HPOTerm¶

HPOTerm instances contain all relevant information about a single HPO term. They are part of an Ontology and contain links to parental and offspring HPOTerm s.

`HPOTerm`¶

class pyhpo.term.HPOTerm[source]¶

Represents an HPO Term with all metadata

Note

An HPOTerm is initialized as an empty object. Attributes are added line by line from an OBO file

all_parents¶

Set of direct and indirect parent HPOTerms

Note

This property is read-only

Type: set of HPOTerm

children¶

List of direct children HPOTerms

Type: list of HPOTerm

comment¶

Comments from HPO Team

Example:

Multicystic kidney dysplasia is the result of
abnormal fetal renal development in which the affected kidney
is replaced by multiple cysts and has little or no residual
function. The vast majority of multicystic kidneys are unilateral.
Multicystic kidney can be diagnosed on prenatal ultrasound.

Type: str

definition¶

HPO Term Definition

Example:

"Multicystic dysplasia of the kidney is characterized by
multiple cysts of varying size in the kidney and the absence of a
normal pelvicaliceal system. The condition is associated with
ureteral or ureteropelvic atresia, and the affected kidney is
nonfunctional." [HPO:curators]

Warning

The string contains double-quote enclosed sections

Type: str

genes¶

All genes associated with the term or its children

Note

The set is recursively calcualted the first time it is requested by retrieving all children genes as well. The updated set is then cached.

It is not possibe to remove genes from the set. Any updates will only allow addition of new genes.

Warning

Updating the associated gene set causes a recalculation of the cache and the caches of all parents, so this is a quite expensive operation and should be avoided.

Type: set of pyhpo.annotations.Gene

id¶

HPO Term ID

Example:

'HP:0000003'

Type: str

information_content¶

The information content of the HPO term for:

gene: float
omim: float
orpha: float
decipher: float

Example:

{
    'gene': 0.24,
    'omim': 0.84,
    'orpha': 0.43,
    'decipher': 0.12
}

Type: dict

name¶

HPO Term name

Example:

'Abnormality of body height'

Type: str

omim_diseases¶

All OMIM diseases associated with the term or its children

Note

The set is recursively calcualted the first time it is requested by retrieving all children OMIM diseases as well. The updated set is then cached.

It is not possibe to remove OMIM diseases from the set. Any updates will only allow addition of new omim-diseases.

Warning

Updating the associated OMIM disease set causes a recalculation of the cache and the caches of all parents, so this is a quite expensive operation and should be avoided.

Type: set of pyhpo.annotations.Omim

omim_excluded_diseases¶

All OMIM diseases that are excluded from the term

Note

Since excluded diseased do not follow the general model of ontology inheritance, the associated annotations are not inherited from or passed on to parents or children

Type: set of pyhpo.annotations.Omim

orpha_diseases¶

All Orphanet diseases associated with the term or its children

Note

The set is recursively calcualted the first time it is requested by retrieving all children Orphanet diseases as well. The updated set is then cached.

It is not possibe to remove Orphanet diseases from the set. Any updates will only allow addition of new orphanet-diseases.

Warning

Updating the associated Orphanet disease set causes a recalculation of the cache and the caches of all parents, so this is a quite expensive operation and should be avoided.

Type: set of pyhpo.annotations.Orpha

decipher_diseases¶

All Decipher diseases associated with the term or its children

Note

The set is recursively calcualted the first time it is requested by retrieving all children Decipher diseases as well. The updated set is then cached.

It is not possibe to remove Decipher diseases from the set. Any updates will only allow addition of new decipher-diseases.

Warning

Updating the associated Decipher disease set causes a recalculation of the cache and the caches of all parents, so this is a quite expensive operation and should be avoided.

Type: set of pyhpo.annotations.Decipher

parents¶

List of direct parent HPOTerms

Type: list of HPOTerm

synonym¶

List of synonymous names

Example:

['Multicystic dysplastic kidney', 'Multicystic kidneys',
'Multicystic renal dysplasia']

Type: list of str

xref¶

List of xref attributes

Type: list

is_a¶

List of parent HPO terms

Example:

['HP:0000107 ! Renal cyst']

Type: list of str

is_obsolete¶

Indicates if the HPO term is obsolete and should not be used anymore.

Note

Check the replaced_by attribute which HPO term to use instead.

Type: bool

replaced_by¶

Specifies which HPO term to use instead if self is obsolete.

Example:

'HP:0008665'

Warning

It is not guaranteed that this attribute is present - even for obsolete terms.

Type: str (HPOTerm.id)

is_modifier¶

Indicates whether the HPO is a child of a mooifier term. (read only) Modifier terms are specified in HPOTerm._modifier_ids

Mode of inheritance - 'HP:0000005'
Clinical modifier - 'HP:0012823'
Frequency - 'HP:0040279'
Clinical course - 'HP:0031797'
Blood group - 'HP:0032223'
Past medical history - 'HP:0032443'

Type: bool

_index¶

Integer representation of ID

Example:

Type: int

parent_of¶

HPOTerm.parent_of(other: pyhpo.term.HPOTerm) → bool[source]¶

Checks if self is a direct or indirect parent of other.

Parameters: other (HPOTerm) – HPOTerm to check for lineage dependency
Returns: Is the HPOTerm a direct or indirect parent of another HPOTerms
Return type: bool

child_of¶

HPOTerm.child_of(other: pyhpo.term.HPOTerm) → bool[source]¶

Checks if self is a direct or indirect child of other.

Parameters: other (HPOTerm) – HPOTerm to check for lineage dependency
Returns: Is the HPOTerm a direct or indirect child of another HPOTerms
Return type: bool

parent_ids¶

HPOTerm.parent_ids() → List[int][source]¶

List of IDs of parent HPO Terms

Returns: All ids of the direct parents
Return type: list of int

common_ancestors¶

HPOTerm.common_ancestors(other: pyhpo.term.HPOTerm) → Set[pyhpo.term.HPOTerm][source]¶

Identifies all common ancestors of two HPO terms

Parameters: other (HPOTerm) – Target HPO term for path finding
Returns: Set of common ancestor HPOTerms
Return type: set

count_parents¶

HPOTerm.count_parents() → int[source]¶

Calculates total number of ancestral HPO Terms

Returns: The number of all ancestral HPO Terms
Return type: int

longest_path_to_root¶

HPOTerm.longest_path_to_root() → int[source]¶

Calculates the longest path to root

Returns: Maximum number of nodes until the root HPOTerm
Return type: int

shortest_path_to_root¶

HPOTerm.shortest_path_to_root() → int[source]¶

Calculates the shortest path to root

Returns: Minimum number of nodes until the root HPOTerm
Return type: int

shortest_path_to_parent¶

HPOTerm.shortest_path_to_parent(other: pyhpo.term.HPOTerm) → Tuple[Union[int, float], Optional[Tuple[pyhpo.term.HPOTerm, …]]][source]¶

Calculates the shortest path to another HPO Term

Parameters

other (HPOTerm) – parent HPOTerm instance

Returns

int – Minimum number of nodes until the specified HPOTerm

(float(‘inf’) if other is not a parent.)
tuple – Tuple of all HPOTerm instances on the path

(None if other is not a parent)

longest_path_to_bottom¶

HPOTerm.longest_path_to_bottom(level: int = 0) → int[source]¶

Calculates how far the most distant child is apart

Parameters: level (int) – Offset level to indicate for calculation Default: 0
Returns: Number of steps to most distant child
Return type: int

path_to_other¶

HPOTerm.path_to_other(other: pyhpo.term.HPOTerm) → Tuple[int, Tuple[pyhpo.term.HPOTerm, …], int, int][source]¶

Identifies the shortest connection between two HPO terms

Parameters

other (HPOTerm) – Target HPO term for path finding

Returns

int – Length of path
tuple – Tuple of HPOTerms in the path
int – Number of steps from term-1 to the common parent
int – Number of steps from term-2 to the common parent

hierarchy¶

HPOTerm.hierarchy() → Tuple[Tuple[pyhpo.term.HPOTerm, …], …][source]¶

Calculates all paths from current term to Root term and returns each path as a Tuple of HPOTerms

Note

This function is expensive. To ensure better performance, the result is cached and all subsequent calls utilize the cache. Don’t call hierarchy before the Ontology is fully built with all items.

Returns: Tuple of paths. Each path is another tuple made up of HPOTerms
Return type: tuple of tuple of HPOTerm s

print_hierarchy¶

HPOTerm.print_hierarchy(indent: int = 0, indent_increase: int = 2) → None[source]¶

Prints hierarchy diagram of current and all ancestral HPO Terms

Parameters

indent (int) – Number of spaces for current indentation level
indent_increase (int) – Number of spaces to increase the next indentation level

Returns

Return type

None

similarity_score¶

HPOTerm.similarity_score(other: pyhpo.term.HPOTerm, kind: str = '', method: str = '') → float[source]¶

According to Robinson et al, American Journal of Human Genetics, (2008) and Resnik et at, Proceedings of the 14th IJCAI, (1995)

Parameters

kind (str, default omim) –
Which kind of information content should be calculated.

Available option:
- omim (Default)
- orpha
- decipher
- gene
method (string, default resnik) –
The method to use to calculate the similarity.

Available options:
- resnik - Resnik P, Proceedings of the 14th IJCAI, (1995)
- lin - Lin D, Proceedings of the 15th ICML, (1998)
- jc - Jiang J, Conrath D, ROCLING X, (1997) Implementation according to R source code
- jc2 - Jiang J, Conrath D, ROCLING X, (1997) Implementation according to paper from R hposim library Deng Y, et. al., PLoS One, (2015)
- rel - Relevance measure - Schlicker A, et.al., BMC Bioinformatics, (2006)
- ic - Information coefficient - Li B, et. al., arXiv, (2010)
- graphic - Graph based Information coefficient - Deng Y, et. al., PLoS One, (2015)
- dist - Distance between terms

Returns

The similarity score of the two terms.

Return type

float

toJSON¶

HPOTerm.toJSON(verbose: bool = False) → Dict[source]¶

Creates a JSON-like object of the HPOTerm

Parameters: verbose (bool, default False) – Include extra properties
Returns: A dictionary with the main properties of the HPOTerm
Return type: dict

Example:

>>> terms[2].toJSON()
{
    'name': 'Abnormality of body height',
    'id': 'HP:0000002',
    'int': 2
}

>>> terms[2].toJSON(verbose=True)
{
    'name': 'Abnormality of body height',
    'synonym': ['Abnormality of body height'],
    'comment': None,
    'def': '"Deviation from the norm of height with respect [...]',
    'xref': ['UMLS:C4025901'],
    'is_a': ['HP:0001507 ! Growth abnormality'],
    'id': 'HP:0000002',
    'int': 2
}

Class methods¶

id_from_string¶

static HPOTerm.id_from_string(hpo_string: str) → int[source]¶

Formats the HPO-type Term-ID into an integer id

Parameters

hpo_string (str) –

HPO term ID.

(e.g.: HP:000001)

Returns

Integer representation of provided HPO ID

(e.g.: 1)

Return type

int

parse_synonym¶

static HPOTerm.parse_synonym(synonym: str) → str[source]¶

Extracts the synonym from the synonym data line in the obo file format

Parameters

synonym (str) –

value part of synonym-data line of obo file

e.g: “Multicystic dysplastic kidney” EXACT []

Returns

Actual synonym title

e.g.: Multicystic dysplastic kidney

Return type

str