Convert between GTrack/BED/WIG/bedGraph/GFF/FASTA files

The most commonly used formats for genomic location data are (arguably) the formats BED, BedGraph and WIG defined by the UCSC genome browser, as well as the format GFF in various versions. The tool allows converting between these formats, to the degree they are able to represent the same information as other of the formats. It also allows converting data to the recent GTrack [1] format, which is a recent, unified format that is capable of representing data of any track type, and thus stemming from any of the other file formats.

In this example we will look at and convert different types of files. This tool only work on tracks from history so first different files are imported/extracted to the history.

• A BedGraph file consisting of values from a microarray experiment [2] is extracted from the HyperBrowser hierarchy (H1)
• A WIG file with a valued points from the conservation track (phyloP46wayPrimates) in UCSC Genome Browser [3] (H2)
• A file in BED format with the sno/miRNA track from UCSC Genome Browser [3] (H3)
• A file in FASTA format that is the sequence of the TP53 gene downloaded from NCBI (H4)

View all the files by clicking the eye icon.

• The different files are then converted to GTrack format (H5-H8)

It is important that the correct format is set in the history element, otherwise the converter will not find it or an inappropriate conversion will be attempted. To change the format, click the "pencil" icon of the history element, change the value under "Change file type" and click "Save"

You may import the history by clicking the "import history" button below. You will see a overview of the the files and parameter settings in the tools.

References

1. Gundersen, S., Kalas, M., Abul, O., Frigessi, A., Hovig, E., & Sandve, G. K. (2011). Identifying elemental genomic track types and representing them uniformly. BMC Bioinformatics, 12(1), 494. doi:10.1186/1471-2105-12-494

2. Su, A. I., Wiltshire, T., Batalov, S., Lapp, H., Ching, K. A., Block, D., et al. (2004). A gene atlas of the mouse and human protein-encoding transcriptomes. Proceedings of the National Academy of Sciences of the United States of America, 101(16), 6062–6067. doi:10.1073/pnas.0400782101

3. UCSC Genome Browser, http://genome.ucsc.edu/