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N-of-1-pathways

Introduction

Many methods can find deregulated pathways for studying the genetic variations between two groups of patients. Traditionally, this kind of study first unveil the deregulated genes between the two conditions, then enrich them into pathways or mechanisms for interpreting the results. However those techniques require many patients/samples for each condition, in order to reach sufficient statistical power.
The main issue is that these methods miss the personal deregulation of each patient, in order to find a global/common signal across patients. Therefore, when a drug is designed to treat those patients, it is based on common deregulation, and may not be appropriate for specific patients genetic backgrounds.

Method

N-of-1-pathways [1] is a framework we developed for unveiling deregulated gene sets with as few as two paired samples. It contains different models for scoring the pathways, the most straightforward being a "Wilcoxon signed-rank test".

Results

Different papers were published using this framework [1-3] in different conditions: normal vs tumoral samples [1], before and after knockdown of a gene [2], before and after exposure to virus [3]. Arguably it could also be applied to before vs after treatment or other type of conditions.
The papers showed that the patients were splitting automatically according to the N-of-1-pathways scores, even with complex phenotypes such as survival or response to treatment.
We also proposed a Star plot representation for individual deregulation.

References

[1] "N-of-1-pathways" unveils personal deregulated mechanisms from a single pair of RNA-seq samples: towards precision medicine, Journal of the American Medical Informatics (JAMIA), vol.21, issue 6, November 2014 (PDF)
[2] Concordance of deregulated mechanisms unveiled in underpowered experiments: PTBP1 knockdown case study, BMC Medical Genomics, 2014 (PDF)
[3] Concordance between ex vivo PBMC and in vivo human infections confirmed by N-of-1-pathways analysis of single-subject transcriptome, under review for JBI

Tools

Source codes/executables in Java and R are available here.