Replicate

Constructor

class itpseq.Replicate(*, replicate: str | None = None, file_prefix: Path | None = None, sample: Sample | None = None, labels: dict | None = None, **kwargs)

Replicate instances represent a specific biological or experimental replicate of a Sample.

The purpose of the class is to handle, process, and analyze data corresponding to a replicate. Replicate objects provide methods to load associated data, compute statistical measures, and generate graphical representations such as sequence logos.

filename

Path to the file associated with the replicate. This file is expected to contain raw data relevant to the replicate.

Type:

Optional[Path]

sample

The sample object this replicate belongs to.

Type:

Optional[Sample]

replicate

Identifier or label for the replicate (e.g., “1”).

Type:

Optional[str]

labels

Dictionary of labels or metadata associated with the replicate.

Type:

Optional[dict]

name

Name of the sample, derived from sample.name if provided.

Type:

str

dataset

The DataSet the Sample belongs to, derived from sample.dataset if provided.

Type:

Any

kwargs

Additional keyword arguments and metadata stored as “meta” during initialization.

Type:

dict

Attributes:

aa_filename

File name for the amino-acid inverse toeprints for the replicate

dataset

Linked DataSet name (if any)

filename

File name for the nucleotide inverse toeprints for the replicate

json_filename

File name for the JSON metadata for the replicate

sample_name

Linked Sample name (if any)

Methods

copy([sample, replicate, name])	Creates a copy of the replicate.
format_sequences([codons, aa, ...])	Formats a nucleotide inverse toeprint file in a custom human-readable format
get_counts([pos, how])	Counts the number of reads for each motif or combination of amino-acid/position.
infos()	Returns the Replicate metadata from the JSON file
load_data([how, min_peptide, max_peptide, ...])	Reads the nucleotide/aminoacid inverse-toeprint file as a pandas Series, filters entries based on peptide length and stop codons.
logo([logo_kwargs, ax, fMet, type])	Generates a sequence logo based on the aligned inverse-toeprints, using the logomaker library.
rename([name])	Sets the name of the replicate from a parameter or automatically.

Methods

Replicate.load_data([how, min_peptide, ...])	Reads the nucleotide/aminoacid inverse-toeprint file as a pandas Series, filters entries based on peptide length and stop codons.
Replicate.rename([name])	Sets the name of the replicate from a parameter or automatically.
Replicate.get_counts([pos, how])	Counts the number of reads for each motif or combination of amino-acid/position.
Replicate.logo([logo_kwargs, ax, fMet, type])	Generates a sequence logo based on the aligned inverse-toeprints, using the logomaker library.