Category Archives: bioinformatics

What do dolphins, bivalves and algae have in common?

Collaboration as it turns out, between three scientists interested in vertebrates, invertebrates and algae! A few days before we left for Evolution 2016 in Austin, one of my collaborators, Eric Pante, came to Charleston as the final stop in a North American … Continue reading

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Posted in bioinformatics, blogging, career, conferences, DNA barcoding, haploid-diploid, natural history, phylogenetics, phylogeography, population genetics | Tagged , , , , , | Leave a comment

STITCH, in time, could save a lot of array design

A new algorithm for processing DNA sequence data, STITCH, could lower costs for studies of genetic variation within species by reconstructing, or “imputing”, the sequences of individual samples within a larger dataset. The ongoing proliferation of high-throughput (or, ugh, “next … Continue reading

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Who’s really riding the subway with you? Characterization of the microbial communities on Boston transport

(Figure modified from Hsu et al., 2016, Boston transport map and wikicommons image of Boston) Understanding the microbes around us is an important challenge to take on. There have been articles covering changes in microbial communities among rural and more … Continue reading

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The not so singular process of hybridization

What, if anything, are hybrids? Zach Gompert and Alex Buerkle ask this question in a special issue in Evolutionary Applications. Hybrids occur when unrelated individuals mate, but how distant do the taxa need to be to constitute a cross? The varied … Continue reading

Posted in bioinformatics, conservation, domestication, evolution, genomics, natural history, next generation sequencing, plants | Tagged , , , | Leave a comment

Data, data everywhere and another tool to use: Taxonomer, a web-tool for metagenomics data analysis

Because sequencing. With all the affordable genome and metagenome sequencing available, we’ve reached an unprecedented point at which we can profile microbial communities more accurately than ever before. For this reason, it’s essential to develop efficient methods for data analysis. … Continue reading

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Steelhead in a random forest: identifying the genetic basis of migration

Genome-wide association studies (GWAS) have been quite successful in identifying variants associated with various phenotypes (I suppose there is some debate surrounding this statement. For an interesting, if dated, discussion look here). While most of this work was originally conducted … Continue reading

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Poorly updated databases will affect your results

If you’re anything like me, your research is heavily dependent on the many wonderful database resources available online. NCBI, UniProtKB, Ensembl, Swiss-Prot, EMBL-EBI, and many other sites and organizations offer highly useful (and often curated) molecular information. Can you imagine … Continue reading

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