Month: July 2017

This is a joint work with Benjamin Rodriguez-Santiago (qGenomics) and Luis Pérez-Jurado (UPF). MAD is a software tool to detect mosaic events from SNP arrays using BAF and LRR values. The algorithm is based on a segmentation procedure which uses the main features of GADA (and R package to detect CNVs). To install MAD, start R and enter: [generic] source("http://www.creal.cat/media/upload/arxius/jr/CREAL_install/install.R") creal.install("mad") [/generic] The methodological paper has been accepted in BMC Bioinformatics and can be found here. An example about how to use the software is described in the vignette. The algorithm has been used to discover mosaic alterations in a large collaborative study: > *Jacobs KB, Yeager M, Zhou W, ... Gonzalez JR, ... Rothman N, Pérez-Jurado LA, Chanock SJ. Detectable clonal mosaicism and its relationship to aging and cancer.…

`inveRsion` is an R package for the detection of genetic inversions using SNP-array data. This is a joint collaboration with Alejandro Caceres (ISGlobal) and Suzanne Sindi (Center for Computational Molecular Biology, Brown University). `inveRsion` is available at Bioconductor, and a manuscript is published at BMC Bioinformatics: > *Cáceres A, Sindi SS, Raphael BJ, Cáceres M, González JR. Identification of polymorphic inversions from genotypes. BMC Bioinformatics. 2012 Feb 9;13:28.* Our aim is to use SNP-array data of large cohorts, for which phenotype information has been collected, to assess the association of inversions with disease. We also intent to use the tool to assist in the mapping of human inversions; a project headed by Mario Caceres (Universitat Autonoma de Barcelona). * **Bioconductor**: [`inveRsion`](http://bioconductor.org/packages/release/bioc/html/inveRsion.html)

`tweeDEseq` is an R package for analyzing RNAseq count data. It implements Poisson-Tweedie family of distributions to model count data distribution. This family includes Poisson and Negative Bionomial as particular cases. The testPT test is used to detect genes that are deferentially expressed (DE). The methods are described in the manuscript published at BMC Bioinformatics: > *Esnaola M, Puig P, Gonzalez D, Castelo R, Gonzalez JR. A flexible count data model to fit the wide diversity of expression profiles arising from extensively replicated RNA-seq experiments. BMC Bioinformatics 2013, 14:254.* The manuscript illustrates the performance of our proposed method using a real RNA-seq data set comprising 69 Nigerian. We have created an experimental data pacakge (tweeDEseqCountData) that is available at Bioconductor. `tweeDEseq` is available from Bioconductor: * **Bioconductor**: [`tweeDEseq`](http://bioconductor.org/packages/release/bioc/html/tweeDEseq.html)

Joint with Alejandro Cáceres (ISGlobal), we have developed a method that can be applied to common GWAS for calling the inversion genotypes, which accounts for population stratification when an appropriate reference population is not known. This method is extremely useful when performing inversion association studies in a GWAS context were population stratification can be present. To install `invClust`, start R and enter: ``` source("http://www.creal.cat/media/upload/arxius/jr/CREAL_install/install.R") creal.install("invClust") ``` If you experiment some problem during this process, the source code of the package can be download from [here](http://www.creal.cat/media/upload/arxius/jr/inversions/invClust_1.0.tar.gz). The methods are described in the manuscript: > *Cáceres and González, J. R. (2015) Following the footprints of polymorphic inversions on SNP data: from detection to association tests. NAR doi:10.1093.*

This is a joint work with Roderic Guigó's group - Bioinformatics and Genomics program, Center for Genomic Regulatio (CRG). This R package is designed to compare transcript relative expression of different conditions obtained from RNA-seq experiments. Our approach is based on a distance-based non-parametric multivariate ANOVA method. The Linux version of the package is currently under development. To install a beta version of rasp, start R and enter: ``` library(devtools) install_github("isglobal-brge/rasp") ``` The performance of our approach has been compared with two other existing R packages (`DEXseq` and `EBseq`) using data from The Cancer Genome Atlas (TCGA). Exon abundances from RNA-seq data were obtained for several individuals diagnosed with Liver hepatocellular carcinoma [LIHC] and Bladder Urothelial Carcinoma [BLCA]. We have created two experimental data packages (`ExonCountDataLIHC` and `ExonCountDataBLCA`, respectively). So…

This package contains a set of tools to analyze and visualize methylation and gene expression data. This is a work of Carlos Ruiz (ISGlobal). The package can be installed through Bioconductor: ``` source("https://bioconductor.org/biocLite.R") biocLite("MEAL") ```

This package is created for combining several different sources of information (including different omic data-sets) into a single convenient structure. A `MultiDataSet` object can be manipulated (e.g., subsetted, copied, ...) conveniently, and can be the input or output from some Bioconductor packages designed to integrate multi-omic data. This is a joint work with Carlos Ruiz-Arenas (ISGlobal) and Carles Hernandez-Ferrer (ISGlobal). The package can be bound at **Bioconductor** and **GitHub**: * **Bioconductor**: [`MultiDataSet`](http://bioconductor.org/packages/release/bioc/html/MultiDataSet.html) * **GitHub**: [`MultiDataSet`](https://github.com/isglobal-brge/MultiDataSet) We published an article about its implementation (January 17th, 2017): > Carles Hernandez-Ferrer, ... Juan R. González; MultiDataSet: an R package for encapsulating multiple data sets with application to omic data integration. BMC Bioinformatics; https://doi.org/10.1186/s12859-016-1455-1