Protein domain evolution analysis pipeline

Protein domains are independent sections of protein sequences that can have function distint functions. One of the major ways in which proteins can evolve is through domain insertion/delection/duplication. In this project, we will attempt to build an analysis pipeline that will take in 2 groups of species proteomes and find differences in domain compositions between the two groups. The whole pipeline will be packaged inside a docker container which can executed on any given data in any machine environment.

Inputs

Prepare a data directory with a user-defined name containing following files and directories:

• Proteome fasta file for each species in the directory named fasta. The number of fasta files will depend of which two groups of species the user decides to compare and how many species the user the user wants in each group. It is recommended that there should be atleast 10 species per group to obtain significant results. These can be collected from following databases.

  • Phytozome for plant species
  • Uniprot for any species

• The HMM file containing Pfam domains from Pfam database which contains registry of all the domains found in all the organisms. The HMM file must be processed using hmmpress program to create a HMM database. For more details on how to use the hmmpress tool, please see the HMMER user manual. The Pfam HMM file along with all the HMM pressed file must be present inside the directory named pfam_database.

• A species.label file with two columns species and species_label. The species column contains fasta file names of individual species append by string "pfamscan". The species_label column contains labels (0 or 1) classifying the species in different groups.

Execute the container using user defined datasets

• Pull the docker image from https://hub.docker.com/r/akshayayadav/protein-domain-evolution-project .

docker pull akshayayadav/protein-domain-evolution-project

• Since the data directory is not built into the container, you need to bind mount a volume with the data directory into the container.

docker run -v <path to the data directory>:/data akshayayadav/protein-domain-evolution-project run_analysis.sh -c 10

The number "10" gives the number of cores passed to snakemake to run the analysis.