cmap_rank | R Documentation |
CMap2 (Version build02) contains GESs for 1,309 drugs and eight cell lines that
were generated with Affymetrix Gene Chips as expression platform. In some cases
this includes drug treatments at different concentrations and time points. For
consistency, the CMap2 data was reduced to drug treatments with concentrations
and time points that are comparable to those used for the LINCS data. CMap2 data
can be downloaded from GEO or its project site either in raw format or as rank
transformed matrix. The ranks are based on DEG analyses of drug treatments
(drug vs. no-drug) where the resulting Z-scores were used to generate the
rank matrix. The latter was used here and is referred to as rankMatrix. The
Affymetrix probe set identifiers stored in the row name slot of this matrix
were translated into gene identifies. To obtain a matrix with unique gene
identifiers, the ranks for genes represented by more than one probe set were
averaged and then re-ranked accordingly. This final gene level rank matrix,
referred to as cmap_rank
, contains rank profiles for 12,403 genes from
1,309 compound treatments in up to 5 cells corresponding to a total of
3,587 treatment signatures. This matrix can be used for all GESS methods in
the signatureSearch package that are compatible with rank data, such as the
gess_cmap
method.
The cmap_rank
data can be downloaded from Bioconductor’s ExperimentHub as
HDF5 file. Since CMap2 is much smaller than LINCS, it can be imported in its
entirety into a SummarizedExperiment object without excessive memory requirements
as shown in the Examples section.
The loaded cmap_rank
data object is generated from the rankMatrix
downloaded from the CMap project site.
For documentation and code of generating the cmap_rank databases from sources,
please refer to the vignette of this package by running
browseVignettes("signatureSearchData")
in R.
CMap project site: https://portals.broadinstitute.org/cmap
library(ExperimentHub)
# eh <- ExperimentHub()
# query(eh, c("signatureSearchData", "cmap_rank"))
# cmap_rank_path <- eh[["EH3225"]]
# rhdf5::h5ls(cmap_rank_path)
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