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We have developed some packages included in the R project in collaboration with other researches from different
institutions. Some of these libraries are related to
genetics and other ones to survival analysis with recurrent events. Genetics We are interested in assessing association between CNVs and traits
using information obtained from MLPA, Illumina, aCGH or any other platform
that provides quantitative measurements. To do so, we propose a class of
latent models that incorporates uncertainty when copy number status is
inferred. The functions for assessing association are implemented in an R
package (tar.gz file (Linux) or zip file (Windows)). The package requires libraries ‘mixdist’
and ‘mclust’ to be installed. We have included two real data sets to
illustrate how the model works. They are described in the vignette (the scripts can be
downloaded here MLPA example and aCGH example). The statistical
methods and the examples are described in the paper: ·
Gonzalez JR, Subirana I, Escaramis
G, Peraza S, Caceres A, Estivill X, Armengol L. Latent Class Model to Assess
Association between Copy Number and Disease. BMC Bioinformatics 2009, 10:172. Multiplex
ligation-dependent probe amplification (MLPA) method is a potentially useful
semi-quantitative method to detect copy number alterations in targeted
regions. In this project we are developing statistical models and methods to
determine the statistical significance of altered probes. The functions are
implemented in an R package (tar.gz file
(Linux) or zip file (Windows)) that
contains an R GUI application. The package has two real MLPA data sets that
can be analyzed as described in the vignette. The script can be downloaded here. The
statistical methods are described in the paper: ·
Gonzalez JR, Carrasco JL, Armengol
J, Villatoro S, Jover L, Yasui Y, Estivill X. Probe-specific mixed-model
approach to detect copy number differences using multiplex ligation-dependent
probe amplification (MLPA). BMC Bioinformatics 2008, 9:261. This package was built when I was working at Xavier Estivill’s
lab at Center
for Genomic Regulation and it is written in collaboration with Victor
Moreno and his colleagues. The R package SNPassoc contains classes
and methods to help the analysis of whole genome association studies.
SNPassoc utilizes S4 classes and extends haplo.stats
R package to facilitate haplotype analyses. The package is useful to carry
out most common analysis when performing whole genome association studies.
These analyses include descriptive statistics and exploratory analysis of
missing values, calculation of Hardy-Weinberg equilibrium, analysis of
association based on generalized linear models (either for quantitative or
binary traits), and analysis of multiple SNPs (haplotype and epistasis
analysis). Permutation test and related tests (sum statistic and truncated
product) are also implemented. The methodology is described in: ·
JR Gonzalez, L Armengol, X Sole, E Guino, JM Mercader, X Estivill, V
Moreno (2007). SNPassoc: an R package to perform whole genome
association studies. Bioinformatics, 23:644-5 and it has been used in: ·
Mercader JM, Ribasés M, Gratacòs M, González JR, Bayés M, de Cid R,
Badía A, Fernández-Aranda F, Estivill X (2007). Altered
brain-derived neurotrophic factor blood levels and gene variability are
associated with anorexia and bulimia. Genes Brain Behav. [Epub ahead of
print] ·
Gratacòs M, Soria V, Urretavizcaya M, González JR, Crespo JM, Bayés M,
de Cid R, Menchón JM, Vallejo J, Estivill X (2007). A
brain-derived neurotrophic factor (BDNF) haplotype is associated with
antidepressant treatment outcome in mood disorders. Pharmacogenomics J. [Epub
ahead of print] This package is available from CRAN (source
code, manual
and vignettes)
The function requires BayesMedel R package in particular a C program
which computes the probability of observing the phenotypes for the whole
pedigree (deaf or hearing) given the genotype of the proband. This package is
available upon request at BayesMendel
lab from The Johns Hopkins University. The methodology is described in: ·
Gonzalez JR, Wang W, Ballana E, Estivill X (2006). A
Recessive Mendelian Model to Predict Carrier Probabilities of DFNB1 for Nonsyndromic
Deafness. Human Mutation, 27(11):1135-1142. Packages for dealing with recurrent events This package is written joint with
Virginie Rondeau. Frailtypack can be used to
estimate the parameters in a shared gamma frailty model with potentially
right censored, left truncated and stratified survival data, using maximum
penalized likelihood estimation. Time-dependent structure for the explanatory
variables and/or estension of the Cox regression model to recurrent events
are also allowed. This program can also be used simply to obtain directly a
smooth estimates of the baseline hazard function. The methodology is described and the package used in: ·
V Rondeau, JR Gonzalez (2005).
Frailtypack: a computer program for the analysis of correlated failure time
data using penalized likelihood estimation. Computer Methods and Programs in
Biomedicine, 80:154-64. This package is available from CRAN: source
code and manual A new version of frailtypack will be available soon!. This new version will include functions for
analyzing hierarchical (nested) models, recurrent event data with terminal
event as well as an additive frailty model to model the random treatment ×
trial interaction and the random trial effect jointly in an individual
patient data meta-analysis. This package is written joint with Edsel A
Peña and
Elizabeth
Slate. Gcmrec estimates the parameters involved in a
general class of models for recurrent event data proposed by Pena and
Hollander. This software also estimate a model designed for analyzing
relapses in patients diagnosed with cancer considering the effect of
treatment after treatment as described in Gonzalez JR, Peña E, Slate (2006). The methodology is described and the package used in: ·
E Peña, EH Slate, JR Gonzalez (2007). Semiparametric
inference for a general class of models for recurrent event data. J Stat
Planning Inference, 137:1727-1747. ·
JR Gonzalez, E Peña, E Slate (2005). Modelling
intervention effects after cancer relapses. Stat Med, 24:3959-75. This package is available from CRAN: source
code and manual This package is written joint with Edsel A
Peña and
Robert
Strawderman. Survrec is designed to estimate the survival
function for recurrent event data using Pena-Stawderman-Hollander and
Wang-Chang estimators and MLE
estimation under a gamma frailty model. This package is available from CRAN: source
code and manual
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