In case you have not hear – Nature Publishing Group continues to play around with open publishing and other open science initiatives (when they switch some of their big journals to fully OpenAccess I will stop referring to it as playing around …). The latest is that Nature has bought into the Frontiers publishing group which publishes a series of Open Access journals. For more on this see:
Below is a guest post from my friend and colleague Kimmen Sjölander, Prof. at UC Berkeley and phylogenomics guru.
Announcing the FAT-CAT phylogenomic annotation webserver.
FAT-CAT is a new web server for phylogenomic prediction of function and ortholog identification and for taxonomic origin prediction of metagenome sequences based on HMM-based classification of protein sequences to >93K pre-calculated phylogenetic trees in the PhyloFacts database. PhyloFacts is unique among phylogenomic databases in having both broad taxonomic coverage – more than 7.3M proteins from >99K unique taxa across the Tree of Life, including targeted coverage of genomes from Eukaryotes, Bacteria and Archaea — and integrating functional data on trees for Pfam domains and multi-domain architectures. PhyloFacts trees include functional and annotation data from UniProt (SwissProt and TrEMBL), GO, BioCyc, Pfam, Enzyme Commission and other sources. The FAT-CAT pipeline uses HMMs at all nodes in PhyloFacts trees to classify user sequences to different levels of functional hierarchies, based on the subtree HMM giving the sequence the strongest score. Phylogenetic placements within orthology groups defined on PhyloFacts trees are used to to predict function and to predict orthologs. Sequences from metagenome projects can be classified taxonomically based on the MRCA of the sequences descending from the top-scoring subtree node. Because of the broad taxonomic and functional coverage, FAT-CAT can identify orthologs and predict function for most sequence inputs. We’re working to make FAT-CAT less computationally intensive so that users will be able to upload entire genomes for analysis; in the interim, we limit users to 20 sequence inputs per day. Registered users are given a higher quota (see details online). We’d love to hear from you if you have feature requests or bug reports; please send any to Kimmen Sjölander – kimmen at berkeley dot edu (parse appropriately). Interesting paper came up in my automated google searches for “phylogenomics”: Transitioning Toward a Universal Species Concept for the Classification of all Organisms | InTechOpen. It is by Jim Staley who has been writing a lot about microbial species concepts in the last few years. In addition to trying to bridge the gap between bacteria/archaea and eukaryotes in terms of species concepts. Not sure how I feel about everything in the paper but it has a really nice history of how species have been defined for bacteria. He breaks down this history into four periods
First of all, how do you spell the thing?? I’ve seen it both ways.. pipet and pipette. I’m thinking it’s pipette because it doesn’t have the red squiggly spelling error sign under it. Just wondering!
Now for the good stuff! We’ve been rocking and rolling in the lab. (Except for the week I came down with the flu) We have so many samples and it would be a bummer to do EVERYTHING (DNA extractions, PCR, Gel confirmation, etc) for every single sample and have disappointing results. While we are optimistic about our results, we are currently preparing samples from the first coral ponds at different time points for sequencing just so we can see how our results look in terms of succession of the microbial community in the pond. If we get cool results (crossing our fingers) we’ll go back to the pipettes and prepare the rest of the samples!
We’ve got a lot of work to do but we are making progress. We are presenting to the lab next Friday about our project. I am really excited to get feedback from experts who know a lot more than me!
This is based off an e-mail I sent recently to a student and someone suggested I post it here:
Asking for letters of recommendation
In general I, and others are happy to write letters of recommendation for people… it’s part of our jobs after all. However, there are some tips I would offer anyone soliciting letters at any stage of their career.
1) Don’t ask me for a letter only a few days before it’s due. This seems like such a simple concept but one that is violated so often.
2) If you ask me for a letter, you need to send a copy of your CV. No matter how long I’ve worked with you, there’s probably still information in there I didn’t know and this helps me write a letter that doesn’t sound like a form letter.
3) Send me a description of the program you’re applying for and why. Again, this helps me write a better letter and doesn’t force me to have to trawl the internet for information
4) Make it as easy as possible for me to write the letter! This is especially critical with professors. If the letter needs to be mailed, you should hand me a stamped, already addressed envelope so all I have to do is drop in a letter and throw it in the outgoing mail. If it’s an electronic form provide me with detailed instructions and links.
5) Don’t attempt to bribe me. I’m not kidding… for example once I got a handwritten request for a letter of recommendation along with $50. This is not a good idea!
(Updated with two more in May 2013)
6) Before asking a post-doc or a project scientist for a letter of recommendation make sure that you don’t actually need one from the professor.
7) Don’t list me as a reference for anything without at least asking first.
Nice commentary / viewpoint piece in PLOS Biology last months: PLOS Biology: Evolutionary Biology for the 21st Century
Citation.Jonathan Losos, Stevan J. Arnold, Gill Bejerano, E. D. Brodie III, David Hibbett, Hopi E. Hoekstra, David P. Mindell, Antónia Monteiro, Craig Moritz, H. Allen Orr, Dmitri A. Petrov, Susanne S. Renner, Robert E. Ricklefs, Pamela S. Soltis, Thomas L. Turner (2013) Evolutionary Biology for the 21st Century. PLoS Biol 11(1): e1001466. doi:10.1371/journal.pbio.1001466
They discuss issues like Biodiversity Informatics (see Figure to the left) and evolutionary applications like evolutionary medicine, food production, sustaining biodiversity, computational algorithms, and justice. They also discuss issues like the oncoming onslaught of specimens and the need to link up with museums who have expertise in dealing with such issues. Anyway – it is worth a look. Not the most visionary of pieces ever but it has some concrete suggestions and predictions that will be of use.
I confess I do not have the time right now to delve into this in detail but this seems of interest: Robust estimation of microbial diversity in theory and in practice. From Bart Haegeman, Jerome Hamelin, John Moriarty, Peter Neal, Jonathan Dushoff and Joshua S. Weitz (full disclosure -I am friends and co-author with some of the authors here).
Abstract: Quantifying diversity is of central importance for the study of struc- ture, function and evolution of microbial communities. The estima- tion of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably es- timate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in compar- ing species richness estimates by applying Chao’s estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics (“Hill diversities”), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao’s estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.
It is in press in ISME and freely available at arXiv.
A few years ago I used to post many things for the Web through Apple’s Mobile Me service. Annoyingly, Apple ended up treating this like they treat connectors and plugs for their phones and Macs. They just decided to move their online system to iCloud and deleted all the old websites through Mobile Me. Which left me in a lurch. And then I forgot about it. But I have been rediscovering how annoying this is since I had a lot of information out there on old papers and projects and now it is gone from the interwebs. So I have ben trying to re-share all of this stuff.
One way has ben to post data from old papers to Figshare. See for example:
But I also had all sorts of website related material that is annoyingly gone. And yesterday I discovered at least a simple solution to this. I can put all my old websites in my Dropbox public folder and share the link to those files with others and they work pretty well.
See for example my re-releasing of some of my April 1 and other joke websites:
Also – I have reposted some of the my old websites
Jonathan Eisen's Lab 