Phenoscape Journal Club

1st Friday of the month, 2:30-3:30 eastern

Connection info

Zoom: https://renci.zoom.us/j/929124809
US phone toll free: 877.853.5257, 855.880.1246
US phone not toll free: 669 900 6833, 646.558.8656
International #'s": https://renci.zoom.us/zoomconference?m=pZZ0jdZAKrL_L2SZsyjJ1rn04r0jrDVv
Meeting ID: 929 124 809

Papers available on Paperpile

Sign up

Suggestions for next time:

2020

  • May 1 - Predicting candidate genes from phenotypes, functions, and anatomical site of expression. Jun Chen, Azza Althagafi, Robert Hoehndorf https://doi.org/10.1101/2020.03.30.015594

  • April 3 - A. Martin (NIH proposal) The loci of evolution: integrating knowledge about the genomic targets of phenotypic variation across Eukaryotes. Posted to Slack, with reviews.

  • March 6 - Diego - Lewis et al (2016) Estimating Bayesian Phylogenetic Information Content. Systematic Biology, 65, 1009. https://doi.org/10.1093/sysbio/syw042

    • Diego interested in using the measure of Dissonance (D) proposed here
    • Hypothesis: D will be 'correlated' with semantic distance
    • Problem: method only scales to ~20 taxa because the clades have to be enumerated
    • Diego interested in measuring these stats not over probability of trees but over probability of change on a branch (eg from a stochastic map) - as a way to detect clusters of characters changing at similar places on the tree

2019

2018

Notes

March 6, 2020

  • Lewis et al (2016) Estimating Bayesian
  • Entropy: measure of uncertainty in a system; here, compare prior and posterior distributions
  • measure how much conflict there is in partitions of the data (gene tree example in paper)
  • run analysis with subsets of data, prior is the same, get posterior distribution for each partition
    • if those partitions agree, will have similar posterior distributions and entropy will be lower
    • if not …entropy will be higher
  • size of partition matters for ?
  • will dissonance positively correlate with semantic distance?
    • lower dissonance between two clusters of characters with high semantic similariy
  • caveats: limited by number of taxa; 20 taxa upper limit with taxa that have good coverage
    • missing data: up to 50% might be OK
    • having small matrix to maximize taxa and traits

May 3, 2019

  • Ochoterena et al (2019) The search for common origin: homology revisited https://academic.oup.com/sysbio/advance-article/doi/10.1093/sysbio/syz013/5364027
  • What is their goal for establishing homology? Phylogenetic inference, defining clades, which may lead to some disconnect with our own concerns.
  • Discussion of levels of organization (ontogenetic, population , species) and their proposal that homology must be concordant among them.
  • Discussion of relevance of the idea of paralogy to morphological traits
  • what is the appropriate state space for phenotypes? we are trying to code phenotypes in that space of genetic/developmental networks but we will never be able to do so perfectly.
  • does xenology preclude homology? doesn't seem like it needs to.
  • how does it relate to ontological issues?

Mar 1, 2019

  • Tarasov et al. preprint:
  • extracting presence/absence dependencies should be in place in time for workshop
  • description of how algorithm works should be documented where?
    • currently the algorithm is in OWL

Feb 1, 2019

  • Endara et al 2018 https://doi.org/10.3897/BDJ.6.e29232
  • Some discussion questions (from Todd)
    • Will this help reasoning escape from the implicit assumption of a normal and abnormal phenotype?
    • How should position along a list be incorporated into semantic similarity?
    • What would be the arguments for the open world form of the modifier ontology?
    • Have we been misusing PATO, etc to serve as modifiers in the absence of these classes?

Vogt 2018

Some interesting points (very rough notes from Todd):

  • Paula makes the observation that the debate over the merits of atomizing anatomy into characters echoes a debate w/ "Berkeley school" of comparative morphology from her graduate days
  • Would be interesting to see seeing whether use of a whole instance graph would lead to different max parsimony reconstructions than individual analysis of each ontologized character.
  • In Vogt's approach, what a matrix would list as different characters could, in principle, be interdependent in Vogt's analysis (and hopefully reflective of integration in the organism)
  • Might be able to test Vogt's idea with 'monograph to matrix', Andy Dean's wasp, or Laura J's fish dataset.
  • Does Vogt's proposal really escape the assumptions of primary homology in phylo. analysis, or does annotation with common ontology terms mean the same thing in practice?
  • Similarly, is the ontology taking on some of the burden of character state delimitation in Vogt's approach (as opposed to escaping the necessity of that step)
  • Some interesting parallels between Tarasov preprint (from previous jclub) & Vogt
Select a repo