minor fixes

R/utils.R

@@ -71,7 +71,7 @@ get_insilico_prediction_statistics <- function(cpg_calls) {
       "DBNSFP_CLINPRED",
       "DBNSFP_MUTFORMER",
       "DBNSFP_ALPHA_MISSENSE",
-      "DBNSFP_POLYPHEN_HVAR",
+      "DBNSFP_POLYPHEN2_HVAR",
       "DBNSFP_FATHMM_XF",
       "DBNSFP_M_CAP",
       "DBNSFP_LIST_S2",

data-raw/data-raw.R

@@ -22,6 +22,7 @@ col_format_output[['html_tier']] <-
     "MUTATION_HOTSPOT",
     "RMSK_HIT",
     "PREDICTED_EFFECT",
+    "SPLICE_EFFECT",
     "miRNA_TARGET_HIT",
     "miRNA_TARGET_HIT_PREDICTION",
     "TF_BINDING_SITE_VARIANT",
@@ -69,6 +70,7 @@ col_format_output[['html_sf']] <-
     "ENSEMBL_TRANSCRIPT_ID",
     "CDS_CHANGE",
     "PREDICTED_EFFECT",
+    "SPLICE_EFFECT",
     "LOSS_OF_FUNCTION",
     "LOF_FILTER",
     "DBSNP_RSID",
@@ -104,6 +106,7 @@ col_format_output[['html_pgx']] <-
     "ENSEMBL_TRANSCRIPT_ID",
     "CDS_CHANGE",
     "PREDICTED_EFFECT",
+    "SPLICE_EFFECT",
     "LOSS_OF_FUNCTION",
     "LOF_FILTER",
     "DBSNP_RSID",
@@ -193,6 +196,7 @@ col_format_output[['tsv']] <-
     "MUTATION_HOTSPOT",
     "RMSK_HIT",
     "EFFECT_PREDICTIONS",
+    "SPLICE_EFFECT",
     "LOSS_OF_FUNCTION",
     "LOF_FILTER",
     "NULL_VARIANT",
@@ -313,6 +317,7 @@ col_format_output[['xlsx_classification']] <-
     "CDS_CHANGE",
     "MUTATION_HOTSPOT",
     "EFFECT_PREDICTIONS",
+    "SPLICE_EFFECT",
     "LOSS_OF_FUNCTION",
     "LOF_FILTER",
     "NULL_VARIANT",
@@ -359,6 +364,7 @@ col_format_output[['xlsx_secondary']] <-
     "CODING_STATUS",
     "MUTATION_HOTSPOT",
     "EFFECT_PREDICTIONS",
+    "SPLICE_EFFECT",
     "LOSS_OF_FUNCTION",
     "LOF_FILTER",
     "NULL_VARIANT",
@@ -395,6 +401,7 @@ col_format_output[['xlsx_pgx']] <-
     "CODING_STATUS",
     "MUTATION_HOTSPOT",
     "EFFECT_PREDICTIONS",
+    "SPLICE_EFFECT",
     "LOSS_OF_FUNCTION",
     "LOF_FILTER",
     "NULL_VARIANT",

inst/templates/quarto/cpsr_documentation.qmd

@@ -101,6 +101,29 @@ The ACMG/AMP criteria listed in @nte-table-criteria form the basis for the *CPSR
 
 :::
 
+::: {.callout-note title="Variant loss-of-function annotation" collapse="true" #nte-lof-annotation}
+
+For SNVs and InDels, CPSR considers the following consequence types as candidates for loss-of-function variation:
+
+  * Stop gains - [SO:0001587](http://www.sequenceontology.org/miso/current_svn/term/SO:0001587)
+ * Frameshift variants - [SO:0001589](http://www.sequenceontology.org/miso/current_svn/term/SO:0001589)
+ * Splice-site disruptions (2bp donor/acceptor site) - [SO:0001574](http://www.sequenceontology.org/miso/current_svn/term/SO:0001574),
+ [SO:0001575](http://www.sequenceontology.org/miso/current_svn/term/SO:0001575)
+ * Start losses - [SO:0001574](http://www.sequenceontology.org/miso/current_svn/term/SO:0002012)
+
+If variants of other consequence types (e.g. synonymous variants, or splice site variants beyond the canonical 2bp site) are found to affect splicing, specifically through records in [MutSpliceDB](https://brb.nci.nih.gov/splicing/), these are also marked as loss-of-function candidates.
+
+A collection of filters is next applied, which can potentialy remove the loss-of-function property for candidates identified above:
+
+ * Frameshifts/stop gains within the last 5% of the CDS
+ * Splice site variants that are not predicted to affect a donor site (GC -> GT)
+ * Variants where [MaxEntScan](https://pubmed.ncbi.nlm.nih.gov/15285897/) does not predict an effect on splicing
+    - Annotations in MutSpliceDB will have precedence if any conflicting evidence with MaxEntScan output is found
+
+If a variant is filtered as non-LoF through any of these criteria, this will be evident from the `LOF_FILTER` variable (found in the interactive tables of the HTML report as well as the TSV/Excel output).
+
+:::
+
 ::: {.callout-note title="Implemented evidence criteria - ACMG/AMP" collapse="true" #nte-table-criteria}
 
 In the table below, a detailed description of all evidence criteria that are currently used for variant classification in CPSR (green elements indicate criteria that contribute with a benign effect, red elements contribute with a pathogenic effect):<br><br>

vignettes/CHANGELOG.Rmd

@@ -3,24 +3,24 @@ title: "Changelog"
 output: rmarkdown::html_document
 ---
 
-## v2.1.3
+## v2.2.0
 
-- Date: **2025-02-24**
+- Date: **2025-03-XX**
 - Major data updates
   - ClinVar (2025-02)
   - dbNSFP (v5.0)
-  - CIViC (2025-02-08)
+  - CIViC (2025-02-27)
   - GENCODE v47 (VEP v113)
   - PanelApp (2025-02)
   - UniProt KB (2025-01)
   - Cancer Gene Census (v101)
 - Added more cancer susceptibility genes in panel zero (ATG12, BIK, CHD1L, CMTR2, 
 CPAP, HAVCR2, LLGL2, MYO3A, MYO5B, PAH, TTC7A)
 - Added a pharmacogenetic findings option (`--pgx_findings`), which will include pharmacogenetic findings in the HTML report (within the `Genomic biomarkers` section)
-   - For now, this is implemented very simple, not considering star alleles, but merely focusing on pathogenic variants or drug-response related variants in DPYD, TPMT and NUDT15
+   - For now, this is implemented very simple, not considering star alleles, but merely focusing on pathogenic variants or drug-response related variants in DPYD, TPMT, and NUDT15
 - Multiple cosmetic changes to HTML report - e.g. collapsed call-outs
 - Improved the variant classification algorithm
-   - addition of new criterion: disruption of esssential nucleotides (ACMG_PM6)
+   - addition of new criterion: disruption of essential nucleotides (ACMG_PM6)
    - improved matching against pathogenic/benign codons (ClinVar)
 
 ## v2.1.2

vignettes/annotation_resources.Rmd

@@ -10,13 +10,13 @@ output: rmarkdown::html_document
   * [dBNSFP](https://sites.google.com/site/jpopgen/dbNSFP) - database of non-synonymous functional predictions (v5.0, January 2025)
 
 ###  Variant frequency databases
-  * [gnomAD](http://exac.broadinstitute.org/) - germline variant frequencies exome-wide (r4.1, April 2024)
+  * [gnomAD](http://exac.broadinstitute.org/) - germline variant frequencies exome-wide (r2.1.1 (non-cancer subject allele frequencies), r4.1)
   * [dbSNP](http://www.ncbi.nlm.nih.gov/SNP/) - database of short genetic variants (build 156)
   * [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 2025)
-  * [CIViC](https://civicdb.org) - clinical interpretations of variants in cancer (February 8th 2025)
+  * [CIViC](https://civicdb.org) - clinical interpretations of variants in cancer (February 27th 2025)
 
 ### Protein domains/functional features
   * [UniProt/SwissProt KnowledgeBase](http://www.uniprot.org) - resource on protein sequence and functional information (2025_01)
@@ -29,5 +29,5 @@ output: rmarkdown::html_document
 
 ### Phenotype ontologies
   * [UMLS/MedGen](https://www.ncbi.nlm.nih.gov/medgen/) - January 2025
-  * [Disease Ontology](https://disease-ontology.org/) - January 2025
-  * [Experimental Factor Ontology](https://github.com/EBISPOT/efo) - v3.74.0
+  * [Disease Ontology](https://disease-ontology.org/) - February 2025
+  * [Experimental Factor Ontology](https://github.com/EBISPOT/efo) - v3.75.0