Something good must have happenend at Nature Genetics. After a flood of GWASs they seem to be back to publications I am actually interested in. I’m not exactly sure when the change happened, but in the current issue several computational papers stand out:
De novo assembly and genotyping of variants using colored de Bruijn graphs
Nature Genetics 44, 226 (2012). doi:10.1038/ng.1028
Authors: Zamin Iqbal, … & Gil McVean
We introduce de novo assembly algorithms using colored de Bruijn graphs for detecting and genotyping simple and complex genetic variants in an individual or population. We provide an efficient software implementation, Cortex, the first de novo assembler capable of assembling multiple eukaryotic genomes simultaneously.
A method paper, nice! I hope it is as definitive as it is groundbreaking.
Toward interoperable bioscience data
Nature Genetics 44, 121 (2012). doi:10.1038/ng.1054
Authors: Susanna-Assunta Sansone, … many others … & Winston Hide
The research community requires solutions that accommodate the current ‘wealth’ of standards and resources, but hides it from users, thereby simplifying their efforts to meet (or ideally, exceed) applicable reporting requirements.
Right they are! I am a user, and known to be particularly lazy in filling out forms. Anything that makes ‘data interoperability’ work without too much effort on my side is very welcome!
Developing predictive molecular maps of human disease through community-based modeling
Nature Genetics 44, 127 (2012). doi:10.1038/ng.1089
Authors: Jonathan M J Derry, … several others … & Stephen H Friend
Biology is rapidly becoming a science that is driven by technology and large-scale data. Herein lies an opportunity to transform our understanding of the molecular underpinnings of disease and develop modeling frameworks that can describe complex systems and predict their behavior.
An opinion piece, not a research paper. I have been following the efforts of SAGE Bionetworks for a while and am very supportive of their goals – even though the talks I’ve heard were sometimes a bit on the abstract side and I would need some more concrete success stories to be fully convinced.
And finally: The age of GWAS is not over –and Nat Gen couldn’t resist to put a GWAS-theme on the cover– but at least this is a new perspective on it:
The authorship network of genome-wide association studies
Nature Genetics 44, 113 (2012). doi:10.1038/ng.1052
Authors: Brendan K. Bulik-Sullivan & Patrick F. Sullivan
We constructed network diagrams in the form of graphs, where nodes are authors and edges connect coauthors on a GWAS paper (…). This graph (…) is coherent in the identification of individuals, laboratories and phenotypes studied.
I must have missed the bit where the authors explain what new things they have learned from the graph. But then again, ‘pretty, but useless‘ is not an unusual outcome in the field of network biology.
The current issue still contains some GWAS and the Nature Genetics homepage lists even more as latest highlights, but still the current issue makes me cautiously hopeful that in future NatGen will get the balance right.