TP53 germline mutation carrier estimation and cancer risk predictions


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Documentation for package ‘LFSPRO’ version 2.0.0

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LFSPRO-package TP53 mutation carrier estimation and cancer risk predictions
calLK Calculate the likelihood Pr(D|G).
calLK.cs Calculate the likelihood Pr(D|G) for cancer specific.
calLK.mpc Calculate the likelihood Pr(D|G) of multiple primary cancers.
cancer.data Built-in Cancer Information Data example
cancer.type.all Predefined cancer types in LFSPRO.
combined.risk.mpc Calculate the future cancer risk using the MPC model
combinedata Combine the family information data and cancer information data
convert.data Convert the combined family information data and cancer information data into separate data objects.
fam.cancer.data Data object with Family and Cancer Information Example
fam.data Built-in Family Information Data Example
firstDegreeRelative First degree relatives
invasive.cut Cutoff for malignant cancer
lfs.cut Cutoff for Li-Fraumeni Syndrome spectrum cancer
lfsChompret2009 The Chompret criteria for Li-Fraumeni syndrome
lfsChompret2015 The Chompret criteria for Li-Fraumeni syndrome
lfsClassic The Classic criteria for Li-Fraumeni syndrome
lfspenet.2010 Penetrance for TP53 mutations
lfspenet.cs.death Penetrance table for cancer-specific mutation with four competing risks (breast cancer, sarcoma, other cancers and death).
lfspenet.cs.nodeath Penetrance table for cancer-specific mutation with three competing risks (breast cancer, sarcoma and other cancers). Default penetrance table in predicting cancer-specific risks.
lfspro.cancer.type Predefined cancer types and the corresponding number in lfspro
lfspro.mode Estimate TP53 mutation probability and predict cancer risk for families with Li-Fraumeni Syndrome with mode choice
lfsproC Calculate the posterior probability of p53 mutations on the basis of family history
lfsproC.cs Calculate the posterior probability of p53 mutations for cancer-specific risk prediction model on the basis of family history
lfsproC.mpc Calculate the posterior probability of p53 mutations for multiple primary cancer on the basis of family history
lkNoneAffect Likelihood for un-affected individuals
lkNoneAffect.cs Likelihood for un-affected individuals for cancer-specific model
parameter.mpc Estimated parameter for semiparametric recurrent event model of multiple primary cancers
peelingRC Peeling interface in R.
reformatForClassicChompret Reformat input data of LFSPRO for evaluation using the Classic or the Chompret criteria
risk.cs Predict the cancer-specific risk
risk.mpc Predict the risks of developing multiple primary cancers
secondDegreeRelative Second degree relative