The goal of SkeletalVis is to enable the search and visualisation of uniformly processed skeletal transcriptomic datasets. It provides tools to identify datasets in which genes of interest are differentially expressed and to discover datasets with similar gene expression profiles to a given query.
It additional allow exploration of the OATargets database and prioritised genes for causing an osteoarthritis damage phenotype in animal models.
You can install the development version of SkeletalVis from GitHub with:
# install.packages("pak")
pak::pak("soulj/SkeletalVis")This is a basic example which shows how to search for a gene of interest across the SkeletalVis data. See the vignette for a full tutorial of SkeletalVis.
# Load the library
library(SkeletalVis)
# Set up the database
skeletalvis <- load_skeletalvis()
#> All files are already present in /home/njs289/.local/share/R/SkeletalVis
# Get the differential expression of the gene SOX9 across the database
gene_results <- get_gene_fold_changes(skeletalvis, "SOX9", return_fdr = TRUE)
head(gene_results)
#> # A tibble: 6 × 16
#> datasetID log2FoldChange FDR Gene accession comparisonsText Description
#> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 E-GEOD-6… 7.15 0 SOX9 E-GEOD-6… SOX9vseGFP SOX9 overe…
#> 2 GSE15511… 3.11 0 SOX9 GSE155118 Sox5_6_9_OEvsc… Primary ch…
#> 3 E-GEOD-5… -1.28 2.25e-195 SOX9 E-GEOD-5… Day18vsDay2 Temporal g…
#> 4 GSE11026… 3.45 2.28e-151 SOX9 GSE11026… YAP KO_MSCvsWT… YAP1 and T…
#> 5 GSE10447… -3.26 1.41e-117 SOX9 GSE104473 Mandibular Dis… Mouse mand…
#> 6 GSE12516… 3.18 8.58e-112 SOX9 GSE125167 PLZF_10_days_d… PLZF knock…
#> # ℹ 9 more variables: PMID <chr>, Species <chr>, Tissue <chr>, ExpType <chr>,
#> # Perturbation <chr>, Effect <chr>, Type <chr>, foldChangeOnly <lgl>,
#> # platform <chr>There are also several built in plotting functions:
# Plot the log2fold change against the FDR for SOX9 across the datasets
volcano_plot(gene_results, number_points = 3)