Merge pull request #243 from sigven/pd_fixes

Documentation update
sigven · Jun 26, 2024 · 49398ab · 49398ab
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diff --git a/README.md b/README.md
@@ -2,110 +2,89 @@
 
 [![Conda install ver](https://anaconda.org/pcgr/pcgr/badges/version.svg)](https://anaconda.org/pcgr/pcgr)
 [![Conda install lrd](https://anaconda.org/pcgr/pcgr/badges/latest_release_date.svg)](https://anaconda.org/pcgr/pcgr)
-[<img src="https://img.shields.io/badge/dockerhub-images-important.svg?logo=LOGO">](https://hub.docker.com/repository/docker/sigven/pcgr/)
+[<img src="https://img.shields.io/badge/dockerhub-images-important.svg?logo=LOGO">](https://hub.docker.com/r/sigven/pcgr)
 
 ### Overview
 
-The Personal Cancer Genome Reporter (PCGR) is a stand-alone software package for translation of individual tumor genomes for precision cancer medicine.
+The Personal Cancer Genome Reporter (PCGR) is a stand-alone software package for functional annotation and translation of individual tumor genomes for precision cancer medicine. It interprets primarily somatic SNVs/InDels and copy number aberrations, and has additional support for interpretation of bulk RNA-seq expression data. The software classifies variants both with respect to _oncogenicity_, and _actionability_. Interactive HTML output reports allow the user to interrogate the clinical impact of the molecular findings in an individual tumor.
 
-PCGR interprets primarily somatic SNVs/InDels and copy number aberrations, and has additional support for interpretation of bulk RNA-seq expression data. The software produces interactive HTML reports intended for clinical interpretation. PCGR can perform multiple types of analyses, including:
+- Variant classification
+  - according to *oncogenicity*: evaluating the oncogenic potential of somatic DNA aberrations (VICC/CGC/ClinGen guidelines)
+  - according to *actionability*: mapping the therapeutic, diagnostic, and prognostic implications of somatic DNA aberrations (ACMG/AMP guidelines)
+- Tumor mutational burden (TMB) estimation
+- Mutational signature analysis
+- Microsatellite instability (MSI) classification
+- RNA expression analysis - outlier detection, similarity analysis, and immune contexture profiling
 
--   Variant classification
-    -   according to *oncogenicity*: evaluating the oncogenic potential of somatic DNA aberrations (VICC/CGC/ClinGen guidelines)
-    -   according to *actionability*: mapping the therapeutic, diagnostic, and prognostic implications of somatic DNA aberrations (ACMG/AMP guidelines)
--   Tumor mutational burden (TMB) estimation
--   Mutational signature analysis
--   Microsatellite instability (MSI) classification
--   RNA expression analysis - outlier detection, similarity analysis, and immune contexture profiling
+PCGR supports both of the most recent human genome assemblies (GRCh37/GRCh38), and accepts variant calls from both tumor-control and tumor-only sequencing assays. Much of the functionality is intended for whole-exome/whole-genome sequencing assays, but you can also apply PCGR to output from targeted sequencing panels. If you are interested in the interrogation of germline variants and their relation to cancer predisposition, we recommend trying the accompanying tool [Cancer Predisposition Sequencing Reporter (CPSR)](https://github.com/sigven/cpsr).
 
-PCGR supports both of the most recent human genome assemblies (grch37/grch38), and accepts variant calls from both tumor-control and tumor-only sequencing assays. Much of the functionality is intended for whole-exome/whole-genome sequencing assays, but you can also apply PCGR to output from targeted sequencing panels. If you are interested in the interrogation of germline variants and their relation to cancer predisposition, we recommend trying the accompanying tool [Cancer Predisposition Sequencing Reporter (CPSR)](https://github.com/sigven/cpsr).
+Example screenshots from the [quarto](https://quarto.org)-based cancer genome report by PCGR:
 
 ![PCGR screenshot 1](pcgrr/pkgdown/assets/img/sc2.png)
 ![PCGR screenshot 2](pcgrr/pkgdown/assets/img/sc1.png)
 ![PCGR screenshot 3](pcgrr/pkgdown/assets/img/sc3.png)
 
-### News
+PCGR originates from the [Norwegian Cancer Genomics Consortium (NCGC)](http://cancergenomics.no), at the [Institute for Cancer Research, Oslo University Hospital, Norway](http://radium.no).
 
--   *June 2024*: **2.0.0 release**
-    - Massive reference data bundle upgrade, new report layout, oncogenicity classification++
-    - Details at [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html)
+### Top News
 
--   *February 2023*: **1.3.0 release**
-    - Details at [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html)
-    - proritize protein-coding BIOTYPE csq ([pr201](https://github.com/sigven/pcgr/pull/201))
-    - expose `--pcgrr_conda` option to flexibly activate pcgrr env via a non-default pcgrr name
-    - `cpsr_validate_input.py`: refactor for efficient custom gene egrep
+- *June 2024*: **2.0.0 release**
+  - Details in [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html)
+  - Massive reference data bundle upgrade, new report layout, oncogenicity classification++
+  - Support for Singularity/Apptainer
+  - Major data/software updates:
+    - Ensembl VEP `v112`
+    - ClinVar (2024-06)
+    - CIViC (2024-06-21)
+    - GENCODE `v46/v19` (GRCh38/GRCh37)
+    - CancerMine `v50` (2023-03)
+    - UniProt KB `v2024_03`
 
--   *November 2022*: **1.2.0 release**
-    -    Keep only autosomal, X, Y, M/MT chromosomes
-    -    Import bcftools as dependency
+- *February 2023*: **1.3.0 release**
+  - Details in [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html)
+  - prioritize protein-coding BIOTYPE csq ([pr201](https://github.com/sigven/pcgr/pull/201))
+  - expose `--pcgrr_conda` option to flexibly activate pcgrr env via a non-default pcgrr name
+  - `cpsr_validate_input.py`: refactor for efficient custom gene egrep
 
+- *November 2022*: **1.2.0 release**
+  -    Keep only autosomal, X, Y, M/MT chromosomes
+  -    Import bcftools as dependency
 
--   *October 2022*: **1.1.0 release**
-
-    -   Remove Docker command wrappers
-    -   Deprecate `--no_docker` and `--docker_uid` CLI options
-    -   Merged PRs [pr192](https://github.com/sigven/pcgr/pull/192), [pr193](https://github.com/sigven/pcgr/pull/193), [pr194](https://github.com/sigven/pcgr/pull/194), [pr196](https://github.com/sigven/pcgr/pull/196).
-    -   See [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html) for a few more changes.
-
--   *May 2022*: **1.0.3 release**
-
-    -   Merged [PR #191](https://github.com/sigven/pcgr/pull/191)
-
--   *March 2022*: **1.0.2 release**
-
-    -   Fixed [CPSR issue #44](https://github.com/sigven/cpsr/issues/44)
-
--   *March 2022*: **1.0.1 release**
-
-    -   Fixed bug for huge input sets that cause JSON output crash
-        -   huge input variant sets (WGS) are now reduced prior to reporting with R, i.e. exclusion of intronic and intergenic variants, as well as upstream/downstream gene variants ([#178](https://github.com/sigven/pcgr/issues/178)).
-    -   Fixed bug for cases where mutational signature analysis reports \> 18 different aetiologies after fitting ([#187](https://github.com/sigven/pcgr/issues/187)).
-    -   [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html)
-
--   *February 2022*: **1.0.0 release**
+### Example reports
 
-    -   Complete restructure of Python and R components. Installation now relies on two separate [conda](https://docs.conda.io/en/latest/) packages, `pcgr` (Python component) and `pcgrr` (R component). Direct Docker support remains, with the Dockerfile simplified to rely exclusively on the installation of the above Conda packages. Significant contributon by the great [\@pdiakumis](https://github.com/pdiakumis)
-    -   VCF validation step removed. Feedback from users suggested that Ensembl's `vcf-validator` was often too stringent so its use has been deprecated. The `--no_vcf_validate` option remains for backwards compatibility.
-    -   New documentation site (<https://sigven.github.io/pcgr>)
-    -   Data bundle updates (CIViC, ClinVar, Open Targets Platform, CancerMine, UniProt KB, Pfam)
-    -   [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11401431.svg)](https://doi.org/10.5281/zenodo.11401431)
 
--   *June 30th 2021*: **0.9.2 release**
+### Why use PCGR?
 
-    -   Data bundle updates (CIViC, ClinVar, CancerMine, UniProt KB, PFAM)
-    -   Software upgrades: VEP (104), R v4.1/BioConductor 3.13
-    -   **NEW**: TOML configuration removed - all options to PCGR are now command-line based
-    -   **NEW**: Feed PCGR with a [CPSR report](https://github.com/sigven/cpsr) to view key germline findings in the tumor report
-    -   [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html)
-    -   Planned for next release: Support for analysis of RNA fusions
+The great complexity of acquired mutations in individual tumor genomes poses a severe challenge for clinical interpretation. PCGR aims to be a comprehensive reporting platform that can
 
--   *November 30th 2020*: **0.9.1 release**
+- systematically interrogate tumor-specific variants in the context of known therapeutic, diagnostic, and prognostic biomarkers
+- highlight genomic aberrations with likely oncogenic potential
+- provide a structured and concise summary of the most relevant findings
+- present the results in a format accessible to clinical experts
 
-    -   Data bundle updates (CIViC, ClinVar, CancerMine, UniProt KB)
-    -   [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html)
+PCGR integrates a [comprehensive set of knowledge resources](articles/annotation_resources.html) related to tumor biology and therapeutic biomarkers, both at the gene, and at the level of individual variants. The software generates a comprehensive molecular interpretation report that supports the translation of individual cancer genomes towards molecularly guided treatment strategies.
 
-### Example reports
+### Getting started
 
-[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11401431.svg)](https://doi.org/10.5281/zenodo.11401431)
+- [Installation instructions](https://sigven.github.io/pcgr/articles/installation.html)
+- [Run through an example](https://sigven.github.io/pcgr/articles/running.html#example-run)
+- Learn more about:
 
-### Getting started
+    1) Details regarding [PCGR input files](https://sigven.github.io/pcgr/articles/input.html), and how they should be formatted
+    2) Configuration of [key settings](https://sigven.github.io/pcgr/articles/running.html)
+    3) The types and contents of [PCGR output files](https://sigven.github.io/pcgr/articles/output.html)
+    4) [Variant classifications implemented in PCGR](https://sigven.github.io/pcgr/articles/variant_classification.html)
+    5) [Primary tumor sites used in PCGR](https://sigven.github.io/pcgr/articles/primary_tumor_sites.html)
+    6) The list of [gene and variant annotation resources](https://sigven.github.io/pcgr/articles/annotation_resources.html) used in PCGR annotation
 
--   [Installation instructions](https://sigven.github.io/pcgr/articles/installation.html)
--   [Run through an example](https://sigven.github.io/pcgr/articles/running.html#example-run)
--   Learn more about
-    -   Details regarding [PCGR input files](https://sigven.github.io/pcgr/articles/input.html), and how they should be formatted
-    -   How to configure [key settings](https://sigven.github.io/pcgr/articles/running.html)
-    -   The types and contents of [PCGR output files](https://sigven.github.io/pcgr/articles/output.html)
-    -   The [variant classifications](https://sigven.github.io/pcgr/articles/variant_classification.html) implemented in PCGR
-    -   The list of [gene and variant annotation resources](https://sigven.github.io/pcgr/articles/annotation_resources.html) used in PCGR annotation
--   [Frequenty asked questions (FAQ)](https://sigven.github.io/pcgr/articles/faq.html)
+- [Frequently asked questions (FAQ)](https://sigven.github.io/pcgr/articles/faq.html)
 
 ### Citation
 
-If you use PCGR, please cite the publication:
+If you use PCGR, please cite our publication:
 
-Sigve Nakken, Ghislain Fournous, Daniel Vodák, Lars Birger Aaasheim, Ola Myklebost, and Eivind Hovig. **Personal Cancer Genome Reporter: variant interpretation report for precision oncology** (2017). *Bioinformatics*. 34(10):1778--1780. [doi:10.1093/bioinformatics/btx817](https://doi.org/10.1093/bioinformatics/btx817)
+Sigve Nakken, Ghislain Fournous, Daniel Vodák, Lars Birger Aaasheim, Ola Myklebost, and Eivind Hovig. **Personal Cancer Genome Reporter: variant interpretation report for precision oncology** (2017). *Bioinformatics*. 34(10):1778--1780. [doi.org/10.1093/bioinformatics/btx817](https://doi.org/10.1093/bioinformatics/btx817)
 
 ## Contact
 

diff --git a/pcgrr/R/acmg.R b/pcgrr/R/acmg.R
@@ -142,7 +142,7 @@ assign_acmg_tiers <- function(
           as.integer(.data$ACMG_TIER_OTHER_VARS)
         )) |>
         dplyr::mutate(ACMG_AMP_TIER = dplyr::if_else(
-          is.na(ACMG_AMP_TIER) &
+          is.na(.data$ACMG_AMP_TIER) &
             .data$CODING_STATUS == "noncoding",
           as.integer(5),
           as.integer(.data$ACMG_AMP_TIER)

diff --git a/pcgrr/R/utils.R b/pcgrr/R/utils.R
@@ -984,7 +984,7 @@ get_genome_obj <- function(genome) {
     stop(glue::glue(
       "{pkg} is not installed on your system.\n",
       "Please install with:\n'BiocManager::install(\"{pkg}\")'\n",
-      "(or use 'mamba install -c bioconda bioconductor-bsgenome.hsapiens.ucsc.hgXX' ",
+      "(or use 'conda install -c bioconda bioconductor-bsgenome.hsapiens.ucsc.hgXX' ",
       "if inside a conda environment)."
     ))
   }