Clinical Genetics Has a Big Problem That's Affecting People's Lives

Over the last decade, there’s been a lot of talk about reproducibility problems in science — about published results that turn out to be false alarms. In fields like psychology, neuroscience, and cell biology, these errors can send scientists down unproductive paths, waste time and money, and pollute headlines with misleading claims. "But I get much more exercised about reproducibility problems in clinical genetics, because those have massive and real-time consequences for thousands of families," says MacArthur.

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  • Emphasize Sex in Research, orders National Institutes of Health

    While experiments may be published even in a top scientific journal, other researchers who attempt to repeat the same experiments under the same conditions often find contradicting results. As a measure of this, a recent study attempted to reproduce psychology publications and successfully replicated only 39 out of 100 studies. It turns out that excluding sex in experimental design may have contributed to reproducibility issues. Furthermore, sex can also have a biological impact on our scientific understanding and influence how well early biological studies translate into advances in human medicine.

    Big problems for common fMRI thresholding methods

    Stanford Center for Reproducible Neuroscience: A new preprint has been posted to the ArXiv that has very important implications and should be required reading for all fMRI researchers. Anders Eklund, Tom Nichols, and Hans Knutson applied task fMRI analyses to a large number of resting fMRI datasets, in order to identify the empirical corrected “familywise” Type I error rates observed under the null hypothesis for both voxel-wise and cluster-wise inference. What they found is shocking: While voxel-wise error rates were valid, nearly all cluster-based parametric methods (except for FSL’s FLAME 1) have greatly inflated familywise Type I error rates. This inflation was worst for analyses using lower cluster-forming thresholds (e.g. p=0.01) compared to higher thresholds, but even with higher thresholds there was serious inflation. This should be a sobering wake-up call for fMRI researchers, as it suggests that the methods used in a large number of previous publications suffer from exceedingly high false positive rates (sometimes greater than 50%).

    Letting Out Steam: Reproducibility Problems

    The first part of the STM innovations seminar focused on the problems of reproducibility in science. For some years now, there have been voices of concern noting that when previously reported results are tested, the data very often doesn’t come out the same way. During the seminar, Andrew Hufton of Scientific Data went so far as to state that progress in the pharmaceutical sciences is being held back by lack of reliability in the basic literature.

    Translation, cultural adaptation and reproducibility of the Oxford Shoulder Score questionnaire for Brazil, among patients with rheumatoid arthritis.

    Although shoulder questionnaires validated for Brazil do exist, none of them are aimed at populations with rheumatic disease. We believe that the Oxford Shoulder Score (OSS) may be useful in this population. The objective of this study was to translate the OSS, adapt it to Brazilian culture and test its reproducibility.

    How do we fix bad science?

    Independently verifying research can help science regain its credibility, argues Laurie Zoloth. His paper: "Why Most Published Research Findings Are False", was published in August 2005, in PLOS Medicine. It became one of the journal’s most-cited articles. While climate sceptics, anti-vaccination campaigners and the rest of the pseudo-science community have dined out on this paper, arguably it has been a shot in the arm for science.