Skip to content

Latest commit

 

History

History
44 lines (32 loc) · 2.47 KB

01-refr-genome-summary.md

File metadata and controls

44 lines (32 loc) · 2.47 KB
Raw

1. Summary of 10 model organism genomes

We selected a diverse set of 10 model organisms to demonstrate the utility of iLoci for providing a descriptive overview of genome content and organization.

Data retrieval, processing

The fidibus script was used to perform the following tasks.

  • retrieve genome assemblied and annotations from NCBI RefSeq (the download task)
  • pre-process the data (the prep task)
  • compute iLoci (the iloci task)
  • collate sequences and annotations for various feature types (the breakdown task)
  • compile tables of summary statistics over the data (the stats task)
fidibus --workdir=data/ \
        --numprocs=4 \
        --refr=Scer,Cele,Crei,Mtru,Agam,Dmel,Xtro,Drer,Mmus,Hsap \
        download prep iloci breakdown stats

This command could take up to an hour to run: go enjoy lunch or read a paper while you wait! You will want to adjust the --numprocs parameter based on the number of available processors on your computer, as processing multiple genomes in parallel will complete the task more quickly. However, the mammalian genomes each take on the order of 30 minutes, so that's about the best runtime that can be expected.

Output data

The fidibus command creates a directory called data/ containing 10 subdirectories, each dedicated to a specific genome. These subdirectories store many intermediate and ancillary data files that will likely be of limited interest to most users. However, several data files should be of great interest.

  • Xxxx.iloci.gff3: full annotation file, with iLoci specified and associated with their constituent gene features
  • Xxxx.miloci.gff3: annotation file containing just iLocus features, with overlapping siLoci and niLoci merged into miLoci
  • Xxxx.yyyy.tsv: statistics calculated on various data types (iLoci, miLoci, pre-mRNAs, mature mRNAs, exons, introns, coding sequences) and compiled into a tabular format for easy loading into R, Python, or similar data analysis environments

iLocus summary

Summaries of iLocus composition for these genomes, corresponding to Tables 1-3 in the manuscript, were computed with the following commands.

genhub-ilocus-summary.py  --workdir=data/ --outfmt=tex Scer Cele Crei Mtru Agam Dmel Xtro Drer Mmus Hsap
genhub-pilocus-summary.py --workdir=data/ --outfmt=tex Scer Cele Crei Mtru Agam Dmel Xtro Drer Mmus Hsap
genhub-milocus-summary.py --workdir=data/ --outfmt=tex Scer Cele Crei Mtru Agam Dmel Xtro Drer Mmus Hsap