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Fig. 1 | BMC Genomics

Fig. 1

From: Identifying critical state of complex diseases by single-sample Kullback–Leibler divergence

Fig. 1

The outline for detecting the early-warning signal of a pre-disease state based on sKLD. a The progression of complex diseases is modeled as three states, including two stable states, i.e., a normal and a disease state with high stability and resilience, and an unstable pre-disease state with low stability and resilience [5, 9]. As the limit of the normal state, the pre-disease state is a critical state just before the onset of deterioration. b Given a number of reference samples that are generally from normal cohort and represent the healthy or relatively healthy individuals, the sKLD score is capable to quantitatively evaluate the difference between two distributions of each gene, i.e., the background distribution that generated from a set of reference samples, and a perturbed distribution yielded from the single case sample. The detailed procedure and description of deriving the two distributions are presented in Methods section. c During the progression of a complex disease, the pre-disease state is indicated by the significant change of sKLD, i.e., the sKLD changes gradually when the system is in the normal state, while it increases abruptly when the system approaches the tipping point

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