simdataISVA: Simulated data for ISVA
In isva: Independent Surrogate Variable Analysis
Description
Usage
Format
References
Description
A synthetic data set of 750 features and 50 samples with a binary phenotype
and two confounding factors. Relative effect size of confounding
factors (CFs) to that of phenotype of interest is 2. For further details please
see reference.
Usage
1
Format
This synthetic data set is a list object containing the following
elements: (i) data is the data matrix (750 features, 50 samples),
(ii) pheno is a binary phenotype vector, (iii) factors is a list of
length two containing the two binary confounding factors, (iv) deg is
the index vector of those truly differentially "expressed" features, (v)
degL is a list of index vectors for features truly differentially
altered (first element,degL[[1]]=deg) and those features affected by CFs (2nd and
3rd elements).
References
Independent Surrogate Variable Analysis to deconvolve confounding factors in large-scale microarray profiling studies. Teschendorff AE, Zhuang JJ, Widschwendter M. Bioinformatics. 2011 Jun 1;27(11):1496-505.
isva documentation built on May 1, 2019, 6:49 p.m.
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Description Usage Format References
Description
A synthetic data set of 750 features and 50 samples with a binary phenotype and two confounding factors. Relative effect size of confounding factors (CFs) to that of phenotype of interest is 2. For further details please see reference.
Usage
1 |
Format
This synthetic data set is a list object containing the following elements: (i) data is the data matrix (750 features, 50 samples), (ii) pheno is a binary phenotype vector, (iii) factors is a list of length two containing the two binary confounding factors, (iv) deg is the index vector of those truly differentially "expressed" features, (v) degL is a list of index vectors for features truly differentially altered (first element,degL[[1]]=deg) and those features affected by CFs (2nd and 3rd elements).
References
Independent Surrogate Variable Analysis to deconvolve confounding factors in large-scale microarray profiling studies. Teschendorff AE, Zhuang JJ, Widschwendter M. Bioinformatics. 2011 Jun 1;27(11):1496-505.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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