Initially forked from here. Thank you to the awesome binder team!
Part of the Bioinformatics Virtual Coordination Network :)
Run phmmer on the Cyc1 fasta file
phmmer -A Cyc1.refseq.msa --tblout Cyc1.refseq.tblout -E 1E-20 Cyc1.faa ../refseq_db/refseq_nr.sample.faa
Build HMM file from MSA (multiple sequence alignment) file, using hmmbuild
hmmbuild Cyc1.hmm Cyc1.refseq.msa
Query the Cyc1 HMM file against refseq database sample
hmmsearch --tblout Cyc1.hmm.refseq.tblout Cyc1.hmm ../refseq_db/refseq_nr.sample.faa
Examine the output file. What do the bit scores look like for likely false positives
less Cyc1.hmm.refseq.tblout
Move into directory containing MtrA FASTA file, and create an alignment using Muscle.
muscle -in MtrA.faa -out MtrA.fa
Build HMM file from MSA (multiple sequence alignment) file, using hmmbuild
hmmbuild MtrA.hmm MtrA.fa
Query the MtrA HMM file against refseq database sample
hmmsearch --tblout MtrA.hmm.nr.tblout MtrA.hmm ../refseq_db/refseq_nr.sample.faa
Examine the output file. What do the bit scores look like for likely false positives
less MtrA.hmm.nr.tblout
Move the HMM files into a single directory
mv MtrA.hmm ../HMMs/
mv Cyc1.hmm ../HMMs/
Check out the Pfam-derived HMM and bitscores.txt file
less Catalase.hmm
Run HmmGenie (MagicLamp) on test dataset using the new HMM collection
MagicLamp.py HmmGenie -hmm_dir HMMs/ -hmm_ext hmm -bin_dir test_data/ -bin_ext txt -out hmmgenie_out -eval 1E-1
MagicLamp.py HmmGenie -hmm_dir HMMs/ -hmm_ext hmm -bin_dir test_data/ -bin_ext txt -out hmmgenie_out -bit HMMs/bitscores.txt
MagicLamp.py HmmGenie -hmm_dir HMMs/ -hmm_ext hmm -bin_dir test_data/ -bin_ext txt -out hmmgenie_out -bit HMMs/bitscores.txt -clu 2