Partition your alignment into distinct codon positions and non-coding positions
Project description
beastify: Generate input file for BEAST from whole-genome alignmennt
Background
Sometimes you want to partiion your alignment in to distinct codon positions (i.e., 1, 2, and 3), and you want to also model non-coding positions in your BEAST analysis.
beastify
does that for you. It will:
- Figure out all the codon positions in your reference (including overlapping positions)
- Optionally, label your sequences with any metadata (e.g., dates)
- Optionally, allows you to remove one or more positions from the alignment
- Optionally, allows you to mask positions form the alignment
- Optionally, allows you to sub-sample the alignment (if you want to work on a smaller dataset to test your models before throwing the whole kitchen at BEAST).
- Output a NEXUS files with the partitions ready for running BEAUTi.
Partitions are labelled:
- For the first codon position
- For the second codon position
- For the third codon position
- For any overlapping codons (sometimes CDS annotations overlap because sometimes bacterial genes will share codons)
- If position is not found in a CDS.
Installation
Dependencies
- Python >=3.6
- Click
- Pandas
- Numpy
- BioPython
Using pip
pip3 install beastify
Testing your installation
beastify --test
Input
- Genbank reference
snippy
*.consensus.subs.fa files- List of genes to include in the final alignment
- N (optional) --- random number of genes to select and include
Command list
--out TEXT Outfile name (default: out.nexus)
--info TEXT Path to a tab-delimited file with two or more
columns. The first column has the isolate ID, and
other columns have dates, location, etc. The
information will be added to the isolate ID in the
same order as the columns
--inc_ref Whether to include the reference in the final out
file (default: False)
--aln_file TEXT A sequence alignment file to give in lieu of
folder with snippy output.
--aln_file_format TEXT If providing an alignment file with --aln_file,
set the format of the alignment. Any format
supported by BioPython:AlignIO could be valid.
Default: fasta. Tested: fasta.
--subsample INTEGER Subsample X number of bases at random from each
partition. default: all bases
--subsample_seed INTEGER Set the seed when subsampling sites. Default:42
--parts TEXT Comma-separated list of partitions to include.
default:1,2,3,4,5
--test Run beastify tests and exit
--mask TEXT A BED file indicating regions to mask from the
genome
--version Show the version and exit.
--help Show this message and exit.
Output
A nexus
formatted file ready for beast
.
Script outline
- Parse coordinates of genes from Genbank into a
Genes
Class- Methods:
- load_features: a method to load the Genbank features into a dictionary. Method should check that there the length is a multiple of 3, and that the start and end codons are in place. stop codon should be stripped.
- parse_snippycore: a method to load the snippy core.tab data and identify all variable SNPs among the data that are in coding regions --- has options to return a 'random' sample of size N genes, 'top' genes with the most SNPs, with the N top genes with most SNPs.
- Data:
- features: a dictionary with key = genename and value set by seqFeature object --- IF N is provided, only keep a random set of genecoords of size _N
- Methods:
- Load
snippy
alignment into anIsolate
Class- Methods:
- load_fasta: will load the sequence into the object
- cat_genes: given an isolate id, and a genes object, return a concatenated sequence (NOT IMPLEMENTED YET)
- get_gene: return a string with the sequence for the gene specified
by gene_id using a
Genes
object - str: print the sequence ID and length, if there is one
- getitem: return the sequence string associated with the key
- add_dates: the user supplies a table of isolate IDs, and dates in a format suitable for BEAST, and the script adds them to the identifier
- Data:
- seq: A SeqRecord
- id: The isolate id
- genes: a dictionary with 'gene_name' as keys and sequence string as value
- Methods:
Collection
class to store all theIsolate
objects- Methods:
- load_isolates: given a list of isolate files, creates
and stores individual
Isolate
objects for each. - gen_align: given a
Genes
object, generate the alignment --- usescat_genes
- getitem: given an isolate ID as a key, return the
Isolate
object
- load_isolates: given a list of isolate files, creates
and stores individual
- Data:
- isolates: a dictionary with isolate id as keys and
Isolate
objects as values
- isolates: a dictionary with isolate id as keys and
- Methods:
Project details
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