The data from Proceedings of the National Academy of Sciences Dec 2014, 111 (51) E5564-E5573 are available in what looks to be a relatively complete table that includes SNVs, SNPs, as well as copy number variation. This function just loads those data for convenience. It is likely that further filtering is going to be required before use.
get_janeway_alterations()
a tibble
Data from https://www.pnas.org/highwire/filestream/618044/field_highwire_adjunct_files/7/pnas.1419260111.sd08.xlsx. See Proceedings of the National Academy of Sciences Dec 2014, 111 (51) E5564-E5573; DOI: 10.1073/pnas.1419260111.
#> # A tibble: 6 x 24 #> Gene Variant_Classif… Alteration Tumor_allele Reference_allele dbSNP_RS bin #> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> #> 1 PIK3… Missense_Mutati… p.E545D T G rs12191… 0 #> 2 PTEN Copy Number Deleted NA NA NA 0 #> 3 PTEN Copy Number Deleted NA NA NA 0 #> 4 PTEN Copy Number Deleted NA NA NA 0 #> 5 RB1 Copy Number Deleted NA NA NA 0 #> 6 RB1 Copy Number Deleted NA NA NA 0 #> # … with 17 more variables: Score_bin <chr>, Chromosome <chr>, #> # Start_position <dbl>, End_position <dbl>, Coverage <chr>, #> # Allelic_fraction <chr>, Number_of_Probes <chr>, Segment_Mean <chr>, #> # In_Segment <chr>, Pathways <chr>, COSMIC_overlapping_mutations <chr>, #> # COSMIC_total_alterations_in_gene <chr>, UniProt_Region <chr>, #> # Rationale <chr>, `Study ID` <chr>, Clinical_trials <chr>, #> # mutation.assessor <chr>colnames(alts)#> [1] "Gene" "Variant_Classification" #> [3] "Alteration" "Tumor_allele" #> [5] "Reference_allele" "dbSNP_RS" #> [7] "bin" "Score_bin" #> [9] "Chromosome" "Start_position" #> [11] "End_position" "Coverage" #> [13] "Allelic_fraction" "Number_of_Probes" #> [15] "Segment_Mean" "In_Segment" #> [17] "Pathways" "COSMIC_overlapping_mutations" #> [19] "COSMIC_total_alterations_in_gene" "UniProt_Region" #> [21] "Rationale" "Study ID" #> [23] "Clinical_trials" "mutation.assessor"