feature-level imputation values
-#'@param quant_var: column to use for peak values
-#'@param imputation_sd: standard deviation of Gaussian distribution to use for missing peak imputation
+#'@param mzroll_list data in triple omic structure
+#'@param lod_values a tibble that maps groupId to log2 feature-level imputation values
+#'@param quant_var column to use for peak values
+#'@param imputation_sd standard deviation of Gaussian distribution to use for missing peak imputation
 #'
 #'@return triple omic data with imputed missing peaks
 #'
@@ -138,10 +138,10 @@ impute_missing_peaks <- function(mzroll_list,
 #'If \code{fill_values} is a data frame, this function calls \code{impute_missing_peaks()}.
 #'If it is a numeric vector, 'this function calls \code{floor_peaks()}. Other types are not currently supported
 #'
-#'@param mzroll_list: data in triple omic structure
-#'@param fill_values: either a numeric constant or a tibble that maps groupId to log2 feature-level imputation values
-#'@param quant_var: column to use for peak values
-#'@param imputation_sd: standard deviation of Gaussian distribution to use for missing peak imputation
+#'@param mzroll_list data in triple omic structure
+#'@param fill_values either a numeric constant or a tibble that maps groupId to log2 feature-level imputation values
+#'@param quant_var column to use for peak values
+#'@param imputation_sd standard deviation of Gaussian distribution to use for missing peak imputation
 #'
 #'@return triple omic data with imputed missing peaks
 #'
diff --git a/man/fill_in_missing_peaks.Rd b/man/fill_in_missing_peaks.Rd
index 8c1e1ce..ee4dae7 100644
--- a/man/fill_in_missing_peaks.Rd
+++ b/man/fill_in_missing_peaks.Rd
@@ -12,13 +12,13 @@ fill_in_missing_peaks(
 )
 }
 \arguments{
-\item{mzroll_list:}{data in triple omic structure}
+\item{mzroll_list}{data in triple omic structure}
 
-\item{fill_values:}{either a numeric constant or a tibble that maps groupId to log2 feature-level imputation values}
+\item{fill_values}{either a numeric constant or a tibble that maps groupId to log2 feature-level imputation values}
 
-\item{quant_var:}{column to use for peak values}
+\item{quant_var}{column to use for peak values}
 
-\item{imputation_sd:}{standard deviation of Gaussian distribution to use for missing peak imputation}
+\item{imputation_sd}{standard deviation of Gaussian distribution to use for missing peak imputation}
 }
 \value{
 triple omic data with imputed missing peaks
diff --git a/man/impute_missing_peaks.Rd b/man/impute_missing_peaks.Rd
index a735c6b..74d6cac 100644
--- a/man/impute_missing_peaks.Rd
+++ b/man/impute_missing_peaks.Rd
@@ -12,13 +12,13 @@ impute_missing_peaks(
 )
 }
 \arguments{
-\item{mzroll_list:}{data in triple omic structure}
+\item{mzroll_list}{data in triple omic structure}
 
-\item{lod_values:}{a tibble that maps groupId to log2 feature-level imputation values}
+\item{lod_values}{a tibble that maps groupId to log2 feature-level imputation values}
 
-\item{quant_var:}{column to use for peak values}
+\item{quant_var}{column to use for peak values}
 
-\item{imputation_sd:}{standard deviation of Gaussian distribution to use for missing peak imputation}
+\item{imputation_sd}{standard deviation of Gaussian distribution to use for missing peak imputation}
 }
 \value{
 triple omic data with imputed missing peaks

From 21ccf0381c7449fb0890533aedd2ca42cda11ef6 Mon Sep 17 00:00:00 2001
From: Johanna Fleischman <71276903+johanna0321@users.noreply.github.com>
Date: Thu, 16 May 2024 16:02:07 -0700
Subject: [PATCH 6/9] Update median polish documentation

---
 R/mutate_mzroll_list.R | 70 +++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 69 insertions(+), 1 deletion(-)

diff --git a/R/mutate_mzroll_list.R b/R/mutate_mzroll_list.R
index b4224ca..c2236ae 100644
--- a/R/mutate_mzroll_list.R
+++ b/R/mutate_mzroll_list.R
@@ -178,7 +178,9 @@ fill_in_missing_peaks <- function(mzroll_list,
 #' @inheritParams test_mzroll_list
 #' @param normalization_method Normalization method to apply
 #' \itemize{
-#'   \item{\code{median polish}: column normalization based on average signal}
+#'   \item{\code{median polish}: column normalization based on average signal
+#'   (adds \code{median_polish_scaling_factor} as feature variable in addition to
+#'     \code{norm_peak_varname})}
 #'   \item{\code{loading value}: column normalization using a sample-level
 #'     value
 #'     }
@@ -442,6 +444,72 @@ normalize_peaks_median_polish <- function(mzroll_list,
   mzroll_list <- romic::update_tomic(mzroll_list, updated_samples)
   
   return(mzroll_list)
+  
+}
+
+
+#' Predict Dilutions from Median Polish Scaling Factor
+#' 
+#' Using `median_polish_scaling_factor` output from `normalize_peaks_median_polish`,
+#' predict sample-wise dilutions
+#' 
+#' @details This function performs an inverse-normalization on the scaling factors,
+#' and scales the samples based on the observed maximum scaling factor. Assumes that
+#' median polish is perform on log2 transformed data
+#' 
+#' @param mzroll_list data in triple omic structure
+#' @param scaling_factor scaling factor, defaults to `median_polish_scaling_factor`
+#' and must be a `samples` column in `mzroll_list`
+#' @param norm_scale_varname variable in samples to add for dilution predictions
+#' @param group_var optional grouping variable on which to calculate maximum dilution
+#' 
+#' @return a \code{mzroll_list} with \code{norm_scale_varname} variable added to 
+#' samples
+#'   
+#' @export
+median_polish_predict_dilutions <- function (mzroll_list,
+                                             scaling_factor = "median_polish_scaling_factor",
+                                             norm_scale_varname = "median_polish_predicted_dilutions",
+                                             group_vars = NULL) {
+  test_mzroll_list(mzroll_list)
+  
+  checkmate::assertString(scaling_factor)
+  if (!(scaling_factor %in% colnames(mzroll_list$samples))) {
+    stop(
+      "\"scaling_factor\":",
+      scaling_factor,
+      ", not present in samples table"
+    )
+  }
+  checkmate::assertString(norm_scale_varname)
+  
+  updated_samples <- mzroll_list$samples %>%
+    dplyr::mutate(temp_scaling_factor = !!rlang::sym(scaling_factor)) %>%
+    dplyr::mutate(inverse_log_scaling_factor = 2^temp_scaling_factor) 
+  
+  if(!is.null(group_var) && any(group_vars %in% colnames(mzroll_list$samples))) {
+    
+    updated_samples <- updated_samples %>%
+      dplyr::group_by(group_vars) %>%
+      dplyr::mutate(m = max(inverse_log_scaling_factor)) %>%
+      dplyr::ungroup()
+    
+  } else {
+    
+    updated_samples <- updated_samples %>%
+      dplyr::mutate(m = max(inverse_log_scaling_factor))
+    
+  }
+  
+  updated_samples <- updated_samples %>%
+    dplyr::rowwise() %>%
+    dplyr::mutate(`:=`(!!rlang::sym(norm_scale_varname), 
+                       inverse_log_scaling_factor/m)) %>%
+    dplyr::select(-temp_scaling_factor, -inverse_log_scaling_factor, -m)
+                    
+  mzroll_list <- romic::update_tomic(mzroll_list, updated_samples)
+  return(mzroll_list)
+
 }
 
 #' Normalize Peaks - Loading Value

From 3c805e532947355d783010b2ff5b05f92f6228a5 Mon Sep 17 00:00:00 2001
From: Johanna Fleischman <71276903+johanna0321@users.noreply.github.com>
Date: Fri, 17 May 2024 12:35:20 -0700
Subject: [PATCH 7/9] Update documentation and functions

---
 NAMESPACE                              |  1 +
 R/mutate_mzroll_list.R                 | 25 +++++++++--------
 man/median_polish_predict_dilutions.Rd | 37 ++++++++++++++++++++++++++
 man/normalize_peaks.Rd                 |  4 ++-
 4 files changed, 55 insertions(+), 12 deletions(-)
 create mode 100644 man/median_polish_predict_dilutions.Rd

diff --git a/NAMESPACE b/NAMESPACE
index 7babc77..2b64fb5 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -10,6 +10,7 @@ export(floor_peaks)
 export(impute_missing_peaks)
 export(is_has_label)
 export(lipid_components)
+export(median_polish_predict_dilutions)
 export(merge_compounds_tbl)
 export(merge_samples_tbl)
 export(normalize_peaks)
diff --git a/R/mutate_mzroll_list.R b/R/mutate_mzroll_list.R
index c2236ae..ef33fdf 100644
--- a/R/mutate_mzroll_list.R
+++ b/R/mutate_mzroll_list.R
@@ -453,7 +453,7 @@ normalize_peaks_median_polish <- function(mzroll_list,
 #' Using `median_polish_scaling_factor` output from `normalize_peaks_median_polish`,
 #' predict sample-wise dilutions
 #' 
-#' @details This function performs an inverse-normalization on the scaling factors,
+#' @details This function performs an inverse-log transformation on the scaling factors,
 #' and scales the samples based on the observed maximum scaling factor. Assumes that
 #' median polish is perform on log2 transformed data
 #' 
@@ -461,16 +461,18 @@ normalize_peaks_median_polish <- function(mzroll_list,
 #' @param scaling_factor scaling factor, defaults to `median_polish_scaling_factor`
 #' and must be a `samples` column in `mzroll_list`
 #' @param norm_scale_varname variable in samples to add for dilution predictions
-#' @param group_var optional grouping variable on which to calculate maximum dilution
+#' @param group_var optional grouping variable on which to calculate maximum dilution,
+#' must be a `samples` column in `mzroll_list`
 #' 
 #' @return a \code{mzroll_list} with \code{norm_scale_varname} variable added to 
 #' samples
 #'   
 #' @export
-median_polish_predict_dilutions <- function (mzroll_list,
-                                             scaling_factor = "median_polish_scaling_factor",
-                                             norm_scale_varname = "median_polish_predicted_dilutions",
-                                             group_vars = NULL) {
+median_polish_predict_dilutions <- function(mzroll_list,
+                                            scaling_factor = "median_polish_scaling_factor",
+                                            norm_scale_varname = "median_polish_predicted_dilutions",
+                                            group_vars = NULL) {
+  
   test_mzroll_list(mzroll_list)
   
   checkmate::assertString(scaling_factor)
@@ -487,21 +489,22 @@ median_polish_predict_dilutions <- function (mzroll_list,
     dplyr::mutate(temp_scaling_factor = !!rlang::sym(scaling_factor)) %>%
     dplyr::mutate(inverse_log_scaling_factor = 2^temp_scaling_factor) 
   
-  if(!is.null(group_var) && any(group_vars %in% colnames(mzroll_list$samples))) {
+  if(!is.null(group_vars) && any(group_vars %in% colnames(mzroll_list$samples))) {
     
     updated_samples <- updated_samples %>%
-      dplyr::group_by(group_vars) %>%
-      dplyr::mutate(m = max(inverse_log_scaling_factor)) %>%
-      dplyr::ungroup()
+      dplyr::group_by_at(group_vars) %>%
+      dplyr::mutate(m = max(inverse_log_scaling_factor))
     
   } else {
     
+    max_temp <- max(updated_samples$inverse_log_scaling_factor, na.rm = T)
     updated_samples <- updated_samples %>%
-      dplyr::mutate(m = max(inverse_log_scaling_factor))
+      dplyr::mutate(m = .env$max_temp)
     
   }
   
   updated_samples <- updated_samples %>%
+    dplyr::ungroup() %>%
     dplyr::rowwise() %>%
     dplyr::mutate(`:=`(!!rlang::sym(norm_scale_varname), 
                        inverse_log_scaling_factor/m)) %>%
diff --git a/man/median_polish_predict_dilutions.Rd b/man/median_polish_predict_dilutions.Rd
new file mode 100644
index 0000000..d85edbe
--- /dev/null
+++ b/man/median_polish_predict_dilutions.Rd
@@ -0,0 +1,37 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/mutate_mzroll_list.R
+\name{median_polish_predict_dilutions}
+\alias{median_polish_predict_dilutions}
+\title{Predict Dilutions from Median Polish Scaling Factor}
+\usage{
+median_polish_predict_dilutions(
+  mzroll_list,
+  scaling_factor = "median_polish_scaling_factor",
+  norm_scale_varname = "median_polish_predicted_dilutions",
+  group_vars = NULL
+)
+}
+\arguments{
+\item{mzroll_list}{data in triple omic structure}
+
+\item{scaling_factor}{scaling factor, defaults to `median_polish_scaling_factor`
+and must be a `samples` column in `mzroll_list`}
+
+\item{norm_scale_varname}{variable in samples to add for dilution predictions}
+
+\item{group_var}{optional grouping variable on which to calculate maximum dilution,
+must be a `samples` column in `mzroll_list`}
+}
+\value{
+a \code{mzroll_list} with \code{norm_scale_varname} variable added to 
+samples
+}
+\description{
+Using `median_polish_scaling_factor` output from `normalize_peaks_median_polish`,
+predict sample-wise dilutions
+}
+\details{
+This function performs an inverse-log transformation on the scaling factors,
+and scales the samples based on the observed maximum scaling factor. Assumes that
+median polish is perform on log2 transformed data
+}
diff --git a/man/normalize_peaks.Rd b/man/normalize_peaks.Rd
index 1c569bf..706efbf 100644
--- a/man/normalize_peaks.Rd
+++ b/man/normalize_peaks.Rd
@@ -87,7 +87,9 @@ normalize_peaks_center(mzroll_list, quant_peak_varname, norm_peak_varname)
 
 \item{normalization_method}{Normalization method to apply
 \itemize{
-  \item{\code{median polish}: column normalization based on average signal}
+  \item{\code{median polish}: column normalization based on average signal
+  (adds \code{median_polish_scaling_factor} as feature variable in addition to
+    \code{norm_peak_varname})}
   \item{\code{loading value}: column normalization using a sample-level
     value
     }

From e894a85c07441e0a57913392a78c7a23cc7ec8d2 Mon Sep 17 00:00:00 2001
From: Johanna Fleischman <71276903+johanna0321@users.noreply.github.com>
Date: Fri, 17 May 2024 12:44:26 -0700
Subject: [PATCH 8/9] Fix group_var name and add ungroup

---
 R/mutate_mzroll_list.R                 | 9 +++++----
 man/median_polish_predict_dilutions.Rd | 2 +-
 2 files changed, 6 insertions(+), 5 deletions(-)

diff --git a/R/mutate_mzroll_list.R b/R/mutate_mzroll_list.R
index ef33fdf..9d66aa7 100644
--- a/R/mutate_mzroll_list.R
+++ b/R/mutate_mzroll_list.R
@@ -471,7 +471,7 @@ normalize_peaks_median_polish <- function(mzroll_list,
 median_polish_predict_dilutions <- function(mzroll_list,
                                             scaling_factor = "median_polish_scaling_factor",
                                             norm_scale_varname = "median_polish_predicted_dilutions",
-                                            group_vars = NULL) {
+                                            group_var = NULL) {
   
   test_mzroll_list(mzroll_list)
   
@@ -489,10 +489,10 @@ median_polish_predict_dilutions <- function(mzroll_list,
     dplyr::mutate(temp_scaling_factor = !!rlang::sym(scaling_factor)) %>%
     dplyr::mutate(inverse_log_scaling_factor = 2^temp_scaling_factor) 
   
-  if(!is.null(group_vars) && any(group_vars %in% colnames(mzroll_list$samples))) {
+  if(!is.null(group_var) && any(group_var %in% colnames(mzroll_list$samples))) {
     
     updated_samples <- updated_samples %>%
-      dplyr::group_by_at(group_vars) %>%
+      dplyr::group_by_at(group_var) %>%
       dplyr::mutate(m = max(inverse_log_scaling_factor))
     
   } else {
@@ -1096,7 +1096,8 @@ normalize_peaks_center <- function (mzroll_list,
   updated_measurements <- mzroll_list$measurements %>%
     dplyr::group_by(groupId) %>%
     dplyr::mutate(!!rlang::sym(norm_peak_varname) :=
-        scale(!!rlang::sym(quant_peak_varname), scale = F, center = T))
+        scale(!!rlang::sym(quant_peak_varname), scale = F, center = T)) %>%
+    dplyr::ungroup()
   
   mzroll_list <- romic::update_tomic(mzroll_list, updated_measurements)
   
diff --git a/man/median_polish_predict_dilutions.Rd b/man/median_polish_predict_dilutions.Rd
index d85edbe..7818ef5 100644
--- a/man/median_polish_predict_dilutions.Rd
+++ b/man/median_polish_predict_dilutions.Rd
@@ -8,7 +8,7 @@ median_polish_predict_dilutions(
   mzroll_list,
   scaling_factor = "median_polish_scaling_factor",
   norm_scale_varname = "median_polish_predicted_dilutions",
-  group_vars = NULL
+  group_var = NULL
 )
 }
 \arguments{

From 56b69b46a54711ab649d48f7342be39387da8787 Mon Sep 17 00:00:00 2001
From: Johanna Fleischman <71276903+johanna0321@users.noreply.github.com>
Date: Mon, 20 May 2024 09:24:01 -0700
Subject: [PATCH 9/9] Add description tag

---
 R/mutate_mzroll_list.R | 1 +
 1 file changed, 1 insertion(+)

diff --git a/R/mutate_mzroll_list.R b/R/mutate_mzroll_list.R
index 9d66aa7..4b43e33 100644
--- a/R/mutate_mzroll_list.R
+++ b/R/mutate_mzroll_list.R
@@ -450,6 +450,7 @@ normalize_peaks_median_polish <- function(mzroll_list,
 
 #' Predict Dilutions from Median Polish Scaling Factor
 #' 
+#' @description
 #' Using `median_polish_scaling_factor` output from `normalize_peaks_median_polish`,
 #' predict sample-wise dilutions
 #'