MOFA: Multi-Omics Factor Analysis (MOFA)
In MOFA: Multi-Omics Factor Analysis (MOFA)
Description
MOFA provides an unsupervised framework for the integration of multi-omics data sets.
Given several data matrices with measurements of multiple ‘omics data
types on the same or on overlapping sets of samples, MOFA infers an
interpretable low-dimensional data representation in terms of (hidden) factors.
These learnt factors represent the driving sources of variation across data modalities,
thus facilitating the identification of cellular states or disease subgroups.
The package contains all function required for training MOFA on a multi-omics data set as well as
for different downstream analyes, such as visualisation of samples in factor space, annotation of factors
to molecular markers or gene sets, outlier identification and imputation of missing values.
Details
Please have a look at the vignette "MOFA" for a in-depth introduction to the package.
MOFA documentation built on Feb. 11, 2021, 2:01 a.m.
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Description
MOFA provides an unsupervised framework for the integration of multi-omics data sets. Given several data matrices with measurements of multiple ‘omics data types on the same or on overlapping sets of samples, MOFA infers an interpretable low-dimensional data representation in terms of (hidden) factors. These learnt factors represent the driving sources of variation across data modalities, thus facilitating the identification of cellular states or disease subgroups.
The package contains all function required for training MOFA on a multi-omics data set as well as for different downstream analyes, such as visualisation of samples in factor space, annotation of factors to molecular markers or gene sets, outlier identification and imputation of missing values.
Details
Please have a look at the vignette "MOFA" for a in-depth introduction to the package.
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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