MissingHelpers: compute group mean by LOD

In wolski/prolfqua: Proteomics Label Free Quantification

compute group mean by LOD

Description

compute group mean by LOD

compute group mean by LOD

Details

weight lod by nr of NA's $(LOD * nrNas + meanAbundance *nrObs)/(nrMeasured)$

Public fields

data

data

config

config

prob

quantile of groups with one observed value to estimate LOD

keep

stats which might be time consuming to compute

weighted

should we weight the LOD

Active bindings

keep

stats which might be time consuming to compute

Methods

Public methods

• MissingHelpers$new()

• MissingHelpers$get_stats()

• MissingHelpers$get_LOD()

• MissingHelpers$impute_weighted_lod()

• MissingHelpers$impute_lod()

• MissingHelpers$get_poolvar()

• MissingHelpers$get_contrast_estimates()

• MissingHelpers$get_contrasts()

• MissingHelpers$clone()

---

Method new()

initialize

Usage

MissingHelpers$new(data, config, prob = 0.5, weighted = TRUE)

Arguments

data

data

config

config

prob

default 0.5, median of groups with one observed value

weighted

should group average be computed used weighting, default TRUE.

---

Method get_stats()

Usage

MissingHelpers$get_stats()

---

Method get_LOD()

Usage

MissingHelpers$get_LOD()

---

Method impute_weighted_lod()

Usage

MissingHelpers$impute_weighted_lod()

---

Method impute_lod()

Usage

MissingHelpers$impute_lod()

---

Method get_poolvar()

Usage

MissingHelpers$get_poolvar(prob = 0.75)

---

Method get_contrast_estimates()

get contrast estimates

Usage

MissingHelpers$get_contrast_estimates(Contrasts)

Arguments

Contrasts

named array with contrasts

---

Method get_contrasts()

Usage

MissingHelpers$get_contrasts(Contrasts, confint = 0.95, all = FALSE)

---

Method clone()

The objects of this class are cloneable with this method.

Usage

MissingHelpers$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

Contrasts <- c("group.b-a" = "group_A - group_B", "group.a-ctrl" = "group_A - group_Ctrl")
dd <- prolfqua::sim_lfq_data_protein_config(Nprot = 100,weight_missing = 2)
mh <- prolfqua::MissingHelpers$new(dd$data, dd$config, prob = 0.8,weighted = TRUE)
mh$get_stats()
mh$get_LOD()
mh$impute_weighted_lod()
mh$impute_lod()
mh$get_poolvar()
bb <- mh$get_contrast_estimates(Contrasts)
mh$get_contrasts(Contrasts)

dd <- prolfqua::sim_lfq_data_2Factor_config(Nprot = 100,weight_missing = 0.1)

Contrasts <- c("c1" = "TreatmentA - TreatmentB",
               "C2" = "BackgroundX- BackgroundZ",
               "c3" = "`TreatmentA:BackgroundX` - `TreatmentA:BackgroundZ`",
               "c4" = "`TreatmentB:BackgroundX` - `TreatmentB:BackgroundZ`"
               )
mh <- prolfqua::MissingHelpers$new(dd$data, dd$config, prob = 0.8,weighted = TRUE)
mh$get_stats()$interaction |> table()
mh$get_contrast_estimates(Contrasts)

wolski/prolfqua documentation built on May 12, 2024, 10:16 p.m.