Integrated Gene Signal Processing (IGSP)

Integrated gene signal processing (IGSP) is a rare-variant based integrated approach to prioritize risk genes in association sequencing studies. Instead of solely relying on association signals, our IGSP approach integrates this information with gene network and phenotype data to allow optimal detection of putatively bona fide disease association signals of rare variants at the gene level and thus maximize the likelihood of uncovering weak (effect size) but real disease risk genes within a dataset. The design of the method addresses the issue of insufficient statistical power and can significantly improve the identification of disease risk genes with marginal association signals.

 

Citation

Lin et al (2017) Integrated rare variant-based risk gene prioritization in disease case-control sequencing studies. (Submitted)

IGSP webapp

Gene association P-values to upload:

In a text file of tab-delimited format (Ensemble ID/Gene symbol   P-value)    Download an example

PARAMETERS

Method

^[?]Using both network and phenotype features is more powerful in prioritizing risk genes; using network alone provides a better coverage of risk gene prioritization (~18,000 vs. ~9,000 human coding genes).

: Network + Phenotype (Full integration) Network

Risk gene percentage (%)

^[?]Approximate the percentage of risk genes in the submited gene list. The prioritization performance is largely maintained within a reasonable range of its real value.

: 1 2 3 4 5

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References

Guo, T. et al (2015) Histone Modifier Genes Alter Conotruncal Heart Phenotypes in 22q11.2 Deletion Syndrome. Am J Hum Genet, 97, 869-77 (2015).

Sifrim, A. et al (2016) Distinct genetic architectures for syndromic and nonsyndromic congenital heart defects identified by exome sequencing. Nat Genet, 48, 1060-5.