inst/doc/treatment_example.R

In gimap: Calculate Genetic Interactions for Paired CRISPR Targets

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

## ----echo = FALSE, results = 'hide'-------------------------------------------
library(gimap)

## ----eval = FALSE-------------------------------------------------------------
# output_dir <- "output_treatment"
# dir.create(output_dir, showWarnings = FALSE)

## ----eval = FALSE-------------------------------------------------------------
# example_data <- get_example_data("count_treatment")

## ----eval = FALSE-------------------------------------------------------------
# colnames(example_data)

## ----eval = FALSE-------------------------------------------------------------
# counts <- example_data %>%
#   select(c("pretreatment", "dmsoA", "dmsoB", "drug1A", "drug1B")) %>%
#   as.matrix()

## ----eval = FALSE-------------------------------------------------------------
# pg_ids <- example_data %>%
#   dplyr::select("id")

## ----eval = FALSE-------------------------------------------------------------
# sample_metadata <- data.frame(
#   col_names = c("pretreatment", "dmsoA", "dmsoB", "drug1A", "drug1B"),
#   drug_treatment = as.factor(c("pretreatment", "dmso", "dmso", "drug", "drug"))
# )

## ----eval = FALSE-------------------------------------------------------------
# gimap_dataset <- setup_data(
#   counts = counts,
#   pg_ids = pg_ids,
#   sample_metadata = sample_metadata
# )

## ----eval = FALSE-------------------------------------------------------------
# str(gimap_dataset)

## ----eval = FALSE-------------------------------------------------------------
# nrow(gimap_dataset$transformed_data$log2_cpm)

## ----eval = FALSE-------------------------------------------------------------
# run_qc(gimap_dataset,
#   output_file = file.path(output_dir, "example_qc_report.Rmd"),
#   overwrite = TRUE,
#   plots_dir = "plots",
#   quiet = TRUE
# )

## ----eval = FALSE-------------------------------------------------------------
# gimap_filtered <- gimap_dataset %>%
#   gimap_filter()

## ----eval = FALSE-------------------------------------------------------------
# nrow(gimap_filtered$filtered_data$transformed_log2_cpm)

## ----eval = FALSE-------------------------------------------------------------
# str(gimap_filtered$filtered_data)

## ----eval = FALSE-------------------------------------------------------------
# nrow(gimap_filtered$filtered_data$transformed_log2_cpm)

## ----eval = FALSE-------------------------------------------------------------
# gimap_dataset <- gimap_filtered %>%
#   gimap_annotate(cell_line = "PC9") %>%
#   # Whatever is specified for "control_name" is what will be used to normalize other data points
#   gimap_normalize(
#     treatments = "drug_treatment",
#     control_name = "pretreatment"
#   ) %>%
#   calc_gi()

## ----eval = FALSE-------------------------------------------------------------
# head(gimap_dataset$gi_scores)

## ----eval = FALSE-------------------------------------------------------------
# head(dplyr::arrange(gimap_dataset$gi_score, fdr))

## ----eval = FALSE-------------------------------------------------------------
# plot_exp_v_obs_scatter(gimap_dataset)
# 
# # Save it to a file
# ggsave(file.path(output_dir, "exp_v_obs_scatter.png"))

## ----eval = FALSE-------------------------------------------------------------
# plot_rank_scatter(gimap_dataset)
# 
# # Save it to a file
# ggsave(file.path(output_dir, "plot_rank_scatter.png"))

## ----eval = FALSE-------------------------------------------------------------
# plot_volcano(gimap_dataset)
# 
# # Save it to a file
# ggsave(file.path(output_dir, "volcano_plot.png"))

## ----eval = FALSE-------------------------------------------------------------
# # "DUSP21_DUSP18" is top result so let's plot that
# plot_targets(gimap_dataset, target1 = "DUSP21", target2 = "DUSP18")
# 
# # Save it to a file
# ggsave(file.path(output_dir, "DUSP21_DUSP18.png"))

## ----eval = FALSE-------------------------------------------------------------
# readr::write_tsv(gimap_dataset$gi_scores, file.path(output_dir, "gi_scores.tsv"))

## ----eval = FALSE-------------------------------------------------------------
# saveRDS(gimap_dataset, file.path(output_dir, "gimap_dataset_final_treatment.RDS"))

## -----------------------------------------------------------------------------
sessionInfo()