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update NEWS, changelog, Zenodo links
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‎README.md‎

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Original file line numberDiff line numberDiff line change
@@ -28,6 +28,12 @@ PCGR originates from the [Norwegian Cancer Genomics Consortium (NCGC)](https://c
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### Top News
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- *September 17th 2025:* **2.2.5 release**
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- fixing missing support for dp/af filtering, adding ad filtering
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- skip processing when no PASS variants detected in input VCF
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- more streamlined plotting functions in quarto report templates
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- [CHANGELOG](https://sigven.github.io/pcgr/articles/CHANGELOG.html)
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- *September 8th 2025:* **2.2.4 release**
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- various minor bug fixes, addition of `--sex` option for sex-adjusted CNA annotation
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- [CHANGELOG](https://sigven.github.io/pcgr/articles/CHANGELOG.html)
@@ -87,7 +93,7 @@ PCGR originates from the [Norwegian Cancer Genomics Consortium (NCGC)](https://c
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### Example reports
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90-
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.15068347.svg)](https://doi.org/10.5281/zenodo.15068347)
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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.17140659.svg)](https://doi.org/10.5281/zenodo.17140659)
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### Why use PCGR?
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‎pcgrr/R/utils.R‎

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@@ -845,51 +845,73 @@ filter_read_support <- function(vcf_df, config = NULL) {
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if("DP_TUMOR" %in% colnames(vcf_df)){
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if (!any(is.na(vcf_df$DP_TUMOR)) &
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!is.null(config$somatic_snv$allelic_support$tumor_dp_min)) {
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#cat("DP_TUMOR - Number of rows before filtering - ", nrow(vcf_df), "\n")
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#cat("DP_TUMOR - Filtering criteria used: ", config$somatic_snv$allelic_support$tumor_dp_min, "\n")
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vcf_df <- dplyr::filter(
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vcf_df,
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.data$DP_TUMOR >= config$somatic_snv$allelic_support$tumor_dp_min)
853+
#cat("DP_TUMOR - Number of rows after filtering: ", nrow(vcf_df), "\n")
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}
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}
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if("VAF_TUMOR" %in% colnames(vcf_df)){
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if (!any(is.na(vcf_df$VAF_TUMOR)) &
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!is.null(config$somatic_snv$allelic_support$tumor_af_min)) {
859+
#cat("VAF_TUMOR - Number of rows before filtering - ", nrow(vcf_df), "\n")
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#cat("VAF_TUMOR - Filtering criteria used: ", config$somatic_snv$allelic_support$tumor_af_min, "\n")
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vcf_df <- dplyr::filter(
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vcf_df,
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.data$VAF_TUMOR >= config$somatic_snv$allelic_support$tumor_af_min)
864+
#cat("VAF_TUMOR - Number of rows after filtering: ", nrow(vcf_df), "\n")
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}
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}
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if("AD_TUMOR" %in% colnames(vcf_df)){
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if (!any(is.na(vcf_df$AD_TUMOR)) &
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!is.null(config$somatic_snv$allelic_support$tumor_ad_min)) {
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#cat("AD_TUMOR - Number of rows before filtering - ", nrow(vcf_df), "\n")
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#cat("AD_TUMOR - Filtering criteria used: ", config$somatic_snv$allelic_support$tumor_ad_min, "\n")
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vcf_df <- dplyr::filter(
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vcf_df,
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.data$AD_TUMOR >= config$somatic_snv$allelic_support$tumor_ad_min)
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#cat("AD_TUMOR - Number of rows after filtering: ", nrow(vcf_df), "\n")
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}
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}
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if("VAF_CONTROL" %in% colnames(vcf_df)){
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if (!any(is.na(vcf_df$VAF_CONTROL)) &
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!is.null(config$somatic_snv$allelic_support$control_af_max)) {
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#cat("VAF_CONTROL - Number of rows before filtering - ", nrow(vcf_df), "\n")
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#cat("VAF_CONTROL - Filtering criteria used: ", config$somatic_snv$allelic_support$control_af_max, "\n")
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vcf_df <- dplyr::filter(
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vcf_df,
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.data$VAF_CONTROL <= config$somatic_snv$allelic_support$control_af_max)
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#cat("VAF_CONTROL - Number of rows after filtering: ", nrow(vcf_df), "\n")
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}
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}
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if("DP_CONTROL" %in% colnames(vcf_df)){
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if (!any(is.na(vcf_df$DP_CONTROL)) &
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!is.null(config$somatic_snv$allelic_support$control_dp_min)) {
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#cat("Number of rows before filtering - ", nrow(vcf_df), "\n")
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#cat("DP_CONTROL - Filtering criteria used: ", config$somatic_snv$allelic_support$control_dp_min, "\n")
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vcf_df <- dplyr::filter(
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vcf_df,
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.data$DP_CONTROL >= config$somatic_snv$allelic_support$control_dp_min)
902+
#cat("DP_CONTROL - Number of rows after filtering: ", nrow(vcf_df), "\n")
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}
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}
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if("AD_CONTROL" %in% colnames(vcf_df)){
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if (!any(is.na(vcf_df$AD_CONTROL)) &
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!is.null(config$somatic_snv$allelic_support$control_ad_max)) {
909+
#cat("AD_CONTROL - Number of rows before filtering - ", nrow(vcf_df), "\n")
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#cat("AD_CONTROL - Filtering criteria used: ", config$somatic_snv$allelic_support$control_ad_max, "\n")
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vcf_df <- dplyr::filter(
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vcf_df,
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.data$AD_CONTROL <= config$somatic_snv$allelic_support$control_ad_max)
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#cat("AD_CONTROL - Number of rows after filtering: ", nrow(vcf_df), "\n")
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}
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}
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‎pcgrr/inst/templates/pcgr_quarto_report/cna.qmd‎

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@@ -365,7 +365,8 @@ Gene symbols are color-coded according to their strength of association to cance
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dt_other_oncogenic <- pcgrr::get_oncogenic_cna_events(
368-
cna_df_display = pcg_report[["content"]][["cna"]][["callset"]][["variant_display"]])
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cna_df_display =
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pcg_report[["content"]][["cna"]][["callset"]][["variant_display"]])
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dt_other_oncongenic_cna <- DT::datatable(
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dt_other_oncogenic,

‎pcgrr/inst/templates/pcgr_quarto_report/documentation.qmd‎

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@@ -57,24 +57,25 @@ for(i in 1:NROW(ref_datasets)){
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s <- ""
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if(is.na(version)){
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if(!is.na(license_url)){
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s <- paste0(" * [", source_full, "](", url, ") - ", description, " - [",
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license,"](", license_url, ")")
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s <- glue::glue(
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" * [{source_full}]({url}) - {description} - [{license}]({license_url})")
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}else{
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s <- paste0(" * [", source_full, "](", url, ") - ", description, " - ",
64-
license)
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s <- glue::glue(
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" * [{source_full}]({url}) - {description} - {license}")
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}
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}else{
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if(!is.na(license_url)){
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if(source == "cgc" | source == "gepa" | source == "dbnsfp"){
69-
s <- paste0(" * [", source_full, "](", url, ") - ", description, " (<b>", version, "</b>)",
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" - [<b>", license,"</b>](", license_url, ")")
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s <- glue::glue(
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" * [{source_full}]({url}) - {description} (<b>{version}</b>) - [<b>{license}</b>]({license_url})")
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}else{
72-
s <- paste0(" * [", source_full, "](", url, ") - ", description, " (<b>", version, "</b>)",
73-
" - [", license,"](", license_url, ")")
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s <- glue::glue(
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" * [{source_full}]({url}) - {description} (<b>{version}</b>) - [{license}]({license_url})")
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}
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}else{
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s <- paste0(" * [", source_full, "](", url, ") - ", description, " (<b>", version, "</b>)",
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" - ", license)
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s <- glue::glue(
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" * [{source_full}]({url}) - {description} (<b>{version}</b>) - {license}"
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)
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}
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}
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if(s != ""){

‎pcgrr/pkgdown/index.md‎

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@@ -29,6 +29,12 @@ PCGR originates from the [Norwegian Cancer Genomics Consortium (NCGC)](https://c
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### Top News
3131

32+
- *September 17th 2025:* **2.2.5 release**
33+
- fixed failing support for AD/AF filtering, adding AD filtering
34+
- skip processing when no PASS variants detected in input VCF
35+
- more streamlined plotting functions in quarto report templates
36+
- [CHANGELOG](https://sigven.github.io/pcgr/articles/CHANGELOG.html)
37+
3238
- *September 8th 2025:* **2.2.4 release**
3339
- various minor bug fixes, addition of `--sex` option for sex-adjusted CNA annotation
3440
- [CHANGELOG](https://sigven.github.io/pcgr/articles/CHANGELOG.html)
@@ -88,7 +94,7 @@ PCGR originates from the [Norwegian Cancer Genomics Consortium (NCGC)](https://c
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## Example reports
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91-
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.15068347.svg)](https://doi.org/10.5281/zenodo.15068347)
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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.17140659.svg)](https://doi.org/10.5281/zenodo.17140659)
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## Why use PCGR?
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‎pcgrr/vignettes/CHANGELOG.Rmd‎

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@@ -47,14 +47,14 @@ pdiakumis <- user("pdiakumis")
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```
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## v2.2.5
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- Date: **2025-09-15**
50+
- Date: **2025-09-17**
5151
- fixed bug in filtering variants wrt depth/allelic support (`r issue(268)`)
5252
- added new options `--tumor_ad_min` and `--control_ad_max` to set minimum
5353
number of reads supporting alt allele in tumor (maximum allowed in control samples)
5454
for a variant to be considered (also `--tmb_ad_min` for TMB calculation)
5555
- options for allelic support/depth now defaults to `None` if not provided by user
5656
- omit processing when zero PASS variants found in input VCF (`r issue(256)`)
57-
- added gnomAD population frequencies from genome-sequenced samples to VEP annotation (for use with CPSR, option `--af_gnomadg` in VEP)
57+
- added gnomAD population frequencies from genome-sequenced samples to VEP annotation (primarily for use with CPSR, option `--af_gnomadg` in VEP)
5858
- populated patient/sample sex status in HTML report
5959
- avoid showing allelic support settings that are not actively used/set by the user
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- similarly for TMB-dedicated filters

‎pcgrr/vignettes/output.Rmd‎

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@@ -60,7 +60,7 @@ by the user. The following sections may be included in the report:
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#### Example reports
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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.15068347.svg)](https://doi.org/10.5281/zenodo.15068347)
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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.17140659.svg)](https://doi.org/10.5281/zenodo.17140659)
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### SNVs/InDels

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