Summer 2019

From EvoBioLabatHunter
Jump to navigation Jump to search

Rules of Conduct

  1. No eating, drinking, or loud talking in the lab. Socialize in the lobby only.
  2. Be respectful to each other, regardless of level of study
  3. Be on time & responsible. Communicate in advance with the PI if late or absent
  4. No use of phone or laptop during lab meetings

Schedule

conda install numpy
conda install pandas
conda install matplotlib
conda install jupyter
  • June 21 (Fri). Python Tutorial I. Jupyter notebook, string, list, conditions, loops (by Edgar)
  • June 24 (Mon). Python Tutorial II. string functions, function, dictionary, modules (by Edgar)
  • June 26 (Wed). Python Tutorial III. BioPython (Edgar & Muhammud)
  • June 27 (Thur). Paper presentations

Participants

  1. Dr Oliver Attie, Research Associate
  2. Brian Sulkow, Research Associate
  3. Saymon Akther, CUNY Graduate Center, EEB Program
  4. Lily Li, CUNY Graduate Center, EEB Program
  5. Christopher Panlasigui, Hunter Biology
  6. Summer Interns: Muhammad, Radhika Mohan, Oscar Eng, Oliver Cai

Journal Club

  1. a Unix & Perl tutorial
  2. A short introduction to molecular phylogenetics: http://www.ncbi.nlm.nih.gov/pubmed/12801728
  3. A review on Borrelia genomics: https://www.ncbi.nlm.nih.gov/pubmed/24704760
  4. A model of immune selection: He et al (2018). https://www.nature.com/articles/s41467-018-04219-3
  5. A model of flu evolution: Neher et al (2016). https://www.pnas.org/content/113/12/E1701?ijkey=72c6025e999dd043d32f6822dc06c7356d8494b2&keytype2=tf_ipsecsha
  6. Reading on Dengue virus
    1. Bäck & Lundkvist 2013
    2. Overview (from Scitable)

Projects

Project Description/Goal Participants Leader Status/Notes/Weekly report (7/12, 7/19, 7/26)
Lyme genomics phylogeography & genome intragression Saymon, Chris Saymon
Lyme ecology & population genetics host identification; SIR model; coalescence Lily, Chris Lily
Borrelia peptide library Compile ORFs from genome database & send to Mt Sinai team
  • N=17 north american strains selected
  • query script: get_pepseq_anno_for_each_genome.pl -p "B31" or strain ID; -a to get patric annotation
  • Expected outputs: 17 FASTA files; Excel workbook with 17 sheets
Chris, Saymon Chris
Origin of genetic code manuscript revision
  1. Response letter done
  2. Track-change in progress
  3. To do: Reference update; Figure 6 (and legend/text)
Oliver & Brian Oliver
Pseudomonas metabolomics Shiny Web portal development Chris, Edgar Chris
Dengue antigenic variations
  1. Parse Dengue sequences (E & PrM proteins) into data-friendly format: vid (e.g., DENV1_E_0001), strain_name, gene_name
  2. Alignment with MUSCLE & produce 2 alignments, one for E and the other for PrM
  3. Infer tree for each alignment
  4. run GA (DEAP package in python, ask Edgar) to generate centroid
Oliver Cai, Muhammad/Benjamin, Che Muhammad
OspC design

Optimization by GA

  • Identified a sequence with d<=43 to all 16 alleles (using DEAP)
  • also done: write a fitness function to minimize the maximum distance to any of the 16 alleles; run ~10 times
  • output in FASTA file and do a tree (done)
  • To do: minimize Max(d); generate ~10 evolved sequencess
Edgar, Lia Brian
OspC antigenecity model Develop model with mice data by Invanova et al Nevila, Brian Brian
OspC per-site model Quantify per-site importance with likelihood, i.e., Prob{fit->0, given that CW50, site=i}
  1. For allele A, file has been generated at CW50=50
  2. Radhika has turned strings into {0,1}
  3. To do: plot fitness ~ pos
  4. CW50 values: given by Mohammad, estimated by using CW50=-(intercept/slope)
  5. Estimate importance using GA: log(fit) = sum{log(1-p[i])}, with the fitness/error function: error = |log(fit[obs]) - log(fit[simulated])|; using GA to minimize the error; output p[i] as results (importance)
Radhika, Muhammad, Brian Brian
flu implement paper algorithm
  1. plot HI vs Seq.diff, one for each of 15 "refv"
  2. plot HI vs SNP, colored by 0 or 1, with boxplot + jitter
  3. To do: implement Neher et al
  4. Alternatively, generate 0,1 strings and run the "importance" model (see above)
Oscar, Brian Brian