knitr::opts_chunk$set( collapse = TRUE, echo = TRUE, message = FALSE, error = FALSE, comment = "#>", fig.path = "man/figures/" )
The FacileData
package was written to facilitate easier analysis of large,
multi-assay high-throughput genomics datasets. To this end, the FacileData
package provides two things:
FacileDataSet
provides efficient storage and retrieval of arbitrarily large high-throughput
genomics datasets. For example, a single FacileDataSet
can be used to store
all of the RNA-seq, microarray, RPPA, etc. data from the
The Cancer Genome Atlas. This singular FacileDataSet
allows
analysts easy access to arbitrary subsets of these data without having to
load all of it into memory.The FacileData suite of packages is only available from github from now. You
will want to install three FacileData*
packages to appreciate the its utility:
# install.packages("devtools") devtools::install_github("facilebio/FacileData")
As a teaser, we'll show how to plot HER2 copy number vs expression across the
TCGA bladder and breast indications ("BLCA" and "BRCA") using a FacileDataSet
.
library(ggplot2) library(FacileData) library(FacileTCGADataSet) tcga <- FacileTCGADataSet() features <- filter_features(tcga, name == "ERBB2") fdat <- tcga |> filter_samples(indication %in% c("BLCA", "BRCA")) |> with_assay_data(features, assay_name = "rnaseq", normalized = TRUE) |> with_assay_data(features, assay_name = "cnv_score") |> with_sample_covariates(c("indication", "sex")) ggplot(fdat, aes(cnv_score_ERBB2, ERBB2, color = sex)) + geom_point() + facet_wrap(~ indication)
Let's compare how you might do the same using data stored in a
SummarizedExperiment
named se.tcga
that stores RNA-seq (raw and normalized)
and copy number data.
# load / get `se.all` from somewhere fidx <- which(mcols(se.all)$name == "ERBB2") se <- se.all[, se.all$indication %in% c("BLCA", "BRCA")] sdat <- data.frame( ERBB2 = assay(se, "rnaseq_norm")[fidx,], cnv_score_ERBB2 = assay(se, "cnv_score")[fidx,], sex = se$sex, indication = se$indication) ggplot(fdat, aes(cnv_score_ERBB2, ERBB2, color=sex)) + geom_point() + facet_wrap(~ indication)
TODO: Show same analysis using MultiAssayEperiment
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