Abstract
BackgroundCytogenetic nomenclature is used to describe chromosomal aberrations (or lack thereof) in a collection of cells, referred to as the cells’ karyotype. The nomenclature identifies locations on chromosomes using a system of cytogenetic bands, each with a unique name and region on a chromosome. Each band is microscopically visible after staining, and encompasses a large portion of the chromosome. More modern analyses employ genomic coordinates, which precisely specify a chromosomal location according to its distance from the end of the chromosome. Currently, there is no tool to convert cytogenetic nomenclature into genomic coordinates. Since locations of genes and other genomic features are usually specified by genomic coordinates, a conversion tool will facilitate the identification of the features that are harbored in the regions of chromosomal gain and loss that are implied by a karyotype.ResultsOur tool, termed CytoConverter, takes as input either a single karyotype or a file consisting of multiple karyotypes from several individuals. All net chromosomal gains and losses implied by the karyotype are returned in standard genomic coordinates, along with the numbers of cells harboring each aberration if included in the input. CytoConverter also returns graphical output detailing areas of gains and losses of chromosomes and chromosomal segments.ConclusionsCytoConverter is available as a web-based application at https://jxw773.shinyapps.io/Cytogenetic__software/ and as an R script at https://sourceforge.net/projects/cytoconverter/. Supplemental Material detailing the underlying algorithms is available.
Highlights
Cytogenetic nomenclature is used to describe chromosomal aberrations in a collection of cells, referred to as the cells’ karyotype
In order to allow researchers to more identify the genomic entities such as genes and regulatory loci that are harbored in the gained and lost regions of karyotyped samples, we have developed a converter that parses the karyotypes and returns the corresponding gains and losses in terms of genomic coordinates
The copy number changes inferred by CytoConverter from the karyotype match well with the copy number lesions revealed from arrays, except for the more focal changes that are below the limited resolution available on the karyotype level
Summary
We provide a set of examples demonstrating CytoConverter’s capabilities. Single karyotype example Figure 2 (top panel) shows an example of the interface and output of CytoConverter, applied to the karyotype of AML-193, a cell line derived from a female acute myeloid leukemia (AML) patient. The copy number changes inferred by CytoConverter from the karyotype match well with the copy number lesions revealed from arrays, except for the more focal changes that are below the limited resolution available on the karyotype level In this example, the number of cells present are not indicated in the karyotype, but CytoConverter is set up to accommodate complex karyotypes wherein different cells harbor different chromosomal aberrations (see Example involving multiple clones subsection below). Recurrent duplication of chromosome 8 is apparent in CytoConverter’s graphical representation (Fig. 3) It is expected the graphical output will be useful for visual detection of frequent loss or gain of specific chromosomal loci in associated samples. We detail CytoConverter’s approach to parsing each of these in the Additional file 1, where we provide results from its parsing of several more example karyotypes
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