In mstaniak/SharedPeptidesIso:

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Data

library(SharedPeptidesIso)
data("mouse_cluster")
knitr::kable(mouse_cluster)

Nonlinear model

model_full = IsoAPQModel(
  log(intensity/isoDistr) ~ log(..) + (1|precursor_scan) + (1|charge_in_scan) +
    sequence + rep,
  mouse_cluster
)

Coefficients:

round(coef(model_full), 3)

Protein abundances:

getIsoProteinAbundances(model_full)

Compare with linear model based on unique peptides:

data("mouse_cluster_unique")
head(mouse_cluster_unique)
model_lin = lme4::lmer(
  log(intensity/isoDistr) ~ 0 + P35278 + P61021 + Q9CQD1 +
    (1|precursor_scan) + (1|charge_in_scan) +
    sequence + rep,
  data = mouse_cluster_unique
)

fixed_coefs = lme4::fixef(model_lin)
fixed_coefs[1:3]

model_random_d = IsoAPQModelDesign(
  log(intensity/isoDistr) ~ log(..) + (1|precursor_scan) + (1|charge_in_scan),
  model_data = mouse_cluster
)
hasIsoFixedEffects(model_random_d)
# model_random = IsoAPQModel(
#   log(intensity/isoDistr) ~ log(..) + (1|precursor_scan) + (1|charge_in_scan),
#   model_data = mouse_cluster
# )

mstaniak/SharedPeptidesIso documentation built on Dec. 21, 2021, 10:11 p.m.