gbru_planning

primary

• Salmonella graph

  • determine node coverage of xmfa vs pggb_5 vs pggb_250
    • make table of "node,length,reads,num_reads_covering"
  • Test different SPAdes parameters with simulated reads: k 21,33,55
    • Coverage distribution of assembled contigs
    • Get alignments, view in tubemaps - specifically nodes that don't align
  • Compare graph with BWA
    • Take simulated reads of the 4 non-ref genomes -> assemble -> align to the source genome (CP004027.1) - uncovered areas comparable to source genome simulations?
    • How much of CP004027.1 is not covered when you align the same assembled simulated reads to it with BWA? Compare to GraphAligner
      • Some reads are legitimately unmapped in both. Might just be missing in simulated set. Need to simulate more reads.
        • Simulating more reads (1M/direction) showed 100% coverage in same-ref, with ~ 20kbp missing in MEM mode of GA.
    • profile the reads missing in 5,10,15,20,25 line graph
  • Write up all above results

• Genesieve

  • Obtain the Arabidopsis QTL data
    1. Get all associations by paging thru 25/100/1000 at a time, increasing offset to get next page
    2. Get the phenotype desc with JSON parser
    3. Get the SNP Chr/location with JSON parser
    4. Write it down
    5. For each study...
       • Collect all SNPs
       • If many on one chromosome, do k-means of like 2 or 3
       • get k-means boundaries by sorting clusters, get centroid +-50kbp
       • use those as coordinates, obtain genes from gff
  • Complete functionality testing on rice test set
    • Fix genesieve env on genesieve server: numpy/gensim incompatibility issue
    • Run full pipeline tests with hardcoded data
  • Test and validate SQL queries
    • incorporate into genesieve.py when finished
  • Fix issue with QTL <-> coexpression linking (line ~123 of genesieve)
  • Create a validation test
    • Using our test set, pull regions (~300kbp either side?) around "true" genes. Generate distribution of scores. Where is the 'true' gene? Now generate a random region with a random trait. What's that distribution? How do they differ? "true" value minus the median of the "false" values
    • Homology: what if there are tandem dupes? How many validated genes have tandem dupes/copies conflating results? see how many - if it's like 50% then mask them in test set
      • Check to see how often a validated candidate gene has duplicated genes next to/near it in the ~500kbp either side region.

secondary

• Gold fungus project
  • Re-run alignment & variant calling with recurrent parental line included as genotype, produce new figure