hacksig: hacksig: A Tidy Framework to Hack Gene Expression Signatures

In hacksig: A Tidy Framework to Hack Gene Expression Signatures

hacksig: A Tidy Framework to Hack Gene Expression Signatures

Description

The hacksig package has been designed for the purpose of simplifying the way in which gene expression signatures scores are computed. It is a manually curated collection of gene expression signatures found in literature and makes use of three different single sample score calculation methods. Moreover, parallel computation is supported through the future framework.

Get gene signatures scores in different ways

The main function of the package is hack_sig() and it can be used to:

• obtain single sample scores with one of three methods (z-score, ssGSEA, singscore) for a custom list of gene signatures;

• obtain single sample scores for a number of manually curated gene signatures either with the original publication method or with one of the three single sample methods.

Once single sample scores are obtained, you can assign your samples into signature classes with hack_class().

In addition, other more complex methods are implemented through:

• hack_cinsarc(), for the CINSARC classification;

• hack_estimate(), for the ESTIMATE method;

• hack_immunophenoscore(), for the Immunophenoscore.

Information about implemented signatures can be obtained with get_sig_info().

Check if gene signatures are applicable to your data

Sometimes your gene expression matrix can miss some genes due to some prior filtering procedure. The function check_sig() can be used to check how many genes your expression matrix contain for every input signature.

Author(s)

Andrea Carenzo, Loris De Cecco, Federico Pistore

See Also

Useful links:

• https://github.com/Acare/hacksig

• Report bugs at https://github.com/Acare/hacksig/issues

hacksig documentation built on March 18, 2022, 6:44 p.m.