Method to infer PTM (currently only phosphorylation) hotspots in conserved protein alignments based on (Strumillo et al. bioRxiv).

ptm_hotspot requires Python (v3) as well as the following packages:

• numpy
• pandas
• scipy
• statsmodels

If you want to predict all hotspots in all protein domains just run:

python3 ptm_hotspots.py -o predicted_hotspots.csv

To obtain particular domain predictions:

python3 ptm_hotspots.py -o kinase_domain_hotspots.csv -d PF00069

To obtain hotspot residue predictions instead of hotspot ranges

python3 ptm_hotspots.py -o hotspot_residues.csv --printSites

You can obtain more help and options by typing:

python3 ptm_hotspots.py -h

usage: ptm_hotspots.py [-h] [--dir [PATH]] [--ptmfile [PATH]] [-d [PFXXXXX]]
					   [--iter [INTEGER]] [--threshold [FLOAT]]
					   [--foreground [FLOAT]] -o PATH [--printSites]

Estimate PTM hotspots in sequence alignments

optional arguments:
  -h, --help            show this help message and exit
  --dir [PATH]          fasta alignments dir (default: db/alignments)
  --ptmfile [PATH]      file containing PTMs (default: db/all_phosps)
  -d [PFXXXXX], --domain [PFXXXXX]
						query single domain (i.e. PF00069)
  --iter [INTEGER]      number of permutations (default: 100)
  --threshold [FLOAT]   Corrected p-value threshold (default: 0.01)
  --foreground [FLOAT]  effect-size foreground cutoff (default: 2)
  -o PATH, --out PATH   output csv file
  --printSites          print all residue predictions

Note: Since the Bonferroni correction depends on the total number of predictions, small disimilarities might emerge in the same domain hotspots depending on whether you run only a domain or the full set of domains. Similarly, the stochastic nature of the permutation analysis might make the results vary between runs.

By default ptm_hotspot uses a database containing precalculated domain alignments (as described in Strumillo et al.) as well as a collection of phosphorylated residues derived from public high-throughput mass spectrometry experiments. In order to update the database please consider the next points:

Every alignment file should be in FASTA format and the header should contain the start and the end of the domains in the alignment coordinates separated by ";". For example:

>EDP05298 pep:known supercontig:v3.1:DS4 ;51;337

For full protein predictions just include the first and last positions in the multiple sequence alignment.

The ptm database should be included as a csv file containing id, amino acid and position of the phosphosite within the protein.

• Strumillo, M. J., Oplova, M., Viéitez, C., Ochoa, D., Shahraz, M., Busby, B. P., et al. Sopko, M., Studer, R. A., Perrimon, N., Panse, V. G., Beltrao, P. (2018). Conserved phosphorylation hotspots in eukaryotic protein domain families. bioRxiv. https://doi.org/10.1101/391185