HMMSEARCH

https://img.shields.io/github/issues-pr/snakemake/snakemake-wrappers/bio/hmmer/hmmsearch?label=version%20update%20pull%20requests

search profile(s) against a sequence database

Example

This wrapper can be used in the following way:

rule hmmsearch_profile:
    input:
        fasta="test-protein.fa",
        profile="test-profile.hmm.h3f",
    output:
        # only one of these is required
        tblout="test-prot-tbl.txt", # save parseable table of per-sequence hits to file <f>
        domtblout="test-prot-domtbl.txt", # save parseable table of per-domain hits to file <f>
        alignment_hits="test-prot-alignment-hits.txt", # Save a multiple alignment of all significant hits (those satisfying inclusion thresholds) to the file <f>
        outfile="test-prot-out.txt", # Direct the main human-readable output to a file <f> instead of the default stdout.
    log:
        "logs/hmmsearch.log"
    params:
        evalue_threshold=0.00001,
        # if bitscore threshold provided, hmmsearch will use that instead
        #score_threshold=50,
        extra="",
    threads: 4
    wrapper:
        "v3.8.0-49-g6f33607/bio/hmmer/hmmsearch"

Note that input, output and log file paths can be chosen freely.

When running with

snakemake --use-conda

the software dependencies will be automatically deployed into an isolated environment before execution.

Software dependencies

  • hmmer=3.4

Input/Output

Input:

  • hmm profile(s)

  • sequence database

Output:

  • matches between sequences and hmm profiles

Authors

  • N Tessa Pierce

Code

"""Snakemake wrapper for hmmsearch"""

__author__ = "N. Tessa Pierce"
__copyright__ = "Copyright 2019, N. Tessa Pierce"
__email__ = "ntpierce@gmail.com"
__license__ = "MIT"

from os import path
from snakemake.shell import shell

profile = snakemake.input.get("profile")

profile = profile.rsplit(".h3", 1)[0]
assert profile.endswith(".hmm"), 'your profile file should end with ".hmm" '

# Direct the main human-readable output to a file <f> instead of the default stdout.
out_cmd = ""
outfile = snakemake.output.get("outfile", "")
if outfile:
    out_cmd += " -o {} ".format(outfile)

# save parseable table of per-sequence hits to file <f>
tblout = snakemake.output.get("tblout", "")
if tblout:
    out_cmd += " --tblout {} ".format(tblout)

# save parseable table of per-domain hits to file <f>
domtblout = snakemake.output.get("domtblout", "")
if domtblout:
    out_cmd += " --domtblout {} ".format(domtblout)

# Save a multiple alignment of all significant hits (those satisfying inclusion thresholds) to the file <f>
alignment_hits = snakemake.output.get("alignment_hits", "")
if alignment_hits:
    out_cmd += " -A {} ".format(alignment_hits)

## default params: enable evalue threshold. If bitscore thresh is provided, use that instead (both not allowed)
# report models >= this score threshold in output
evalue_threshold = snakemake.params.get("evalue_threshold", 0.00001)
score_threshold = snakemake.params.get("score_threshold", "")

if score_threshold:
    thresh_cmd = " -T {} ".format(float(score_threshold))
else:
    thresh_cmd = " -E {} ".format(float(evalue_threshold))

# all other params should be entered in "extra" param
extra = snakemake.params.get("extra", "")

log = snakemake.log_fmt_shell(stdout=False, stderr=True)

shell(
    " hmmsearch --cpu {snakemake.threads} "
    " {out_cmd} {thresh_cmd} {extra} {profile} "
    " {snakemake.input.fasta} {log}"
)