CIRCOS AN INFORMATION AESTHETIC FOR COMPARATIVE GENOMICS PDF

Delphine Naquin: rf. This article has been cited by other articles in PMC. Abstract Background Detection of large genomic rearrangements, such as large indels, duplications or translocations is now commonly achieved by next generation sequencing NGS approaches. Recently, several tools have been developed to analyze NGS data but the resulting files are difficult to interpret without an additional visualization step. Circos Genome Res, —, , a Perl script, is a powerful visualization software that requires setting up numerous configuration files with a large number of parameters to handle. However, these tools are very general and lack the functions needed to filter, format and adjust specific input genomic data.

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Abstract Background Interpretation of large-scale data is very challenging and currently there is scarcity of web tools which support automated visualization of a variety of high throughput genomics and transcriptomics data and for a wide variety of model organisms along with user defined karyotypes. Circular plot provides holistic visualization of high throughput large scale data but it is very complex and challenging to generate as most of the available tools need informatics expertise to install and run them.

Result We have developed CGDV Circos for Genomics and Transcriptomics Data Visualization , a webtool based on Circos, for seamless and automated visualization of a variety of large scale genomics and transcriptomics data. CGDV takes output of analyzed genomics or transcriptomics data of different formats, such as vcf, bed, xls, tab limited matrix text file, CNVnator raw output and Gene fusion raw output, to plot circular view of the sample data. CGDV take cares of generating intermediate files required for circos.

Conclusion The circular plot for each data type is tailored to gain best biological insights into the data. The inter-relationship between data points, homologous sequences, genes involved in fusion events, differential expression pattern, sequencing depth, types and size of variations and enrichment of DNA binding proteins can be seen using CGDV.

CGDV thus helps biologists and bioinformaticians to visualize a variety of genomics and transcriptomics data seamlessly. Background Advancement in Next Generation Sequencing NGS technology has led to generation of unprecedented amount of data of different forms.

Interpretation of large scale NGS data is complex and challenging. Visualization is one of the means to interpret NGS data and it plays crucial role in data analysis. Circular diagrams are very useful to view large scale data and their inter-relationship on a single frame. Tools such as CiVi [ 2 ] can only handle specified genomics data and is limited to plotting data from microbial genome. Another webtool, CliCo FS [ 3 ] only supports gene bank file. For other types of file it is not automated and hence user needs to format the file before the upload.

Moreover, ClicO FS is visualization driven rather than data type driven. Additionally, multiple clicks are required before generating the plot. There are other desktop based applications such as J-Circos [ 4 ] which needs to be installed before running it. Moreover, J-Circos does not support all types of genomics and transcriptomics data formats and supports limited set of model organisms. Hence none of these tools support automated, guided, and a variety of genomics and transcriptomics raw output file to conveniently interpret data in a form of circular visualization, particularly for biologists with no or minimal knowledge on Circos installation and usage.

Another file required is configuration config file which contains information on how to visualize the data based upon its content. It is complex to make a config file as user needs to thoroughly understand the data, content and different possible visualization options. CGDV not only provides prepackaged karyotype files for various model organisms but also generates config file based upon the genomics and transcriptomics data provided by the user.

The size of the circles represents relative size of the duplications and deletions at each location. Each point represents the value per coordinate from a given sample. Black line represents mean value of the data. Heatmap in the inner track represents fold-enrichment value of the peaks.

The outer track is a histogram displaying tags with p-value. The tracks are heatmaps representing Jffpm value outer track and Sffpm value inner track. The links are the position of gene fusion events between chromosomes. Web interface of CGDV requires input file along with other parameters such as user E-mail id optional, can be run as a guest user , model organism, data type for which user would wish to create circular diagram. It extracts relevant information from input file and creates configuration and data files.

Karyotype information of standard genome is stored in a SQLite database. As per selection of the model organism, specific karyotype details are fetched from the database. Using configuration files, data files and karyotype file, CGDV runs Circos [ 1 ] in the background and creates circular diagram for a given input file. Deletions and amplifications are represented in black and orange circles respectively. Size of the circle is relative to the size of CNVs.

User can filter the data based upon p-value before generating the plot. For example, expression data in a BED format enables user to view and analyze expression of multiple genes of a genome. A maximum of 12 columns of the BED file can be plotted in the form of different colored dots. The middle black line represents the mean value. This image helps user to see the relative pattern on each location of the genome across samples Fig. Tag density of peak at each location is represented by histogram with its p-value colour range with lower to higher p-values are represented in this order: violet, blue, green, yellow, orange, red.

The fold enrichment of each peak is represented with heatmap. This circular plot helps user visualize genome-wide enrichment profile of DNA binding protein s of their interest Fig. User can filter the data based upon number of tags, p-value and fold enrichment before generating the plot.

User can filter the data based upon e-value, identity, minimum hit length and score before generating the plot. Inter and Intra gene fusion events are shown by links. FFPM value is useful for filtering false positives. The color intensity in the outermost track shows Jffpm Junction ffpm while the inner track shows Sffpm Spanning ffpm values of reads. Higher color intensity bars in the two tracks suggest more number of reads supporting the fusion events.

This image helps user visualize gene fusion events as links between genes with number of reads supporting fusion event Fig. Image generated from VCF file provides a holistic view of variation density in the genome, which sometimes is not captured in the genome browser Fig. User can filter the data based upon read depth and quality of the data before generating the plot.

A maximum of 12 samples in 12 different columns in a file can be plotted with following colored dots: violet, indigo, blue, green, yellow, orange, red, brown, gold, gray in which violet dot represents the data in the first column and gray dot represents the data in the 12th column. This circular plot will help user in understanding differential expression of genes at global level in the sample data set Fig.

Matrix link file: A matrix file containing data, a maximum of tab separated columns can be plotted by CGDV. For example, different bacterial population in different conditions or locations can be plotted to display relationship between them. Image generated using matrix link file displays relation between the data in a different rows and columns by connecting them with links Fig. Table 2 CGDV supported data types, corresponding file formats and description of the plot Full size table Conclusion CGDV is an automated and easy to use web application for circular visualization of a variety of genomics and transcriptomics data.

It supports output formats of most of the genomics tools, which, makes it a biologist friendly powerful tool for data visualization and interpretation. Our application not only supports micro-organism such as bacteria and fungi genome, but also supports large organisms such as human and mouse genome. Availability and requirements.

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Circos: An information aesthetic for comparative genomics.

Jones and Marco A. Marra Abstract We created a visualization tool called Circos to facilitate the identification and analysis of similarities and differences arising from comparisons of genomes. Our tool is effective in displaying variation in genome structure and, generally, any other kind of positional relationships between genomic intervals. Such data are routinely produced by sequence alignments, hybridization arrays, genome mapping, and genotyping studies.

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CGDV: a webtool for circular visualization of genomics and transcriptomics data

Abstract Background Interpretation of large-scale data is very challenging and currently there is scarcity of web tools which support automated visualization of a variety of high throughput genomics and transcriptomics data and for a wide variety of model organisms along with user defined karyotypes. Circular plot provides holistic visualization of high throughput large scale data but it is very complex and challenging to generate as most of the available tools need informatics expertise to install and run them. Result We have developed CGDV Circos for Genomics and Transcriptomics Data Visualization , a webtool based on Circos, for seamless and automated visualization of a variety of large scale genomics and transcriptomics data. CGDV takes output of analyzed genomics or transcriptomics data of different formats, such as vcf, bed, xls, tab limited matrix text file, CNVnator raw output and Gene fusion raw output, to plot circular view of the sample data. CGDV take cares of generating intermediate files required for circos. Conclusion The circular plot for each data type is tailored to gain best biological insights into the data. The inter-relationship between data points, homologous sequences, genes involved in fusion events, differential expression pattern, sequencing depth, types and size of variations and enrichment of DNA binding proteins can be seen using CGDV.

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ClicO FS: an interactive web-based service of Circos

Circos: an information aesthetic for comparative genomics. Genome research. Abstract We created a visualization tool called Circos to facilitate the identification and analysis of similarities and differences arising from comparisons of genomes. Our tool is effective in displaying variation in genome structure and, generally, any other kind of positional relationships between genomic intervals.

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