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Table 1 Number of Features in Simulations

From: MOSCATO: a supervised approach for analyzing multi-Omic single-Cell data

Latent Variable

# Features

H

15

G

10

G′

15

Noise in \(\mathbf {\mathcal {G}}\)

1400

S

20

X

15

X′

20

Noise in \(\mathbf {\mathcal {X}}\)

1500

  1. The table summarizes the number of features within each latent variable used in the simulations. These latent variables are displayed in Fig. 7. H describes the subset of features within \(\boldsymbol{\mathcal {G}}\) that relate to the outcome but not any features within \(\boldsymbol{\mathcal {X}}\), G describes the subset of features within \(\boldsymbol{\mathcal {G}}\) belonging to the network, and G′ describes the subset of features within \(\boldsymbol{\mathcal {G}}\) related to some features within \(\boldsymbol{\mathcal {X}}\) but not the outcome. S, X, and X′ describe similar subsets of features within \(\boldsymbol{\mathcal {X}}\)
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BMC Genomics

ISSN: 1471-2164

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