Repository for Data in "Membrane environment imposes unique selection pressures on transmembrane domains of G-protein coupled receptors"
Python
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
InitialGeneSet
dssp_files
guidance_aln_nuc
guidance_aln_prot
hyphy
partitioned_alignments
structures
trees
unaligned_sequences
.gitignore
README.md

README.md

Repository for Data in "Membrane environment imposes unique selection pressures on transmembrane domains of G-protein coupled receptors"

Contents of repository

Of primary interest are alignments and trees:

  • guidance_aln_nuc/ and guidance_aln_prot/ contain respectively codon and amino-acid alignments (they correspond), with sites filtered based on Guidance algorithm

  • unaligned_sequences/ contain raw sequences (unaligned fasta files) for each ortholog

  • trees/ contains all RAxML-inferred trees. All files "*bl_bs.tre" contain bootstrap and branch lengths, whereas other files are just topology

  • structures/ contains transmembrane predictions for GPCRHMM

  • partitioned_alignments/ contains same data as in guidance_aln_nuc/ except partitioned into extramembrane and transmembrane, based on predictions found in structures/. Files named as:

    • *_extra.fasta are extramembrane (intra and extracellular) domains
    • *_inner.fasta are intracellular domains
    • *_outer.fasta are extracellular domains
    • *_trans.fasta are transmembrane domains
    • *_genome.fasta are full sequences (ie unpartitioned)

Other contents:

  • InitialGeneSet/ contains Ensembl and GO annotations for original data collection. Note, many of these sequences end up not being used because they were not GPCRs.
  • dssp_files/ contains structural information predicted with DSSP for known GPCR structures in this study
  • hyphy/ contains results summaries for models tested, including AIC for no partitioning (null_results.txt), AIC for 2 vs 3 partition schemes (2vs3_partitions_results.txt) and mean evo rates using best model (rel_results.txt)