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A Quick Start of sigminer Package

Shixiang Wang ( wangshx@shanghaitech.edu.cn )

2024-05-11

Assume you have already gotten a catalog matrix (sample-by-component) like below:

library(sigminer)
data("simulated_catalogs")
mat <- t(simulated_catalogs$set1)

mat[1:5, 1:5]
#>          A[C>A]A A[C>A]C A[C>A]G A[C>A]T C[C>A]A
#> Sample_1     911     761      88     744     883
#> Sample_2     195     175      19     174     225
#> Sample_3      95      51      12      55     142
#> Sample_4     131      71      14      77     170
#> Sample_5      33      10       2      14      55

Extract signatures with:

# Here I reduce the values for n_bootstrap and n_nmf_run for reducing the run time.  In practice,
# you should keep default or increase the values for better estimation.  The input data here is
# simulated from 10 mutational signatures
e1 <- bp_extract_signatures(mat, range = 8:12, n_bootstrap = 5, n_nmf_run = 10)

Check which signature number is proper:

bp_show_survey2(e1, highlight = 10)
#> Variables can be used: signature_number, silhouette, sample_cosine_distance, L1_error, L2_error, exposure_positive_correlation, signature_similarity_within_cluster, signature_similarity_across_cluster, silhouette_sample

Get the 10 signatures:

obj <- bp_get_sig_obj(e1, 10)

Show signature profile:

show_sig_profile(obj, mode = "SBS", style = "cosmic")

Show signature activity (a.k.a. exposure) profile:

show_sig_exposure(obj, rm_space = TRUE)

Calculate the similarity to COSMIC reference signatures:

sim <- get_sig_similarity(obj, sig_db = "SBS")
#> -Comparing against COSMIC signatures
#> ------------------------------------
#> --Found Sig1 most similar to SBS12
#>    Aetiology: Unknown [similarity: 0.932]
#> --Found Sig2 most similar to SBS13
#>    Aetiology: Activity of APOBEC family of cytidine deaminases [similarity: 0.97]
#> --Found Sig3 most similar to SBS5
#>    Aetiology: Unknown (clock-like signature) [similarity: 0.95]
#> --Found Sig4 most similar to SBS3
#>    Aetiology: Defective homologous recombination DNA damage repair [similarity: 0.927]
#> --Found Sig5 most similar to SBS8
#>    Aetiology: Unknown [similarity: 0.934]
#> --Found Sig6 most similar to SBS18
#>    Aetiology: Damage by reactive oxygen species [similarity: 0.975]
#> --Found Sig7 most similar to SBS1
#>    Aetiology: Spontaneous deamination of 5-methylcytosine (clock-like signature) [similarity: 0.76]
#> --Found Sig8 most similar to SBS6
#>    Aetiology: Defective DNA mismatch repair [similarity: 0.957]
#> --Found Sig9 most similar to SBS17b
#>    Aetiology: Unknown [similarity: 0.888]
#> --Found Sig10 most similar to SBS2
#>    Aetiology: Activity of APOBEC family of cytidine deaminases [similarity: 0.986]
#> ------------------------------------
#> Return result invisiblely.
if (require(pheatmap)) {
    pheatmap::pheatmap(sim$similarity)
}

QA

If you encounter warnings about future package, please set the following options before running code:

options(future.rng.onMisuse = "ignore", future.globals.maxSize = Inf)

More

Please go to reference list for well organized functions and documentation.

For more about mutational signature and sigminer usage, you can read sigminer-book.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.