vignettes update

DESCRIPTION

@@ -2,7 +2,7 @@ Package: cpsr
 Type: Package
 Title: Cancer Predisposition Sequencing Reporter (CPSR)
 Version: 1.0.1.9003
-Date: 2023-12-13
+Date: 2024-02-04
 Authors@R:
     c(person(given = "Sigve",
              family = "Nakken",
@@ -48,6 +48,6 @@ Suggests:
     rmarkdown
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Roxygen: list(markdown = TRUE)
 VignetteBuilder: knitr

R/main.R

@@ -361,7 +361,7 @@ write_cpsr_output <- function(report,
   fnames[["tsv"]] <-
     file.path(output_dir,
               paste0(sample_fname_pattern,
-                     ".snvs_indels.tiers.tsv.gz"))
+                     ".snvs_indels.tsv.gz"))
   fnames[["xlsx"]] <-
     file.path(output_dir,
               paste0(sample_fname_pattern,

inst/templates/cpsr_report.qmd

@@ -15,7 +15,9 @@ include-in-header:
       }
       </style>
 nocite: |
-  @Nakken2021-mb, @Huang2018-ah, @Richards2015-kj, @Maxwell2016-mr, @Amendola2016-pu, @Griffith2017-do, @Martin2019-nq, @Nykamp2017-rj, Dienstmann2015-od
+  @Nakken2021-mb, @Huang2018-ah, @Richards2015-kj, 
+  @Maxwell2016-mr, @Amendola2016-pu, @Griffith2017-do, 
+  @Martin2019-nq, @Nykamp2017-rj, Dienstmann2015-od
 format: 
   html:
     embed-resources: true

pkgdown/index.md

@@ -4,9 +4,9 @@
 
 <br>
 
-The *Cancer Predisposition Sequencing Reporter (CPSR)* is a computational workflow that **interprets germline variants** identified from next-generation sequencing **in the context of cancer predisposition**. The workflow is integrated with the framework that underlies [Personal Cancer Genome Reporter - PCGR ](https://github.com/sigven/pcgr). While *PCGR* is primarily intended for reporting and analysis of somatic variants detected in a tumor, *CPSR* is intended for reporting and ranking of germline variants in protein-coding genes that are implicated in cancer predisposition and inherited cancer syndromes.
+The *Cancer Predisposition Sequencing Reporter (CPSR)* is a computational workflow that **interprets germline variants** identified from next-generation sequencing **in the context of cancer predisposition**. The workflow is integrated with the framework that underlies [Personal Cancer Genome Reporter - PCGR ](https://github.com/sigven/pcgr). While *PCGR* is intended for reporting and analysis of somatic variants detected in a tumor, *CPSR* is intended for reporting and ranking of germline variants in protein-coding genes that are implicated in cancer predisposition and inherited cancer syndromes.
 
-*CPSR* accepts a query file with raw germline variant calls(SNVs/InDels) from a single sample, encoded in the [VCF format ](https://samtools.github.io/hts-specs/VCFv4.2.pdf). Through the use several different [virtual cancer predisposition gene panels](articles/virtual_panels.html), the user can flexibly put a restriction on which genes and findings are displayed in the cancer predisposition report.
+*CPSR* accepts a query file with raw germline variant calls(SNVs/InDels) from a single sample, encoded in the [VCF format ](https://samtools.github.io/hts-specs/VCFv4.2.pdf). Through the use several different [virtual cancer predisposition gene panels](articles/virtual_panels.html), the user can flexibly put a restriction on which genes and findings are displayed in the cancer predisposition report. *CPSR* determines the clinical significance of variants through the implementation of refined ACMG-AMP variant classification criteria.
 
 Snapshots of sections in the cancer predisposition genome report:
 
@@ -15,7 +15,7 @@ Snapshots of sections in the cancer predisposition genome report:
 The software performs extensive variant annotation on the selected geneset and produces an interactive HTML report, in which the user can investigate:
 
 * __ClinVar variants__ - pre-classified variants according to a five-level tier scheme in ClinVar (Pathogenic to Benign)
-* __Novel variants__ - classified by CPSR through ACMG criteria (variant frequency levels and functional effects) into to a five-level tier scheme (Pathogenic to Benign)
+* __Novel variants__ - classified by CPSR through refined ACMG criteria (variant frequency levels and functional effects) into a five-level classification scheme (Pathogenic to Benign)
 * __Variant biomarkers__ - cancer predisposition variants with reported implications for prognosis, diagnosis or therapeutic regimens
 * __Secondary findings (optional)__ - pathogenic ClinVar variants in the [ACMG recommended list for reporting of secondary findings](https://www.ncbi.nlm.nih.gov/clinvar/docs/acmg/)
 * __GWAS hits (optional)__ - variants overlapping with previously identified hits in genome-wide association studies (GWAS) of cancer phenotypes (i.e. low to moderate risk conferring alleles), using [NHGRI-EBI Catalog of published genome-wide association studies](https://www.ebi.ac.uk/gwas/) as the underlying source.
@@ -26,7 +26,7 @@ The variant sets can be interactively explored and filtered further through diff
 ### News
 
 * *November 2022*: **1.0.1 release**
-  * Added CPSR logo (designed by [Hal Nakken](halvetica.net))
+  * Added CPSR logo (designed by [Hal Nakken](https://halvetica.net))
 
 * *February 2022*: **1.0.0 release**
   * Complete restructure of code and Conda installation routines, contributed largely by the great [@pdiakumis](https://github.com/pdiakumis)

vignettes/annotation_resources.Rmd

@@ -4,30 +4,30 @@ output: rmarkdown::html_document
 ---
 
 ### Basic variant consequence annotation
-  * [VEP v105](http://www.ensembl.org/info/docs/tools/vep/index.html) - Variant Effect Predictor ([GENCODE v39](https://www.gencodegenes.org/human/) as gene reference database (v19 for grch37))
+  * [VEP v111](http://www.ensembl.org/info/docs/tools/vep/index.html) - Variant Effect Predictor ([GENCODE v45](https://www.gencodegenes.org/human/) as gene reference database (v19 for grch37))
 
 ###  *Insilico* predictions of effect of coding variants
-  * [dBNSFP](https://sites.google.com/site/jpopgen/dbNSFP) - database of non-synonymous functional predictions (v4.2, March 2021)
+  * [dBNSFP](https://sites.google.com/site/jpopgen/dbNSFP) - database of non-synonymous functional predictions (v4.5, November 2023)
 
 ###  Variant frequency databases
   * [gnomAD](http://exac.broadinstitute.org/) - germline variant frequencies exome-wide (r2.1, October 2018)
   * [dbSNP](http://www.ncbi.nlm.nih.gov/SNP/) - database of short genetic variants (build 154)
   * [Cancer Hotspots](http://cancerhotspots.org) - a resource for statistically significant mutations in cancer (v2, 2017)
 
 ### Variant databases of clinical utility
-  * [ClinVar](http://www.ncbi.nlm.nih.gov/clinvar/) - database of clinically related variants (February 2022)
-  * [CIViC](https://civicdb.org) - clinical interpretations of variants in cancer (February 1st 2022)
+  * [ClinVar](http://www.ncbi.nlm.nih.gov/clinvar/) - database of clinically related variants (January 2024)
+  * [CIViC](https://civicdb.org) - clinical interpretations of variants in cancer (February 2nd 2024)
 
 ### Protein domains/functional features
-  * [UniProt/SwissProt KnowledgeBase](http://www.uniprot.org) - resource on protein sequence and functional information (2021_04, November 2021)
+  * [UniProt/SwissProt KnowledgeBase](http://www.uniprot.org) - resource on protein sequence and functional information (2023_05)
   * [Pfam](http://pfam.xfam.org) - database of protein families and domains (v35.0, November 2021)
 
 ### Cancer gene knowledge bases
-  * [CancerMine](http://bionlp.bcgsc.ca/cancermine/) - Literature-mined database of tumor suppressor genes/proto-oncogenes (v42, December 2021)
-  * [Genomics England PanelApp](https://panelapp.genomicsengland.co.uk) - cancer phenotype panels as of February 2nd 2022
+  * [CancerMine](http://bionlp.bcgsc.ca/cancermine/) - Literature-mined database of tumor suppressor genes/proto-oncogenes (v50, March 2023)
+  * [Genomics England PanelApp](https://panelapp.genomicsengland.co.uk) - cancer phenotype panels as of February 2nd 2024
 
 
 ### Phenotype ontologies
-  * [UMLS/MedGen](https://www.ncbi.nlm.nih.gov/medgen/)
-  * [Disease Ontology](https://disease-ontology.org/) - January 30th 2021
-  * [Experimental Factor Ontology](https://github.com/EBISPOT/efo) - v3.38.0
+  * [UMLS/MedGen](https://www.ncbi.nlm.nih.gov/medgen/) - February 2024
+  * [Disease Ontology](https://disease-ontology.org/) - December 2023
+  * [Experimental Factor Ontology](https://github.com/EBISPOT/efo) - v3.62.0