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Fig 1.

Illustration of topic modeling on EHRs using NMF.

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Fig 2.

Word clouds for six topics.

The size of the words (phecode) in each cloud indicates the weights of the phenotypes on the topic. Phenotypes with larger-sized words have greater influence on the topic compared to phenotypes with smaller-sized words. For each word cloud, we listed the top 60 words.

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Fig 3.

Topic distribution in the cohort.

To visualize the prevalence of each topic in the cohort, we assigned an individual to the topic with the maximum score.

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Fig 4.

t-SNE plot of visualizing the patient clusters in a projected 2D metric map (The perplexity was set to 30).

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Table 1.

Pearson correlation coefficient testing between LPA variant for each topic.

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Table 2.

Logistic regression analysis between LPA variant for each topic.

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Table 2 Expand

Fig 5.

PheWAS results of rs10455872 on 12,759 individuals adjusted by sex and age.

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