In rioualen/NetworkEval: What the Package Does (One Line, Title Case)

Sys.getenv("PATH")
knitr::opts_knit$set(root.dir = "/Users/rioualen/Desktop/NetworkEval/")
knitr::opts_chunk$set(echo=FALSE, include=TRUE, warning=FALSE, message=FALSE, results = 'asis')

library(kableExtra)
library(EcoliGenes)

This report is generated by the NetworkEval R package. Its purpose is to evaluate the accuracy of a set of predicted TF-gene interactions, by comparing them against a set of positive and negative regulatory interactions (RIs) generated using various strategies.

Prediction set: r my_eval@pred_set@id

Summary of input interactions

# cat(paste0("Evaluated set: ", pred_set_id))

table <- data.frame(RIs = get_ris_n(my_eval@pred_set) + nrow(my_eval@out_ris), TFs = get_tfs_n(my_eval@pred_set) + length(my_eval@out_tfs))
kable(table, digits=2, format.args = list(big.mark = ','))  %>% kable_styling(full_width = F, font_size = 20)

# cat("<b>List of TFs: </b>")
# cat(paste0((get_tfs(my_eval@pred_set)), collapse = ", "))

Selection of transcription factors

Evaluated TFs

In order to evaluate TF-gene predicted interactions, we first select the TFs for which we have controls available. The following TFs will thus be evaluated:

# tfs_in <- sapply(get_tfs_eval(my_eval), FUN=function(x){gene_list_by_bnum[[x]]$GENE_NAME[1]})
tfs_in <- EcoliGenes::bnumber_to_symbol(get_tfs_eval(my_eval))
cat(paste0((sort(tfs_in)), collapse = ", "))

cat(paste0("\n\n* Total: ", length(tfs_in)))

Discarded TFs

The following TFs were discarded, for there is no control available to evaluate their interactions:

tfs_out <- my_eval@out_tfs
# tfs_out <- sapply(tfs_out, FUN=function(x){gene_list_by_bnum[[x]]$GENE_NAME[1]})
tfs_out <- EcoliGenes::bnumber_to_symbol(tfs_out)

if (length(tfs_out) != 0) { cat(paste0((sort(tfs_out)), collapse = ", ")) }

cat(paste0("\n\n* Total: ", length(tfs_out)))

The interactions involving those TFs are also discarded of the evaluation.

• Number of interactions excluded: r nrow(my_eval@out_ris)

Evaluation

Summary of evaluated interactions

kable(summarize(my_eval@pred_set), digits=2, format.args = list(big.mark = ','))  %>% kable_styling(full_width = F, font_size = 20)

# cat("<b>List of TFs: </b>")
# cat(paste0((get_tfs(my_eval@pred_set)), collapse = ", "))

Statistics

kable(summarize_stats(my_eval), digits=3, format.args = list(big.mark = ',')) %>% kable_styling(full_width = F, font_size = 20)

Confusion matrix

kable(generate_confusion_matrix(my_eval), digits=2, format.args = list(big.mark = ',')) %>% kable_styling(full_width = F, font_size = 20)

Only interactions that present in either the positive set or the negative set can be labeled. The other interactions are not displayed

• Number of interactions not displayed: r get_ris_n(outer_set(my_eval))

• Proportion of the evaluated set: r round(get_ris_n(outer_set(my_eval))/get_ris_n(my_eval@pred_set)*100, 1)%

Venn diagrams

Comparison of sets

generate_venn_diagram(my_eval, style=1, universe=FALSE)
generate_venn_diagram(my_eval, style=2, universe=FALSE)

Comparison of sets -- including all possible interactions

generate_venn_diagram(my_eval, style=1, universe=TRUE)
generate_venn_diagram(my_eval, style=2, universe=TRUE)

if (length(my_eval@pred_set@scores) >= 1) {
   cat(paste0("\n\n## ROC curves\n"))

   cat(paste0("\n\nNB: curve based on ", round(get_ris_n(inner_set(my_eval))/get_ris_n(my_eval@pred_set)*100, 1), "% of the data.\n\n"))

   roc <- generate_roc_curve(my_eval)

   plot(roc$curve)

   kable(roc$auc, digits=3, format.args = list(big.mark = ',')) %>% kable_styling(full_width = F, font_size = 12, bootstrap_options = c("striped", "hover"))
}

if (length(my_eval@pred_set@scores) >= 1) {

   cat(paste0("\n\n## ROC curves -- shuffled scores\n"))

   shuffled_eval <- shuffle_scores(my_eval)

   roc <- generate_roc_curve(shuffled_eval)

   plot(roc$curve)

   #kable(roc$auc, digits=3, format.args = list(big.mark = ',')) %>% kable_styling(full_width = F, font_size = 12, bootstrap_options = c("striped", "hover"))
}

Control sets

Summary of the positive set

kable(summarize(my_eval@pos_set), digits=2, format.args = list(big.mark = ',')) %>% kable_styling(full_width = F, font_size = 20)

# cat("<b>List of TFs: </b>")
# cat(paste0((get_tfs(my_eval@pos_set)), collapse = ", "))

Summary of the negative set

kable(summarize(my_eval@neg_set), digits=2, format.args = list(big.mark = ',')) %>% kable_styling(full_width = F, font_size = 20)

# cat("<b>List of TFs: </b>")
# cat(paste0((get_tfs(my_eval@neg_set)), collapse = ", "))

rioualen/NetworkEval documentation built on April 10, 2021, 5:22 a.m.