skbio.sequence.RNA#

class skbio.sequence.RNA(sequence, metadata=None, positional_metadata=None, interval_metadata=None, lowercase=False, validate=True)[source]#

Store RNA sequence data and optional associated metadata.

Parameters:
sequencestr, Sequence, or 1D np.ndarray (np.uint8 or ‘|S1’)

Characters representing the RNA sequence itself.

metadatadict, optional

Arbitrary metadata which applies to the entire sequence.

positional_metadataPandas DataFrame consumable, optional

Arbitrary per-character metadata. For example, quality data from sequencing reads. Must be able to be passed directly to the Pandas DataFrame constructor.

interval_metadataIntervalMetadata

Arbitrary metadata which applies to intervals within a sequence to store interval features (such as exons or introns on the sequence).

lowercasebool or str, optional

If True, lowercase sequence characters will be converted to uppercase characters in order to be valid IUPAC RNA characters. If False, no characters will be converted. If a str, it will be treated as a key into the positional metadata of the object. All lowercase characters will be converted to uppercase, and a True value will be stored in a boolean array in the positional metadata under the key.

validatebool, optional

If True, validation will be performed to ensure that all sequence characters are in the IUPAC RNA character set. If False, validation will not be performed. Turning off validation will improve runtime performance. If invalid characters are present, however, there is no guarantee that operations performed on the resulting object will work or behave as expected. Only turn off validation if you are certain that the sequence characters are valid. To store sequence data that is not IUPAC-compliant, use Sequence.

Notes

According to the IUPAC RNA character set [1] , an RNA sequence may contain the following four definite characters (canonical nucleotides):

Code

Nucleobase

A

Adenine

C

Cytosine

G

Guanine

U

Uracil

Plus 11 degenerate characters: R, Y, S, W, K, M, B, D, H, V and N, and two gap characters: - and .. The definitions of degenerate characters are provided in DNA, in which T should be replaced with U for RNA sequences.

Characters other than the above 17 are not allowed. To include additional characters, you may create a custom alphabet using GrammaredSequence. Directly modifying the alphabet of RNA may break methods that rely on the IUPAC alphabet.

It should be noted that some functions do not support degenerate characters characters. In such cases, they will be replaced with N to represent any of the canonical nucleotides.

References

[1]

Nomenclature for incompletely specified bases in nucleic acid sequences: recommendations 1984. Nucleic Acids Res. May 10, 1985; 13(9): 3021-3030. A Cornish-Bowden

Examples

>>> from skbio import RNA
>>> RNA('ACCGAAU')
RNA
--------------------------
Stats:
    length: 7
    has gaps: False
    has degenerates: False
    has definites: True
    GC-content: 42.86%
--------------------------
0 ACCGAAU

Convert lowercase characters to uppercase:

>>> RNA('AcCGaaU', lowercase=True)
RNA
--------------------------
Stats:
    length: 7
    has gaps: False
    has degenerates: False
    has definites: True
    GC-content: 42.86%
--------------------------
0 ACCGAAU

Attributes

alphabet

Return valid characters.

complement_map

Return mapping of nucleotide characters to their complements.

default_gap_char

Gap character to use when constructing a new gapped sequence.

default_write_format

definite_chars

Return definite characters.

degenerate_chars

Return degenerate characters.

degenerate_map

Return mapping of degenerate to definite characters.

gap_chars

Return characters defined as gaps.

interval_metadata

IntervalMetadata object containing info about interval features.

metadata

dict containing metadata which applies to the entire object.

noncanonical_chars

Return non-canonical characters.

nondegenerate_chars

Return non-degenerate characters.

observed_chars

Set of observed characters in the sequence.

positional_metadata

pd.DataFrame containing metadata along an axis.

values

Array containing underlying sequence characters.

wildcard_char

Return wildcard character.

Built-ins

__bool__()

Return truth value (truthiness) of sequence.

__contains__(subsequence)

Determine if a subsequence is contained in this sequence.

__copy__()

Return a shallow copy of this sequence.

__deepcopy__(memo)

Return a deep copy of this sequence.

__eq__(other)

Determine if this sequence is equal to another.

__ge__(value, /)

Return self>=value.

__getitem__(indexable)

Slice this sequence.

__getstate__(/)

Helper for pickle.

__gt__(value, /)

Return self>value.

__iter__()

Iterate over positions in this sequence.

__le__(value, /)

Return self<=value.

__len__()

Return the number of characters in this sequence.

__lt__(value, /)

Return self<value.

__ne__(other)

Determine if this sequence is not equal to another.

__reversed__()

Iterate over positions in this sequence in reverse order.

__str__()

Return sequence characters as a string.

Methods

complement([reverse])

Return the complement of the nucleotide sequence.

concat(sequences[, how])

Concatenate an iterable of Sequence objects.

count(subsequence[, start, end])

Count occurrences of a subsequence in this sequence.

definites()

Find positions containing definite characters in the sequence.

degap()

Return a new sequence with gap characters removed.

degenerates()

Find positions containing degenerate characters in the sequence.

distance(other[, metric])

Compute the distance to another sequence.

expand_degenerates()

Yield all possible definite versions of the sequence.

find_motifs(motif_type[, min_length, ignore])

Search the biological sequence for motifs.

find_with_regex(regex[, ignore])

Generate slices for patterns matched by a regular expression.

frequencies([chars, relative])

Compute frequencies of characters in the sequence.

gaps()

Find positions containing gaps in the biological sequence.

gc_content()

Calculate the relative frequency of G's and C's in the sequence.

gc_frequency([relative])

Calculate frequency of G's and C's in the sequence.

has_definites()

Determine if sequence contains one or more definite characters.

has_degenerates()

Determine if sequence contains one or more degenerate characters.

has_gaps()

Determine if the sequence contains one or more gap characters.

has_interval_metadata()

Determine if the object has interval metadata.

has_metadata()

Determine if the object has metadata.

has_nondegenerates()

Determine if sequence contains one or more non-degenerate characters.

has_positional_metadata()

Determine if the object has positional metadata.

index(subsequence[, start, end])

Find position where subsequence first occurs in the sequence.

is_reverse_complement(other)

Determine if a sequence is the reverse complement of this sequence.

iter_contiguous(included[, min_length, invert])

Yield contiguous subsequences based on included.

iter_kmers(k[, overlap])

Generate kmers of length k from this sequence.

kmer_frequencies(k[, overlap, relative])

Return counts of words of length k from this sequence.

lowercase(lowercase)

Return a case-sensitive string representation of the sequence.

match_frequency(other[, relative])

Return count of positions that are the same between two sequences.

matches(other)

Find positions that match with another sequence.

mismatch_frequency(other[, relative])

Return count of positions that differ between two sequences.

mismatches(other)

Find positions that do not match with another sequence.

nondegenerates()

Find positions containing non-degenerate characters in the sequence.

read(file[, format])

Create a new RNA instance from a file.

replace(where, character)

Replace values in this sequence with a different character.

reverse_complement()

Return the reverse complement of the nucleotide sequence.

reverse_transcribe()

Reverse transcribe RNA into DNA.

to_definites([degenerate, noncanonical])

Convert degenerate and noncanonical characters to alternative characters.

to_indices([alphabet, mask_gaps, wildcard, ...])

Convert the sequence into indices of characters.

to_regex([within_capture])

Return regular expression object that accounts for degenerate chars.

translate([genetic_code])

Translate RNA sequence into protein sequence.

translate_six_frames([genetic_code])

Translate RNA into protein using six possible reading frames.

write(file[, format])

Write an instance of RNA to a file.