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Auto-commit: apps/r/calculate_interaction_zscores5.R

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Bryan Roessler
2024-08-31 16:40:01 -04:00
parent 8973a3f0a7
commit 814cec8ca2
1 changed files with 37 additions and 37 deletions
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74
workflow/apps/r/calculate_interaction_zscores5.R
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@@ -516,6 +516,10 @@ main <- function() {
zscores_interactions_reference <- reference_results$zscores_interactions
zscores_calculations <- deletion_results$zscores_calculations
zscores_interactions <- deletion_results$zscores_interactions
zscores_interactions <- zscores_interactions %>%
arrange(desc(Z_lm_L)) %>%
arrange(desc(NG))
write.csv(zscores_calculations_reference, file = file.path(out_dir, "RF_ZScores_Calculations.csv"), row.names = FALSE)
write.csv(zscores_calculations, file = file.path(out_dir, "ZScores_Calculations.csv"), row.names = FALSE)
@@ -566,10 +570,6 @@ main <- function() {
write.csv(suppressors_lm_K,
file = file.path(out_dir, "ZScores_Interaction_DeletionSuppressors_K_lm.csv"), row.names = FALSE)
interaction_scores_deletion <- interaction_scores_deletion %>%
arrange(desc(Z_lm_L)) %>%
arrange(desc(NG))
# Generate plots for interaction scores
})
})
@@ -861,45 +861,45 @@ for (s in background_strains) {
# )
# }
print("Pass Int Calculation loop")
# print("Pass Int Calculation loop")
# Order the interaction scores by Z_lm_L and NG
interaction_scores_deletion <- interaction_scores_deletion %>%
arrange(desc(Z_lm_L)) %>%
arrange(desc(NG))
# # Order the interaction scores by Z_lm_L and NG
# interaction_scores_deletion <- interaction_scores_deletion %>%
# arrange(desc(Z_lm_L)) %>%
# arrange(desc(NG))
# Save the interaction scores and filtered sets for enhancers and suppressors
output_files <- list(
"ZScores_Interaction.csv" = interaction_scores_deletion,
"ZScores_Interaction_DeletionEnhancers_L.csv" = filter(interaction_scores_deletion, Avg_Zscore_L >= 2),
"ZScores_Interaction_DeletionEnhancers_K.csv" = filter(interaction_scores_deletion, Avg_Zscore_K <= -2),
"ZScores_Interaction_DeletionSuppressors_L.csv" = filter(interaction_scores_deletion, Avg_Zscore_L <= -2),
"ZScores_Interaction_DeletionSuppressors_K.csv" = filter(interaction_scores_deletion, Avg_Zscore_K >= 2),
"ZScores_Interaction_DeletionEnhancers_and_Suppressors_L.csv" = filter(interaction_scores_deletion, Avg_Zscore_L >= 2 | Avg_Zscore_L <= -2),
"ZScores_Interaction_DeletionEnhancers_and_Suppressors_K.csv" = filter(interaction_scores_deletion, Avg_Zscore_K >= 2 | Avg_Zscore_K <= -2),
"ZScores_Interaction_Suppressors_and_lm_Enhancers_L.csv" = filter(interaction_scores_deletion, Z_lm_L >= 2 & Avg_Zscore_L <= -2),
"ZScores_Interaction_Enhancers_and_lm_Suppressors_L.csv" = filter(interaction_scores_deletion, Z_lm_L <= -2 & Avg_Zscore_L >= 2),
"ZScores_Interaction_Suppressors_and_lm_Enhancers_K.csv" = filter(interaction_scores_deletion, Z_lm_K <= -2 & Avg_Zscore_K >= 2),
"ZScores_Interaction_Enhancers_and_lm_Suppressors_K.csv" = filter(interaction_scores_deletion, Z_lm_K >= 2 & Avg_Zscore_K <= -2)
)
# output_files <- list(
# "ZScores_Interaction.csv" = interaction_scores_deletion,
# "ZScores_Interaction_DeletionEnhancers_L.csv" = filter(interaction_scores_deletion, Avg_Zscore_L >= 2),
# "ZScores_Interaction_DeletionEnhancers_K.csv" = filter(interaction_scores_deletion, Avg_Zscore_K <= -2),
# "ZScores_Interaction_DeletionSuppressors_L.csv" = filter(interaction_scores_deletion, Avg_Zscore_L <= -2),
# "ZScores_Interaction_DeletionSuppressors_K.csv" = filter(interaction_scores_deletion, Avg_Zscore_K >= 2),
# "ZScores_Interaction_DeletionEnhancers_and_Suppressors_L.csv" = filter(interaction_scores_deletion, Avg_Zscore_L >= 2 | Avg_Zscore_L <= -2),
# "ZScores_Interaction_DeletionEnhancers_and_Suppressors_K.csv" = filter(interaction_scores_deletion, Avg_Zscore_K >= 2 | Avg_Zscore_K <= -2),
# "ZScores_Interaction_Suppressors_and_lm_Enhancers_L.csv" = filter(interaction_scores_deletion, Z_lm_L >= 2 & Avg_Zscore_L <= -2),
# "ZScores_Interaction_Enhancers_and_lm_Suppressors_L.csv" = filter(interaction_scores_deletion, Z_lm_L <= -2 & Avg_Zscore_L >= 2),
# "ZScores_Interaction_Suppressors_and_lm_Enhancers_K.csv" = filter(interaction_scores_deletion, Z_lm_K <= -2 & Avg_Zscore_K >= 2),
# "ZScores_Interaction_Enhancers_and_lm_Suppressors_K.csv" = filter(interaction_scores_deletion, Z_lm_K >= 2 & Avg_Zscore_K <= -2)
# )
for (file_name in names(output_files)) {
write.csv(output_files[[file_name]], file = file.path(output_dir, file_name), row.names = FALSE)
}
# for (file_name in names(output_files)) {
# write.csv(output_files[[file_name]], file = file.path(output_dir, file_name), row.names = FALSE)
# }
# Further filtering for linear regression enhancers and suppressors
output_files_lm <- list(
"ZScores_Interaction_DeletionEnhancers_L_lm.csv" = filter(interaction_scores_deletion, Z_lm_L >= 2),
"ZScores_Interaction_DeletionEnhancers_K_lm.csv" = filter(interaction_scores_deletion, Z_lm_K <= -2),
"ZScores_Interaction_DeletionSuppressors_L_lm.csv" = filter(interaction_scores_deletion, Z_lm_L <= -2),
"ZScores_Interaction_DeletionSuppressors_K_lm.csv" = filter(interaction_scores_deletion, Z_lm_K >= 2),
"ZScores_Interaction_DeletionEnhancers_and_Suppressors_L_lm.csv" = filter(interaction_scores_deletion, Z_lm_L >= 2 | Z_lm_L <= -2),
"ZScores_Interaction_DeletionEnhancers_and_Suppressors_K_lm.csv" = filter(interaction_scores_deletion, Z_lm_K >= 2 | Z_lm_K <= -2)
)
# # Further filtering for linear regression enhancers and suppressors
# output_files_lm <- list(
# "ZScores_Interaction_DeletionEnhancers_L_lm.csv" = filter(interaction_scores_deletion, Z_lm_L >= 2),
# "ZScores_Interaction_DeletionEnhancers_K_lm.csv" = filter(interaction_scores_deletion, Z_lm_K <= -2),
# "ZScores_Interaction_DeletionSuppressors_L_lm.csv" = filter(interaction_scores_deletion, Z_lm_L <= -2),
# "ZScores_Interaction_DeletionSuppressors_K_lm.csv" = filter(interaction_scores_deletion, Z_lm_K >= 2),
# "ZScores_Interaction_DeletionEnhancers_and_Suppressors_L_lm.csv" = filter(interaction_scores_deletion, Z_lm_L >= 2 | Z_lm_L <= -2),
# "ZScores_Interaction_DeletionEnhancers_and_Suppressors_K_lm.csv" = filter(interaction_scores_deletion, Z_lm_K >= 2 | Z_lm_K <= -2)
# )
for (file_name in names(output_files_lm)) {
write.csv(output_files_lm[[file_name]], file = file.path(output_dir, file_name), row.names = FALSE)
}
# for (file_name in names(output_files_lm)) {
# write.csv(output_files_lm[[file_name]], file = file.path(output_dir, file_name), row.names = FALSE)
# }
# Loop through each gene to generate plots