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GESE (version 2.0.0)

GESE-package: \Sexpr[results=rd,stage=build]{tools:::Rd_package_title("#1")}GESEGene-Based Segregation Test

Description

\Sexpr[results=rd,stage=build]{tools:::Rd_package_description("#1")}GESEImplements the gene-based segregation test(GESE) and the weighted GESE test for identifying genes with causal variants of large effects for family-based sequencing data. The methods are described in Qiao, D. Lange, C., Laird, N.M., Won, S., Hobbs, B., et al. 2016. Gene-based segregation method for identifying rare variants for family-based sequencing studies. More details can be found at .

Arguments

Details

The DESCRIPTION file: \Sexpr[results=rd,stage=build]{tools:::Rd_package_DESCRIPTION("#1")}GESEThis package was not yet installed at build time.

\Sexpr[results=rd,stage=build]{tools:::Rd_package_indices("#1")}GESE Index: This package was not yet installed at build time.

computes gene-based segregation tests(GESE and weighted GESE) for family-based sequencing data. The main functions are: GESE: computes gene-based segregation information and GESE test p-values (unweighted and weighted version). trim_oneLineage: trims the pedigree so that for any subject, either the paternal family or the maternal family is included. Minimal set of sequenced subjects may be removed to ensure one lineage per pedigree only. trim_unrelated: trims the pedigree so that only one founder case is kept for each pedigree, and pedigrees with no cases are removed. condSegProbF: computes the conditional probability that a variant in the gene is segregating in the family specified, conditional on that the variant is present in the family.

References

Qiao, D. Lange, C., Laird, N.M., Won, S., Hobbs, B., et al. 2016. Gene-based segregation method for identifying rare variants for family-based sequencing studies.

http://scholar.harvard.edu/dqiao/gese

See Also

GESE

Examples

Run this code
data(pednew)
data(mapInfo)
data(dataRaw)
data(database)
results <- GESE(pednew, database, 1000000, dataRaw, mapInfo, threshold=1e-2)
results

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