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SmartSVA: Fast and Robust Surrogate Variable Analysis
Introduces a fast and efficient Surrogate Variable Analysis algorithm that captures variation of unknown sources (batch effects) for high-dimensional data sets. The algorithm is built on the 'irwsva.build' function of the 'sva' package and proposes a revision on it that achieves an order of magnitude faster running time while trading no accuracy loss in return.
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Package details |
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| Author | Jun Chen <Chen.Jun2@mayo.edu>, Ehsan Behnam <behnamgh@usc.edu> |
| Maintainer | Jun Chen <Chen.Jun2@mayo.edu> |
| License | GPL-3 |
| Version | 0.1.3 |
| Package repository | View on CRAN |
| Installation |
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