Tutorial: Profile HMMs and HHpred I/O

Hidden Markov Model API

The csb.bio.hmm package defines abstractions for working with HHpred’s HMMs and hit lists. ProfileHMM is the most important object of this module. It describes a sequence profile hidden Markov model in the way HHpred sees this concept:

• a profile is composed of a list of HMMLayers, which contain a number of States
• these States can be of different types: Match, Insertion, Deletion, etc.
• a profile contains a multiple alignment, from which it is derived
• this multiple alignment is an A3M (condensed) Alignment, where the first sequence is a master sequence
• the match states in all layers correspond to the residues of the master sequence

ProfileHMM objects provide list-like access to their layers:

>>> hmm.layers[1](1)
<HMMLayer>    # first layer: layer at master residue=1

Every layer provides dictionary-like access to its states:

>>> layer[States.Match](States.Match)
<Match State>

and every state provides dictionary-like access to its transitions to other states:

>>> state = hmm.layers[1](1)[States.match](States.match)
>>> state.transitions[States.Insertion](States.Insertion)
<Transition>       # Match > Insertion
>>> transition.predecessor
<Match State>      # source state
>>> transition.successor
<Insertion State>  # target state

Whether this transition points to a state at the same (i) or the next layer (i+1) depends on the semantics of the source and the target states. Building HMMs from scratch is supported through a number of append methods at various places:

>>> layer = HMMLayer(...)
>>> layer.append(State(...))
>>> hmm.layers.append(layer)

See HMMLayersCollection, HMMLayer, EmissionTable and TransitionTable in our API docs for details.

HHpred I/O

CSB provides python bindings for working with HHpred’s .hhm (HMM) and .hhr (HHsearch result) files. These are part of the csb.bio.io.hhpred module, which exposes two HHpred format parsers: HHProfileParser and HHOutputParser. The first one is used to read HMM (.hhm) files:

>>> HHProfileParser("profile.hhm", "profile.pdb").parse()
<ProfileHMM>            # ProfileHMM object

while the latter parses HHsearch results files (.hhr):

>>> HHOutputParser().parse_file("hits.hhr"):
<HHpredHitList>        # collection of HHpredHit-s

See ProfileHMM, HHpredHitList and HHpredHit from csb.bio.hmm for details. For text serialization of HMM profiles, see HHMFileBuilder from csb.bio.io.hhpred in our API docs.