A class to represent genome-wide data measured or summarized at cytoband-level resoluton.
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A data frame that must contain at least one
numeric column and may contain the five cytoband location
columns. If the latter are missing, they must be supplied by the
A data frame with
A data frame containing cytoband
locations. Often, simply uses the
An object of the
Additional arguments to the summary method; ignored.
Conventional karyotyping describes chromosomal abnormalities (in a
standardized text-based nomenclature) that are visible through a
microsope. Karyotyping relies on a technique known as Giemsa staining,
which creates a banding pattern along the chromosome of different
shades of gray. The Loss-Gain-Fusion (LGF) model implemented at the
http://cytogps.org web site converts text-based karyotypes into
binary vectors, stored in JSON files. Our
function parses the JSON files to create R data structures, including
cytoband-resolution summaries of the frequencies of
abnormalities. These summaries can be used to create
CytobandData objects, which can be visualized using the
CytobandData conxtructor returns an object of the
CytobandData class. The
summary method returns a table,
which is the usual return value when the summary method is applied to a
data frame (in this case, the
A data frame containg five columns (Chromosome, loc.start, loc.end, Band, and Stain) defining chromosomal locations of cytobands, along with one or more columns of numerical data at cytoband resolution.
A data frame with two columns (Label and
Description) that describes the columns of the
signature(object = "RCytoGPS")
Returns a summary of the
Abrams ZB, Tally DG, Coombes KR. RCytoGPS: An R Package for Analyzing and Visualizing Cytogenetic Data. In preparation.
Abrams ZB, Tally DG, Zhang L, Coombes CE, Payne PRO, Abruzzo LV, Coombes KR. Pattern recognition in lymphoid malignancies using CytoGPS and Mercator. Under review.
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