Mine, yours, ours? Sharing data on human genetic variation

Abstract

The achievement of a robust, effective and responsible form of data sharing is currently regarded as a priority for biological and bio-medical research. Empirical evaluations of data sharing may be regarded as an indispensable first step in the identification of critical aspects and the development of strategies aimed at increasing availability of research data for the scientific community as a whole. Research concerning human genetic variation represents a potential forerunner in the establishment of widespread sharing of primary datasets. However, no specific analysis has been conducted to date in order to ascertain whether the sharing of primary datasets is common-practice in this research field. To this aim, we analyzed a total of 543 mitochondrial and Y chromosomal datasets reported in 508 papers indexed in the Pubmed database from 2008 to 2011. A substantial portion of datasets (21.9%) was found to have been withheld, while neither strong editorial policies nor high impact factor proved to be effective in increasing the sharing rate beyond the current figure of 80.5%. Disaggregating datasets for research fields, we could observe a substantially lower sharing in medical than evolutionary and forensic genetics, more evident for whole mtDNA sequences (15.0% vs 99.6%). The low rate of positive responses to e-mail requests sent to corresponding authors of withheld datasets (28.6%) suggests that sharing should be regarded as a prerequisite for final paper acceptance, while making authors deposit their results in open online databases which provide data quality control seems to provide the best-practice standard. Finally, we estimated that 29.8% to 32.9% of total resources are used to generate withheld datasets, implying that an important portion of research funding does not produce shared knowledge. By making the scientific community and the public aware of this important aspect, we may help popularize a more effective culture of data sharing.

Figure 1. Procedure used to analyze data sharing in papers regarding human genetic variation.

We retrieved a total of 1187 papers indexed between 1^st January 2008 and 31^st December 2011 in the PubMed using the key words “mtDNA human populations” and “Y chromosome human populations”. We set the following limits: “humans” for species and “English” for language. The procedure used for data request by email is described in figure 2. E-mails “will provide on request” were sent to the corresponding authors to request information from papers where data availability upon request is explicitly declared; E-mails “all authors” were sent to all corresponding authors who withheld datasets.

Figure 2. Procedure used to request data from corresponding authors of withheld datasets.

The first two e-mails were sent by the first author (nicola.milia@uniroma1.it) of this paper, while the third one was sent by the corresponding author (destrobisol@uniroma1.it). The data collection was closed five weeks after the first request. E-mails “will provide on request” were sent to the corresponding authors of papers where data availability upon request is explicitly declared; E-mails “all authors” were sent to all other corresponding authors who withheld datasets.

Figure 3. Sharing rates in published datasets regarding human genetic variation.

Vertical bars indicate 95% confidence intervals. Separate results for mtDNA and Y chromosome polymorphisms are reported in Table 1. (A) In the “Immediate sharing” category, we reported the rate of datasets shared in the main text, its supplementary material or online databases which were explicitly indicated in the paper; E-mails “will provide on request” were sent to the corresponding authors to request information from papers where data availability upon request is explicitly declared; E-mails “all authors” were sent to all corresponding authors who withheld datasets. The results reported in frames B, C and D were obtained using the sharing rates obtained including the positive answers to E-mails “will provide on request”. We considered as negative the responses where authors asked for detailed information about the use of datasets and/or requested coauthorship before sending data. (B) Datasets were assigned to each research field according to the research aims, as stated in the paper. When assignment of a given paper to more than one field of research seemed to be possible or research aims were ambiguous or not explicit, the ISI category of the scientific Journal was used as an additional criterion. (C) The type of editorial policy was rated using the information provided in the guide to authors: weak editorial policies are those where the authors are invited to share data, whereas in strong policies, data sharing is indicated as mandatory. (D) Ranks were based on impact factor values released by ISI Reuters in June 2009.