Author Archives: Jeremy Yoder

About Jeremy Yoder

Jeremy Yoder is a postdoctoral associate in the Department of Plant Biology at the University of Minnesota. He also blogs at Denim and Tweed and Nothing in Biology Makes Sense!, and tweets under the handle @jbyoder.

What we’re reading: The color of cichlids, projected genomes, and simplifying NSF proposals

In the journals Albertson RC, KE Powder, Y Hu, KP Coyle, RB Roberts, and KJ Parsons. 2014. Genetic basis of continuous variation in the levels and modular inheritance of pigmentation in cichlid fishes. Molecular Ecology, 23: 5135–5150. doi: 10.1111/mec.12900. … … Continue reading

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What we’re reading: A meta-analysis of meta-analyses, plants’ cytoplasmic genomes, and science under political attack

In the journals Koricheva, J. and J. Gurevitch. 2014. Uses and misuses of meta-analysis in plant ecology. Journal of Ecology, 102: 828–844. doi: 10.1111/1365-2745.12224. We found many cases of imprecise and inaccurate usage of the term ‘meta-analysis’ in plant ecology, … Continue reading

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What we’re reading: QTLs of pine growth, climate-niche evolution, and the shape of Twitter conversations

In the journals Li Z., H.R. Hällingback, S. Abrahamsson, A Fries, B.A. Gull, M.J. Sillanpää and M.R. García-Gil. 2014. Functional multi-locus QTL mapping of temporal trends in Scots pine wood traits. G3: Genes | Genomes | Genetics. doi: 10.1534/g3.114.014068. Two … Continue reading

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How many markers does it take to make a dataset “genomic”?

A new paper in Ecology Letters by Matthew Fitzpatrick and Stephen Keller proposes to use some a class of statistical methods developed for understanding the distribution of species in different environments to understand the distribution of genetic variants in different … Continue reading

Posted in association genetics, genomics, next generation sequencing, population genetics, software | 5 Comments

House science committee is digging for dirt in NSF’s confidential records of peer review

ScienceInsider reports that aides for the U.S. House Committee on Science, Space, and Technology have been spending the summer digging through records of grant the grant review process that the National Science Foundation usually keeps confidential: The Republican aides were … Continue reading

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What we’re reading: Sorting out whole-genome duplication, adaptation without tradeoffs, and is science leaving its logistic growth phase?

In the journals McGrath CL, J-F Gout, P Johri, TG Doak, and M Lynch. Differential retention and divergent resolution of duplicate genes following whole-genome duplication. 2014. Genome Res. 24: 1665-1675. doi: 10.1101/gr.173740.114. Finally, multiple sources of evidence indicate that [Paramecium] … Continue reading

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We’re looking for a few good Molecular Ecologists (UPDATED)

Update, 6 October: Thanks to everyone who has written in to apply for a position! I’ll try to respond to your inquiries in the next day or so; we’ll continue to accept applications until next Monday, 13 October before making … Continue reading

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What we’re reading: A guide to Bioconductor, Latin American admixture, and the sordid truth about academic job hunting

In the journals Lawrence M., M. Morgan. 2014. Scalable genomics with R and Bioconductor. arXiv:1409.2864. This paper reviews strategies for solving problems encountered when analyzing large genomic data sets and describes the implementation of those strategies in R by packages … Continue reading

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What we’re reading: Bayesian phylogenetics for whole genomes and coevolutionary interactions in epidemiology

In the journals Aberer A.J., K. Kobert, and A. Stamatakis. 2014. ExaBayes: Massively parallel Bayesian tree inference for the whole-genome era. Mol. Biol. Evol. 31(10): 2553-2556. doi: 10.1093/molbev/msu236. Modern sequencing technology now allows biologists to collect the entirety of molecular … Continue reading

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Fishing for genetic signals of adaptation

One of the biggest promises of modern DNA sequencing methods is the ability to track the adaptation of living populations at a fine genetic scale, in essentially real time. It’s already been done in a number of experimental evolution systems: … Continue reading

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