minor bug fixing

R/classification.R

@@ -13,7 +13,7 @@ assign_classification <- function(var_calls) {
 
   pcgrr::log4r_info(paste0(
     "Assigning five-tier classifications (P, LP, VUS, LB, B) based on ",
-    "aggregated scores from ACMG criteria"))
+    "aggregated ACMG points"))
 
   path_cols <- c(
     "CPSR_CLASSIFICATION",
@@ -203,7 +203,7 @@ assign_pathogenicity_evidence <- function(var_calls, settings, ref_data) {
   #pcgrr::validate_settings(settings)
 
   pcgrr::log4r_info(
-    "Assigning pathogenicity codes according to enhanced ACMG criteria/guidelines")
+    "Assigning variant classification codes according to refined ACMG criteria")
   classification_settings <-
     settings$conf$variant_classification
 

R/main.R

@@ -116,53 +116,61 @@ generate_cpsr_report <- function(yaml_fname = NULL) {
   callset_all <- list()
   callset_all[['variant']] <-
     cps_report$content$snv_indel[['callset']]$variant$all
-  cps_report$content$snv_indel$v_stat <-
-    pcgrr::variant_stats_report(
-      callset = callset_all,
-      name = "v_stat")$v_stat
+  if(NROW(callset_all[['variant']]) > 0){
+    cps_report$content$snv_indel$v_stat <-
+      pcgrr::variant_stats_report(
+        callset = callset_all,
+        name = "v_stat")$v_stat
+  }
 
   ## get overall call statistics (cpg targets only)
   callset_cpg <- list()
   callset_cpg[['variant']] <-
     cps_report$content$snv_indel[['callset']]$variant$cpg_non_sf
-  cps_report$content$snv_indel$v_stat_cpg <-
-    pcgrr::variant_stats_report(
-      callset = callset_cpg,
-      name = "v_stat_cpg")$v_stat_cpg
+  if(NROW(callset_cpg[['variant']]) > 0){
+    cps_report$content$snv_indel$v_stat_cpg <-
+      pcgrr::variant_stats_report(
+        callset = callset_cpg,
+        name = "v_stat_cpg")$v_stat_cpg
+  }
 
   ## get overall call statistics (sf targets only)
   callset_sf <- list()
   callset_sf[['variant']] <-
     cps_report$content$snv_indel[['callset']]$variant$sf
-  cps_report$content$snv_indel$v_stat_sf <-
-    pcgrr::variant_stats_report(
-      callset = callset_sf,
-      name = "v_stat_sf")$v_stat_sf
+  if(NROW(callset_sf[['variant']]) > 0){
+    cps_report$content$snv_indel$v_stat_sf <-
+      pcgrr::variant_stats_report(
+        callset = callset_sf,
+        name = "v_stat_sf")$v_stat_sf
+  }
 
   callset_bm <- list()
   callset_bm[['variant']] <-
     cps_report$content$snv_indel[['callset']]$variant$bm
-  cps_report$content$snv_indel$v_stat_bm <-
-    pcgrr::variant_stats_report(
-      callset = callset_bm,
-      name = "v_stat_bm")$v_stat_bm
+  if(NROW(callset_bm[['variant']]) > 0){
+    cps_report$content$snv_indel$v_stat_bm <-
+      pcgrr::variant_stats_report(
+        callset = callset_bm,
+        name = "v_stat_bm")$v_stat_bm
+  }
 
   pcgrr::log4r_info(
     paste0(
       "Total number of variants in target cancer predisposition genes: ",
-      cps_report$content$snv_indel[["v_stat_cpg"]][["n"]]
+      "N = ", cps_report$content$snv_indel[["v_stat_cpg"]][["n"]]
     )
   )
   pcgrr::log4r_info(
     paste0(
       "Number of coding variants in target cancer predisposition genes: ",
-      cps_report$content$snv_indel[["v_stat_cpg"]][["n_coding"]]
+      "N = ", cps_report$content$snv_indel[["v_stat_cpg"]][["n_coding"]]
     )
   )
   pcgrr::log4r_info(
     paste0(
       "Number of non-coding variants in cancer predisposition genes: ",
-      cps_report$content$snv_indel[["v_stat_cpg"]][["n_noncoding"]]
+      "N = ", cps_report$content$snv_indel[["v_stat_cpg"]][["n_noncoding"]]
     )
   )
 

inst/templates/quarto/cpsr_biomarkers.qmd

@@ -15,6 +15,10 @@ for (etype in c("Predictive","Diagnostic","Predisposing","Prognostic")) {
   show_germline_filters[[tolower(etype)]] <- F
   missing_germline_items[[tolower(etype)]] <- T
   
+  if(NROW(cps_report[["content"]][["snv_indel"]]$callset$variant_display$bm) == 0){
+    next
+  }
+  
   etype_set[[tolower(etype)]] <- 
     cps_report[["content"]][["snv_indel"]]$callset$variant_display$bm |>
     dplyr::filter(.data$BM_EVIDENCE_TYPE == etype)
@@ -49,7 +53,7 @@ The same genetic variant may match with multiple evidence items, pending on the
 ```{r biomarker_note}
 #| echo: false
 #| output: asis
-#| include: !expr biomarker_present
+#| include: true
 
 cat("\n::: {.callout-note}\n Biomarkers registered in CIViC/CGI are provided at different _resolutions_ (i.e. filter <b>Biomarker resolution</b>). The accuracy of a match between a variant in the sample and a clinical evidence item (biomarker) will vary accordingly (highlighted by gene symbols with different color backgrounds):\n\n")
 

inst/templates/quarto/cpsr_classification.qmd

@@ -635,7 +635,7 @@ htmltools::br()
 <br>
 
 *  A total of n = __`r tot_variants[['class2']][['ClinVar']]`__ variants are recorded with a <i>Likely Benign</i> clinical significance in the [ClinVar](https://www.ncbi.nlm.nih.gov/clinvar/) database.
-*  A total of n = __`r tot_variants[['class2']][['CPSR_ACMG']]`__ <i><b>Other</b></i> variants (i.e. not submitted to/recorded in ClinVar) are classified with a <i>Likely Benign</i> clinical significance by CPSR (refined ACMG criteria - based on population frequency and variant effect).
+*  A total of n = __`r tot_variants[['class2']][['CPSR_ACMG']]`__ <i><b>non-ClinVar</b></i> variants (i.e. not submitted to/recorded in ClinVar) are classified with a <i>Likely Benign</i> clinical significance by CPSR (refined ACMG criteria - based on population frequency and variant effect).
 
 ::: {.callout-note}
 Variants displayed here constitute the top 2000 variants for each of the ClinVar and non-ClinVar variant sets (due to display limitations with client-side tables)

inst/templates/quarto/cpsr_summary.qmd

@@ -82,7 +82,7 @@ bslib::layout_column_wrap(
     value = paste0(
       "N = ", 
       cps_report$content$snv_indel$v_stat_cpg$n_p + 
-        cps_report$content$snv_indel$v_stat_cpg$n_p),
+        cps_report$content$snv_indel$v_stat_cpg$n_lp),
     showcase = bsicons::bs_icon("bullseye"), 
     theme = bslib::value_box_theme(
       bg = color_lp, fg = "#fff"),

inst/templates/quarto/cpsr_virtual_panel.qmd

@@ -18,9 +18,7 @@ tiles_html <- cpsr::plot_virtual_panels(
 <br>
 
 ::: {.callout-note}
-CPSR does not perform any interrogation of _which genes 
-that were subject to sequencing_, it merely checks potential overlap of input variants 
-within the user-defined __virtual__ gene panel.
+For the sample in question, `r cps_report$settings$sample_id`, CPSR does **not** perform any interrogation of _which genes that were subject to sequencing_. CPSR classifies only input variants (i.e. as found in the query VCF) within the user-defined __virtual__ gene panel.
 :::
 
 <br>