Data and Resources

We embrace Open Science and are committed to improving the transparency, accessibility, and reproducibility of our research.

This includes activities such as preregistering our research plans (or registered reports), making our findings accessible through preprints and open access publication, and publicly sharing our results and code in an open and re-usable way. Below are some of the tools, databases and packages that we have produced as part of our research, which we encourage others to use and hope will benefit the research community.

Click here to find our inDEPTH GitHub, where we share resources, tutorials and scripts related to our research.


The EpiDelta Project

An online tool to visualize epigenome-wide changes in DNA methylation over the first two decades of life

Many studies have shown that DNA methylation patterns are strongly related to chronological age. Yet, how these patterns vary within individuals across development has been much less clear, due to the scarcity of longitudinal epigenetic studies. In a study led by Dr Rosa Mulder, we combined data from over 2000 children from two large epidemiological birth cohorts with repeated epigenetic assessments – the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Generation R Study – to map developmental trajectories of genome-wide DNA methylation from birth to adolescence (circa 480,000 sites across the genome). The results of this study have been used to create a freely accessible online tool, to enable interested users to visualize changes over time for DNA methylation sites of interest. Users can also download lists of DNA methylation sites that show specific patterns of change over time, such as (i) linear change (e.g. steadily increasing or decreasing with time), (ii) non-linear change (i.e. changing at different rates across development), (iii) inter-individual differences in change (i.e. with people differing from one another in their pattern of change); and (iv) sex differences in rate of change (i.e. with boys and girls differing in in their pattern of change).


OmicsR2 package

An R package to calculate total phenotypic variance explained by genome-wide DNA methylation

Epigenome-wide association analyses performed to date typically only make it possible to test how each DNA methylation site measured across the genome individually associates with an outcome of interest (e.g. BMI, mental health, behavioural outcomes), with each site generally showing small effect sizes. However, a central question in the field is how much phenotypic variation is explained by overall DNA methylation variation across the genome. To address this question, we have developed a new R package, OmicsR2 – an effort led by Dr Alexander Neumann. This package allows users to calculate the amount of variance explained in an outcome of interest by genome-wide DNA methylation, controlling for covariates. Testing this method in two large population-based birth cohorts – ALSPAC and Generation R – we have found that genome-wide DNA methylation in cord blood at birth explains a substantial amount of variation in birth outcomes, such as gestational age and birth weight. While these have not yet been tested, potential additional applications of OmicsR2 include (i) adding genome-wide SNP data to test phenotypic variance explained by DNA methylation over and above genetic influences, and (ii) applying OmicsR2 to omics data other than DNA methylation (e.g. transcriptomics).

Reference: Neumann, A., Pingault, JB, Felix JF, Jaddoe VWV, Tiemeier H, Cecil CAM* & Walton E* (2022). Epigenome-wide contributions to individual differences in childhood phenotypes: A GREML approach. Clinical Epigenetics. DOI: 10.1186/s13148-022-01268-w.


EarlyCause ELS measure

A cumulative measure of prenatal and postnatal early life stress harmonized across multiple population-based birth cohorts

Early life stress (ELS) is a key predictor of poor mental and physical health in later life. Research shows that (i) stress exposure as early as pregnancy can have an impact on development and health outcomes; (ii) there is continuity in stress exposure from the prenatal to postnatal period; (iii) different types of stressors co-occur with one another; and (iv) the more adversities are experienced, the stronger is the impact on health outcomes. This evidence calls for the need of comprehensive measures of ELS, which take into account the correlated nature of different types of stressors and their continuity across development. To this end, we have created a cumulative measure of prenatal and postnatal ELS spanning pregnancy to late childhood, which has been successfully harmonized across multiple large population-based cohorts, including ALSPAC and Generation R, and which is currently being estimated in the Norwegian Mother, Father and Child Study (MoBa). This work, led by Isabel Schuurmans and Serena Defina, is embedded within the EarlyCause consortium, dedicated to understanding the causal effect of ELS on mental and physical health across the lifespan. A full description of the measure and scripts for reproducibility are available in the link below.


Family Aggression Screening Tool (FAST)

A brief, pictorial screening tool for measuring exposure to intimate partner violence and child victimization

Family aggression, including child victimization and exposure to intimate partner violence (IPV), is a major developmental risk factor. Early screening of family aggression is important to facilitate timely intervention and help to avert negative consequences on children. While several self-report instruments are available to screen for these experiences (i) few assess both exposure to IPV and direct victimization of the child; (ii) fewer still record characteristics of family aggression, such as directionality of aggression between family members; and (iii) available measures rely heavily on a verbal format (e.g. questionnaire), which may limit their applicability to a range of populations, including younger respondents, individuals with reading difficulties and non-native speakers. To address these limitations, we have developed a new instrument in collaboration with Dr Ted Barker: the Family Aggression Screening Tool (FAST). The FAST is a brief, self-report tool that makes use of pictorial representations to assess experiences of caregiver aggression. It is free and takes under 5 minutes to complete. The FAST shows good psychometric properties and it has been validated in both an English sample of high-risk adolescents (Cecil et al., 2016) as well as a large Brazilian sample of high-risk children (Vieira et al., in press). Full details of the FAST can be found in the reference below. The measure is freely available upon request.


Validation in UK sample: Cecil CAM, McCrory, EJ, Viding E, Holden GW, & Barker ED (2016). Initial validation of a brief pictorial measure of caregiver aggression: The family aggression screening tool. Assessment23(3), 307-320. DOI: 10.1177/1073191115587552.

Validation in Brazilian sample: Vieira R, Pires PP, Cecil CAM, Barker E, Reis D, Couto I, Cypriano C & de Oliveira IR. (2022). Family Aggression Screening Tool (FAST): factor structure and psychometric properties of subscales. Child Abuse & Neglect, 127, DOI:

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