In stemangiola/ARMET: Higher-Order Deconvolution Survival Analyses

title: "sccomp - Outlier-aware and count-based compositional analysis of single-cell data" output: github_document always_allow_html: true

knitr::opts_chunk$set( fig.path = "man/figures/")

Installation

devtools::install_github("stemangiola/ARMET")

Usage

library(ARMET)
library(dplyr)
library(tidyr)

data("test_mixture")
data("no_hierarchy_reference")

 estimates = 
    test_mixture |>
    convoluted_glm(
   ~ factor_of_interest,
   .sample = sample,
   .transcript = symbol,
   .abundance = count,
   reference = no_hierarchy_reference, use_cmdstanr = TRUE
  )

 estimates

Continuous regression

ACC = readRDS("/stornext/Bioinf/data/bioinf-data/Papenfuss_lab/projects/mangiola.s/ARMET_dev/dev/armet_ACC_input.rds")
prior_survival_time = ACC |> filter(!alive) |> distinct(patient, DSS.time.cr) |> pull(DSS.time.cr)

 estimates_continuous = 
    ACC |>
    mutate(DSS.time.cr = scale(sqrt(DSS.time.cr)) |> as.numeric()) |> 

    convoluted_glm(
   ~ DSS.time.cr,
   .sample = patient,
     .transcript = transcript,
     .abundance = count, 
   reference = no_hierarchy_reference,
   prior_survival_time = prior_survival_time,
   transform_time_function = sqrt, 
   use_cmdstanr = TRUE
  )

ACC = readRDS("/stornext/Bioinf/data/bioinf-data/Papenfuss_lab/projects/mangiola.s/ARMET_dev/dev/armet_ACC_input.rds")
prior_survival_time = ACC |> filter(!alive) |> distinct(patient, DSS.time.cr) |> pull(DSS.time.cr)

 estimates = 
    ACC |>

    #filter(alive==FALSE) |> nest(data = -patient) %>% sample_n(10) %>% unnest(data) %>% 
    convoluted_glm(
   ~ censored(DSS.time.cr, alive),
   .sample = patient,
     .transcript = transcript,
     .abundance = count, 
   reference = no_hierarchy_reference,
   prior_survival_time = prior_survival_time,
   transform_time_function = sqrt
  )

 ACC |>
filter(alive==FALSE) |> nest(data = -patient) %>% sample_n(10) %>% unnest(data) %>%
mutate(DSS.time.cr = DSS.time.cr %>% sqrt %>% scale %>% as.numeric) %>%
convoluted_glm(
~ DSS.time.cr,
.sample = patient,
.transcript = transcript,
.abundance = count,
reference = no_hierarchy_reference,
prior_survival_time = prior_survival_time,
transform_time_function = sqrt
)

armet_obj =     
    ACC |>
    setup_convolved_lm(
        ~ censored(time, alive),
            .sample = patient,
            .transcript = transcript,
            .abundance = count, 
            prior_survival_time = prior_survival_time, 
            transform_time_function = sqrt
    )


armet_hypothesis_test = 
    armet_estimate |>
    test_hypothesis_convoluted_lm()