Data reuse for re-analysis and publishing results via Twitter is a whole new level of 'open'...

Data reuse for re-analysis and publishing results via Twitter is a whole new level of 'open'...

http://www.nature.com/news/potential-flaws-in-genomics-paper-scrutinized-on-twitter-1.17591?WT.ec_id=NATURE-20150528

Potential flaws in genomics paper scrutinized on Twitter

Reanalysis of a study that compared gene expression in mice and humans tests social media as a forum for discussing research results.

• Chris Woolston

20 May 2015

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A recent Twitter conversation that cast doubt on the conclusions of a genomics study has revived a debate about how best to publicly discuss possible errors in research. Yoav Gilad, a geneticist at the University of Chicago in Illinois, last month wrote on Twitter that fundamental errors in the design and data analysis of a December 2014 study² led to an unfounded conclusion about the genetic similarities between mice and humans. Gilad and his co-author Orna Mizrahi-Man, a bioinformatics researcher at the University of Chicago, have since detailed their data reanalysis¹ in the open-access journal F1000Research (in which articles are openly peer-reviewed after publication). Michael Snyder, a geneticist at Stanford University in California and co-author of the original paper, stands by his team’s study and its conclusions and says that Gilad broke the “social norms” of science by initially posting the critique on Twitter. Gilad says that he took to social media to highlight his work, which might otherwise have been overlooked.

http://www.nature.com/news/potential-flaws-in-genomics-paper-scrutinized-on-twitter-1.17591?WT.ec_id=NATURE-20150528

Nature article on data sharing

Thank you for sharing

Initiatives to make genetic and medical data publicly available could improve diagnostics — but they lose value if they do not share with other projects.....

....The imperative to share data remains an esoteric issue for much of the public, and one that is easily obscured. Companies or researchers who talk the talk of sharing but do not actually walk the walk should be challenged. Data sharing is too important to be turned into meaningless marketing speak.

Nature

 

520,

 

585

 

(30 April 2015)

 

doi:10.1038/520585a

August 28, 2014

NIH Tells Genomic Researchers: ‘You Must Share Data'

By Paul Basken

Scientists who use government money to conduct genomic research will now be required to quickly share the data they gather under a policy announced on Wednesday by the National Institutes of Health.

The data-sharing policy, which will take effect with grants awarded in January, will give agency-financed researchers six months to load any genomic data they collect—from human or nonhuman subjects—into a government-established database or a recognized alternative.

http://chronicle.com/article/NIH-Tells-Genomic-Researchers-/148509/

Inflammation Data Clash

Identical datasets yield opposite conclusions on the use of mice as models of human inflammation.

http://www.the-scientist.com//?articles.view/articleNo/40713/title/Inflammation-Data-Clash/

WIKIMEDIA, DOUG BECKERSIn 2013, a large group of collaborators published a paper in PNAS concluding that genomic responses to inflammatory stress in mice don’t correlate well with those in humans. “The prevailing assumption—that molecular results from current mouse models developed to mimic human diseases translate directly to human conditions—is challenged by our study,” Junhee Seok, who’s now at the Northwestern University Feinberg School of Medicine, and his colleagues wrote in their paper.

Fast forward to last week, and another study, using the very same data, reached the opposite conclusion.

“Here we re-evaluated the same gene expression datasets used in the previous study by focusing on genes whose expression levels were significantly changed in both humans and mice,” Keizo Takao and Tsoyosji Miyakawa wrote in their recent paper, also published in PNAS. “Contrary to the previous findings, the gene expression patterns in the mouse models showed extraordinarily significant correlations with those of the human conditions.”

So what gives?

According to a press release from Fujita Health University, where Miyakawa is based, the original study compared all the genomic changes, regardless of whether the involved genes only responded to the stress in one of the species. Such an approach “obscures the correlation between homologous genes of humans and mice to nearly zero, as demonstrated by Seok et al.” in the 2013 paper, the release read.

Gregory Hickok, a neuroscientist at the University of California, Irvine, tweeted: “Reflects that the conclusions aren’t automatically given by data. It’s all in the interpretation.”