Functionalities of OmicSignature

Vanessa Mengze Li

10/17/2024

devtools::load_all(".")

Read an OmicSignature object from a json file

Alternatively, you can read and write the object in .rds format as any other R objects.

OmS <- readJson(file.path(system.file("extdata", package = "OmicSignature"), "Myc_reduce_mice_liver_24m_OmS.json"))
#>   [Success] OmicSignature object Myc_reduce_mice_liver_24m created.

Write an OmicSignature object into a json file 

writeJson(OmS, "Myc_reduce_mice_liver_24m_OmS.json")
OmS
#> Signature Object: 
#>   Metadata: 
#>     adj_p_cutoff = 0.05 
#>     assay_type = transcriptomics 
#>     covariates = none 
#>     description = mice MYC reduced expression 
#>     direction_type = bi-directional 
#>     keywords = Myc, KO, longevity 
#>     organism = Mus Musculus 
#>     others = C57BL/6 
#>     phenotype = Myc_reduce 
#>     platform = GPL6246 
#>     PMID = 25619689 
#>     sample_type = liver 
#>     score_cutoff = 5 
#>     signature_name = Myc_reduce_mice_liver_24m 
#>     year = 2015 
#>   Metadata user defined fields: 
#>     animal_strain = C57BL/6 
#>   Signature: 
#>     Length (15)
#>     Class (character)
#>     Mode (character)
#>   Differential Expression Data: 
#>     884 x 9

Extract new signatures from the OmicSignature object

We can use new criterias to extract new signatures conveniently from the OmicSignature Object, if it has difexp matrix included.
For example, extract all features with a t-score with absolute value higher than 5 and adj_p smaller than 0.01:

OmS$extractSignature("abs(score) > 5; adj_p < 0.01")
#>   probe_id       feature_name   score direction
#> 1 10349648 ENSMUSG00000004552  14.762         +
#> 2 10345762 ENSMUSG00000026072 -13.543         -
#> 3 10353192 ENSMUSG00000025932  10.487         +
#> 4 10355259 ENSMUSG00000061816 -10.315         -
#> 5 10351477 ENSMUSG00000102418   8.818         +