You then copy bigWig files onto your own webserver and they are referenced in custom tracks or track hubs via their URL. After the upload, wiggle data is compressed and stored internally in unique bins. This compression means that there is a minor loss of precision when data is exported from a wiggle track i. For custom tracks, use the bedGraph format if it is important to retain exact data when exporting.
However, the size of all custom tracks is limited. For these reasons, we recommend always converting wiggle files to the bigWig storage format and reference these from your custom tracks or track hubs via their URL. Wiggle format is line-oriented. For wiggle custom tracks, the first line must be a track definition line i. For conversion to bigWig, the most common use case, this line must not be present. Wiggle format is composed of declaration lines and data lines, and require a separate wiggle track definition line.
There are two options for formatting wiggle data: variableStep and fixedStep. These formats were developed to allow the file to be written as compactly as possible.
But we recommand that you convert them on your own computer to the binary bigWig storage format. You then copy bigWig files onto your own webserver and they are referenced in custom tracks or track hubs via their URL. The resulting bigWig files are in an indexed binary format. In this example, you will create your own bigWig file from an existing wiggle file.
Access source using git Download source code. Multiple alignments of 99 vertebrate genomes with human Conservation scores for alignments of 99 vertebrate genomes with human Basewise conservation scores phyloP of 99 vertebrate genomes with human FASTA alignments of 99 vertebrate genomes with human for CDS regions Multiple alignments of 45 vertebrate genomes with human Conservation scores for alignments of 45 vertebrate genomes with human Basewise conservation scores phyloP of 45 vertebrate genomes with human FASTA alignments of 45 vertebrate genomes with human for CDS regions.
Multiple alignments of 43 vertebrate genomes with human Conservation scores for alignments of 43 vertebrate genomes with human Basewise conservation scores phyloP of 43 vertebrate genomes with human FASTA alignments of 43 vertebrate genomes with human for CDS regions Multiple alignments of 27 vertebrate genomes with human Conservation scores for alignments of 27 vertebrate genomes with human Basewise conservation scores phyloP of 27 vertebrate genomes with human FASTA alignments of 27 vertebrate genomes with human for CDS regions Multiple alignments of 16 vertebrate genomes with human Conservation scores for alignments of 16 vertebrate genomes with human Multiple alignments of 35 vertebrate genomes with human in ENCODE regions.
Multiple alignments of 16 vertebrate genomes with Human Conservation scores for alignments of 16 vertebrate genomes with Human Multiple alignments of 8 vertebrate genomes with Human Conservation scores for alignments of 8 vertebrate genomes with Human.
Multiple alignments of 3 vertebrate genomes with Cat Conservation scores for alignments of 3 vertebrate genomes with Cat. Multiple alignments of 77 vertebrate genomes with Chicken Conservation scores for alignments of 77 vertebrate genomes with Chicken Basewise conservation scores phyloP of 77 vertebrate genomes with Chicken. Multiple alignments of 6 vertebrate genomes with chicken Conservation scores for alignments of 6 vertebrate genomes with chicken.
Multiple alignments of 4 vertebrate genomes with Cow Conservation scores for alignments of 4 vertebrate genomes with Cow. SQL table dump annotations Fileserver bigBed, maf, fa, etc annotations.
Also see Data Access. Multiple alignments of 3 vertebrate genomes with Dog Conservation scores for alignments of 3 vertebrate genomes with Dog. Multiple alignments of 7 vertebrate genomes with Fugu Conservation scores for alignments of 7 vertebrate genomes with Fugu.
Multiple alignments of 4 vertebrate genomes with Fugu Conservation scores for alignments of 4 vertebrate genomes with Fugu. Multiple alignments of 11 vertebrate genomes with Gorilla Conservation scores for alignments of 11 vertebrate genomes with Gorilla. Multiple alignments of 6 genomes with Lamprey Conservation scores for alignments of 6 genomes with Lamprey.
Multiple alignments of 5 genomes with Lamprey Conservation scores for alignments of 5 genomes with Lamprey. Multiple alignments of 4 genomes with Lancelet Conservation scores for alignments of 4 genomes with Lancelet. Multiple alignments of 5 vertebrate genomes with Malayan flying lemur Conservation scores for alignments of 5 vertebrate genomes with Malyan flying lemur.
Multiple alignments of 8 vertebrate genomes with Marmoset Conservation scores for alignments of 8 vertebrate genomes with Marmoset. Multiple alignments of 4 vertebrate genomes with Medaka Conservation scores for alignments of 4 vertebrate genomes with Medaka. Multiple alignments of 6 vertebrate genomes with the Medium ground finch Conservation scores for alignments of 6 vertebrate genomes with the Medium ground finch Basewise conservation scores phyloP of 6 vertebrate genomes with the Medium ground finch.
Multiple alignments of 59 vertebrate genomes with Mouse Conservation scores for alignments of 59 vertebrate genomes with Mouse Basewise conservation scores phyloP of 59 vertebrate genomes with Mouse FASTA alignments of 59 vertebrate genomes with Mouse for CDS regions.
BigWig files are created from wiggle wig type files using the program wigToBigWig. The bigWig files are in an indexed binary format.
The main advantage of this format is that only those portions of the file needed to display a particular region are transferred to the Genome Browser server. Because of this, bigWig files have considerably faster display performance than regular wiggle files when working with large data sets. The bigWig file remains on your local web-accessible server http, https or ftp , not on the UCSC server, and only the portion needed for the currently displayed chromosomal position is locally cached as a "sparse file".
If you do not have access to a web-accessible server and need hosting space for your bigWig files, please see the Hosting section of the Track Hub Help documentation. Wiggle data must be continuous and consist of equally sized elements. If your data is sparse or contains elements of varying sizes, use the bedGraph format instead of the wiggle format. If you have a very large bedGraph data set, you can convert it to the bigWig format using the bedGraphToBigWig program.
For details, see Example 3 below. Refer to this wiki page for help in selecting the graphing track data format most appropriate for the type of data you have. While running the wigToBigWig utility, we recommend that you monitor the system's memory usage with the top command. To create a bigWig track from a wiggle file, follow these steps: Step 1. Create a wig format file following the directions here.
When converting a wig file to a bigWig file, you are limited to one track of data in your input file; therefore, you must create a separate wig file for each data track.
Step 2. Remove any existing "track" or "browser" lines from your wig file so that it contains only data.
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