CuBlock

Cross-platform normalization method of gene expression micorarrays
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Updated 6 Apr 2021

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CuBlock is a cross-platform gene expression microarrays normalization method. Microarrays from one platform can be normalized together as shown in the file "example.m". This method is useful when a study includes the analysis of microarrays originating from multiple platforms and standard normalization methods don't apply to reduce the inter-platform batch effect.

More details can be found in the publication: Valentin Junet, Judith Farrés, José M Mas, Xavier Daura, CuBlock: a cross-platform normalization method for gene-expression microarrays, Bioinformatics, 2021;, btab105, https://doi.org/10.1093/bioinformatics/btab105

The input of CuBlock are:
-data: the log2 transform of the microarrays' raw intensisities where the rows are probes and the columns are samples.
-N: the number of time the algorithm is repeated. By default N is set to 30.
-k: the number of probes clusters for the application of k-means to find probes cluster partitions. By default k is set to 5.

Cite As

Valentin Junet (2024). CuBlock (https://www.mathworks.com/matlabcentral/fileexchange/77882-cublock), MATLAB Central File Exchange. Retrieved .

Valentin Junet, Judith Farrés, José M Mas, Xavier Daura, CuBlock: a cross-platform normalization method for gene-expression microarrays, Bioinformatics, 2021;, btab105, https://doi.org/10.1093/bioinformatics/btab105

MATLAB Release Compatibility
Created with R2017a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.9

Addition of remarks in the header of the script "CuBlock"

1.0.8

Reference update

1.0.7

small change in description

1.0.6

Small modifications in the commented text

1.0.5

Comments in "example.m" on the cdf used in the main text

1.0.4

Addition of comments in the file "example.m".

1.0.3

Minor term correction in example.m

1.0.2

Addition of a script with examples

1.0.1

Typos correction

1.0.0