Archive for Hubei

Nature snapshots

Posted in Books with tags , , , , , , , , , , , , , , , , , , , , , , , on September 5, 2024 by xi'an

Some quick breakfast reads from the 11 July issue of Nature (the one with the frog cover!),

  • A tribune on the Canadian example of advocating for graduate and postdoc pay raises, with a success last April. It would prove difficult to achieve in a French academic landscape when postdocs here earn about as much as starting lecturers, whose salary is notoriously low.
  • A news article on the UK elections Labour landslide impact on national scientific landscape, with the former Conservatives’ government Chief Adviser and former Head of Research at GlaxoSmithKline and governmental speaker during the COVID crisis appointed as science minister (how many countries enjoy a science ministry?!) But Labour has shown no inclination to back up (from the former stance) on EU collaborations (no Erasmus!), restrictions on students visa that induced a 40% drop in overseas enrolments, or funding of UK universities (whose finances are in a terrible state). Followed by a call from five UK researchers to “give UK science the overhaul it urgently needs¨.
  • A paper about identifying brain cells attached to a word’s meaning (with an example opposing son and Sun that reminded me of the confusion I had with the Taïwanese movie A Sun!)
  • An another paper on an analysis of January 2020 data collected in the Huanan seafood market in Wuhan, with three virus identified. But inconclusive about the origin of the virus.
  • A work column on the challenges of conservation ecology, with trade-offs between intervention and inaction for endangered species (with the nugget of information that Ecuador gives nature constitutional rights).
  • And a back page on the TIGRR lab [great acronym!] in Melbourne attempt at resurrecting the extinct thyalacine (or Tasmanian tiger) from historical specimens, not mentioning the involvement of a biotech company, Colossal Biosciences, also involved in recreating  mammoths. Which sounds counterproductive beyond the bioengineering feat, esp. with regard to the mammoths, which would be woolly (!) unsuited to the current World (except in some remote corner of Siberia?!) and its climate. When considering how challenging protecting the few remaining African elephants is, imaging free roaming mammoths that would not come to clash with human activities beggars belief.

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Bayesian phylogeographic inference of SARS-CoV-2

Posted in Books, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , , , on December 14, 2020 by xi'an

Nature Communications of 10 October has a paper by Philippe Lemey et al. (incl. Marc Suchard) on including travel history and removing sampling bias on the study of the virus spread. (Which I was asked to review for a CNRS COVID watch platform, Bibliovid.)

The data is made of curated genomes available in GISAID on March 10, that is, before lockdown even started in France. With (trustworthy?) travel history data for over 20% of the sampled patients. (And an unwelcome reminder that Hong Kong is part of China, at a time of repression and “mainlandisation” by the CCP.)

“we model a discrete diffusion process between 44 locations within China, including 13 provinces, one municipality (Beijing), and one special administrative area (Hong Kong). We fit a generalized linear model (GLM) parameterization of the discrete diffusion process…”

The diffusion is actually a continuous-time Markov process, with a phylogeny that incorporates nodes associated with location. The Bayesian analysis of the model is made by MCMC, since, contrary to ABC, the likelihood can be computed by Felsenstein’s pruning algorithm. The covariates are used to calibrate the Markov process transitions between locations. The paper also includes a posterior predictive accuracy assessment.

“…we generate Markov jump estimates of the transition histories that are averaged over the entire posterior in our Bayesian inference.”

In particular the paper describes “travel-aware reconstruction” analyses that track the spatial path followed by a virus until collection, as below. The top graph represents the posterior probability distribution of this path.Given the lack of representativity, the authors also develop an additional “approach that adds unsampled taxa to assess the sensitivity of inferences to sampling bias”, although it mostly reflects the assumptions made in producing the artificial data. (With a possible connection with ABC?). If I understood correctly, they added 458 taxa for 14 locations,

An interesting opening made in the conclusion about the scalability of the approach:

“With the large number of SARS-CoV-2 genomes now available, the question arises how scalable the incorporation of un-sampled taxa will be. For computationally expensive Bayesian inferences, the approach may need to go hand in hand with down-sampling procedures or more detailed examination of specific sub-lineages.”

In the end, I find it hard, as with other COVID-related papers I read, to check how much the limitations, errors, truncations, &tc., attached with the data at hand impact the validation of this philogeographic reconstruction, and how the model can help further than reconstructing histories of contamination at the (relatively) early stage.

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