gosling.MultivecData

class gosling.MultivecData(type=Undefined, url=Undefined, aggregation=Undefined, binSize=Undefined, categories=Undefined, column=Undefined, end=Undefined, row=Undefined, start=Undefined, value=Undefined, **kwds)

MultivecData schema wrapper

Mapping(required=[type, url]) Two-dimensional quantitative values, one axis for genomic coordinate and the other for different samples, can be converted into HiGlass’ “multivec” data. For example, multiple BigWig files can be converted into a single multivec file. You can also convert sequence data (FASTA) into this format where rows will be different nucleotide bases (e.g., A, T, G, C) and quantitative values represent the frequency. Find out more about this format at [HiGlass Docs](https://docs.higlass.io/data_preparation.html#multivec-files).

Attributes:

typestring

urlstring

Specify the URL address of the data file.

aggregationBinAggregate

Determine aggregation function to apply within bins. __Default__: “mean”

binSizefloat

Binning the genomic interval in tiles (unit size: 256).

categoriesList(string)

assign names of individual samples.

columnstring

Assign a field name of the middle position of genomic intervals. __Default__: “position”

endstring

Assign a field name of the end position of genomic intervals. __Default__: “end”

rowstring

Assign a field name of samples. __Default__: “category”

startstring

Assign a field name of the start position of genomic intervals. __Default__: “start”

valuestring

Assign a field name of quantitative values. __Default__: “value”

__init__(type=Undefined, url=Undefined, aggregation=Undefined, binSize=Undefined, categories=Undefined, column=Undefined, end=Undefined, row=Undefined, start=Undefined, value=Undefined, **kwds)

Methods

__init__([type, url, aggregation, binSize, ...])
copy([deep, ignore])	Return a copy of the object
from_dict(dct[, validate, _wrapper_classes])	Construct class from a dictionary representation
from_json(json_string[, validate])	Instantiate the object from a valid JSON string
resolve_references([schema])	Resolve references in the context of this object's schema or root schema.
to_dict([validate, ignore, context])	Return a dictionary representation of the object
to_json([validate, ignore, context, indent, ...])	Emit the JSON representation for this object as a string.
validate(instance[, schema])	Validate the instance against the class schema in the context of the rootschema.
validate_property(name, value[, schema])	Validate a property against property schema in the context of the rootschema