Loading nucleotide, protein sequences¶
LoadSeqs
from a file¶
As an alignment¶
The function LoadSeqs()
creates either a sequence collection or an alignment depending on the keyword argument aligned
(the default is True
).
>>> from cogent import LoadSeqs, DNA
>>> aln = LoadSeqs('data/long_testseqs.fasta', moltype=DNA)
>>> type(aln)
<class 'cogent.core.alignment.Alignment'>
This example and some of the following use the long_testseqs.fasta
file.
As a sequence collection (unaligned)¶
Setting the LoadSeqs()
function keyword argument aligned=False
returns a sequence collection.
>>> from cogent import LoadSeqs, DNA
>>> seqs = LoadSeqs('data/long_testseqs.fasta', moltype=DNA, aligned=False)
>>> print type(seqs)
<class 'cogent.core.alignment.SequenceCollection'>
Note
An alignment can be sliced, but a SequenceCollection
can not.
Specifying the file format¶
LoadSeqs()
uses the filename suffix to infer the file format. This can be overridden using the format
argument.
>>> from cogent import LoadSeqs, DNA
>>> aln = LoadSeqs('data/long_testseqs.fasta', moltype=DNA,
... format='fasta')
...
>>> aln
5 x 2532 dna alignment: Human[TGTGGCACAAA...
LoadSeqs
from a series of strings¶
>>> from cogent import LoadSeqs
>>> seqs = ['>seq1','AATCG-A','>seq2','AATCGGA']
>>> seqs_loaded = LoadSeqs(data=seqs)
>>> print seqs_loaded
>seq1
AATCG-A
>seq2
AATCGGA
LoadSeqs
from a dict of strings¶
>>> from cogent import LoadSeqs
>>> seqs = {'seq1': 'AATCG-A','seq2': 'AATCGGA'}
>>> seqs_loaded = LoadSeqs(data=seqs)
Specifying the sequence molecular type¶
Simple case of loading a list
of aligned amino acid sequences in FASTA format, with and without molecule type specification. When the MolType
is not specified it defaults to ASCII.
>>> from cogent import LoadSeqs
>>> from cogent import DNA, PROTEIN
>>> protein_seqs = ['>seq1','DEKQL-RG','>seq2','DDK--SRG']
>>> proteins_loaded = LoadSeqs(data=protein_seqs)
>>> proteins_loaded.MolType
MolType(('a', 'b', 'c', 'd', 'e', ...
>>> print proteins_loaded
>seq1
DEKQL-RG
>seq2
DDK--SRG
>>> proteins_loaded = LoadSeqs(data=protein_seqs, moltype=PROTEIN)
>>> print proteins_loaded
>seq1
DEKQL-RG
>seq2
DDK--SRG
Stripping label characters on loading¶
Load a list of aligned nucleotide sequences, while specifying the DNA molecule type and stripping the comments from the label. In this example, stripping is accomplished by passing a function that removes everything after the first whitespace to the label_to_name
parameter.
>>> from cogent import LoadSeqs, DNA
>>> DNA_seqs = ['>sample1 Mus musculus','AACCTGC--C','>sample2 Gallus gallus','AAC-TGCAAC']
>>> loaded_seqs = LoadSeqs(data=DNA_seqs, moltype=DNA, label_to_name=lambda x: x.split()[0])
>>> print loaded_seqs
>sample1
AACCTGC--C
>sample2
AAC-TGCAAC
Using alternative constructors for the Alignment object¶
An example of using an alternative constructor is given below. A constructor is passed to the aligned parameter in lieu of True
or False
.
>>> from cogent import LoadSeqs
>>> from cogent.core.alignment import DenseAlignment
>>> seqs = ['>seq1','AATCG-A','>seq2','AATCGGA']
>>> seqs_loaded = LoadSeqs(data=seqs,aligned=DenseAlignment)
>>> print seqs_loaded
>seq1
AATCG-A
>seq2
AATCGGA
Loading sequences using format parsers¶
LoadSeqs
is just a convenience interface to format parsers. It can sometimes be more effective to use the parsers directly, say when you don’t want to load everything into memory.
Loading FASTA sequences from an open file or list of lines¶
To load FASTA formatted sequences directly, you can use the MinimalFastaParser
.
Note
This returns the sequences as strings.
>>> from cogent.parse.fasta import MinimalFastaParser
>>> f=open('data/long_testseqs.fasta')
>>> seqs = [(name, seq) for name, seq in MinimalFastaParser(f)]
>>> print seqs
[('Human', 'TGTGGCACAAATAC...
Handling overloaded FASTA sequence labels¶
The FASTA label field is frequently overloaded, with different information fields present in the field and separated by some delimiter. This can be flexibly addressed using the LabelParser
. By creating a custom label parser, we can decided which part we use as the sequence name. We show how convert a field into something specific.
>>> from cogent.parse.fasta import LabelParser
>>> def latin_to_common(latin):
... return {'Homo sapiens': 'human',
... 'Pan troglodtyes': 'chimp'}[latin]
>>> label_parser = LabelParser("%(species)s",
... [[1, "species", latin_to_common]], split_with=':')
>>> for label in ">abcd:Homo sapiens:misc", ">abcd:Pan troglodtyes:misc":
... label = label_parser(label)
... print label, type(label)
human <class 'cogent.parse.fasta.RichLabel'>
chimp <class 'cogent.parse.fasta.RichLabel'>
The RichLabel
objects have an Info
object as an attribute, allowing specific reference to all the specified label fields.
>>> from cogent.parse.fasta import MinimalFastaParser, LabelParser
>>> fasta_data = ['>gi|10047090|ref|NP_055147.1| small muscle protein, X-linked [Homo sapiens]',
... 'MNMSKQPVSNVRAIQANINIPMGAFRPGAGQPPRRKECTPEVEEGVPPTSDEEKKPIPGAKKLPGPAVNL',
... 'SEIQNIKSELKYVPKAEQ',
... '>gi|10047092|ref|NP_037391.1| neuronal protein [Homo sapiens]',
... 'MANRGPSYGLSREVQEKIEQKYDADLENKLVDWIILQCAEDIEHPPPGRAHFQKWLMDGTVLCKLINSLY',
... 'PPGQEPIPKISESKMAFKQMEQISQFLKAAETYGVRTTDIFQTVDLWEGKDMAAVQRTLMALGSVAVTKD']
...
>>> label_to_name = LabelParser("%(ref)s",
... [[1,"gi", str],
... [3, "ref", str],
... [4, "description", str]],
... split_with="|")
...
>>> for name, seq in MinimalFastaParser(fasta_data, label_to_name=label_to_name):
... print name
... print name.Info.gi
... print name.Info.description
NP_055147.1
10047090
small muscle protein, X-linked [Homo sapiens]
NP_037391.1
10047092
neuronal protein [Homo sapiens]