Selected Publications

The exposome is defined as the totality of human environmental exposures from conception onward, complementing the genom and its holistic approach may advance understanding of disease etiology. We aimed to describe the correlation structure of the exposome during pregnancy to better understand the relationships between and within families of exposure and to develop analytical tools appropriate to exposome data.
Environ Sci. Technol.

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  • CTDquerier: a tool for enrichment analysis in genetic and toxicological studies using CTD

    Details GitHub Bioinformatics

  • Association between the Early-Life exposome and birth weight


  • Cohort Profile: the Human Early Life Exposome (HELIX) study - A European Population-Based Exposome Cohort


  • Circulating miRNAs, isomiRs and small RNA clusters in human plasma and breast milk

    Details PLoS ONE

  • Comprehensive analysis of the exposome-health associations and omics signatures detection using rexposome project R/Biodonductor packages

    Details GitHub

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To annotate a list of KEGG compounds to the KEGG pathways where they are involved I used the R package KEGGREST from Bioconductor. library(KEGGREST) So, having a list of KEGG compounds saved in a character vector like kegg_compounds, we use the method keggGet in batches of maximum 10 compounds to annotate them. The following (rudimentary) code, queries the database in batches of ten compounds fiddling a list (pathways) where it creates an entry per pathway and updates the field compounds with the compounds from kegg_compounds for each pathway.


At the end of January I will be moving to Boston. I will start my post-doc at the Boston Children’s Hospital. So… I started looking to weather and temperature conditions. I used Weather Underground to download a weatehr tamble for each month in 2016 and 2017. The aim is to create a plot with everyday mínimum and maximum temperature along all 2017. Also a heat-map indicating the weather condition of each day of the year.


It is the time to follow the tradition of creating a geek christmas card. As I did last year, the one for this year is typed it in javascript. It is much simpler compared to the game of the 2016 Christmas, but I enjoyed coding it. Merry Christmas 2017-2018 The card is a HTML5 canvas used as a grid where different pixelled cartoons appears being drawn pixel-a-pixel. I have coded five different patterns.


In the HELIX project we decided to use residuals instead of M values for the methylation analyses. So, how we get the residuals of a basic lineal model? Libraries and Data First of all we load the libraries we will use in this test: library( limma ) # We use lmFit to fit the lineal model library( minfi ) # Methylation data is saved as a GenomicRatioSet library( SmartSVA ) # We want to compute the SVA to correct methylation data library( isva ) # " library( Biobase ) # We will sabe the residuals in an ExpressionSet Once the libraries are loaded we proceed to obtain the methylation data:


The Rcupcake package contains functions to query different databases through the BD2K RESTful API. BD2K RESTful API is an interface that provides access to different data sources, making easier data accessibility, analysis reproducibility and scalability. The package is installed via devtools using it’s GitHub URL (hms-dbmi/Rcupcake) library( Rcupcake ) Rcupcake package follows a four-step process to retrieve the data from a database: Start session Select the variables of interest Build the JSON query Run the query to obtain the data The start.