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BED (Browser Extensible Data) format provides a flexible way to define the data lines that are displayed in an annotation track. BED lines have three required fields and nine additional optional fields. The number of fields per line must be consistent throughout any single set of data in an annotation track. The order of the optional fields is binding: lower-numbered fields must always be populated if higher-numbered fields are used.
BED information should not be mixed as explained above (BED3 should not be mixed with BED4), rather additional column information must be filled for consistency, for example with a "." in some circumstances, if the field content is to be empty. BED fields in custom tracks can be whitespace-delimited or tab-delimited. Only some variations of BED types, such as bedDetail, require a tab character delimitation for the detail columns.
Please note that only in custom tracks can the first lines of the file consist of header lines, which begin with the word "browser" or "track" to assist the browser in the display and interpretation of the lines of BED data following the headers. Such annotation track header lines are not permissible in downstream utilities such as bedToBigBed, which convert lines of BED text to indexed binary files.
If your data set is BED-like, but it is very large (over 50MB) and you would like to keep it on your own server, you should use the bigBed data format.
The first three required BED fields are:
The 9 additional optional BED fields are:
| shade | |||||||||
| score in range | ≤ 166 | 167-277 | 278-388 | 389-499 | 500-611 | 612-722 | 723-833 | 834-944 | ≥ 945 |
In BED files with block definitions, the first blockStart value must be 0, so that the first block begins at chromStart. Similarly, the final blockStart position plus the final blockSize value must equal chromEnd. Blocks may not overlap.
Example:
Here's an example of an annotation track, introduced by a
header line, that is followed by a complete
BED definition:
track name=pairedReads description="Clone Paired Reads" useScore=1
chr22 1000 5000 cloneA 960 + 1000 5000 0 2 567,488, 0,3512
chr22 2000 6000 cloneB 900 - 2000 6000 0 2 433,399, 0,3601
Example:
This example shows an annotation track that uses the itemRgb attribute to individually color each
data line. In this track, the color scheme distinguishes between items named "Pos*" and
those named "Neg*". See the usage note in the itemRgb description above for color
palette restrictions. NOTE: The track and data
lines in this example have been reformatted for documentation purposes. This
example can be pasted into the
browser without editing.
browser position chr7:127471196-127495720
browser hide all
track name="ItemRGBDemo" description="Item RGB demonstration" visibility=2 itemRgb="On"
chr7 127471196 127472363 Pos1 0 + 127471196 127472363 255,0,0
chr7 127472363 127473530 Pos2 0 + 127472363 127473530 255,0,0
chr7 127473530 127474697 Pos3 0 + 127473530 127474697 255,0,0
chr7 127474697 127475864 Pos4 0 + 127474697 127475864 255,0,0
chr7 127475864 127477031 Neg1 0 - 127475864 127477031 0,0,255
chr7 127477031 127478198 Neg2 0 - 127477031 127478198 0,0,255
chr7 127478198 127479365 Neg3 0 - 127478198 127479365 0,0,255
chr7 127479365 127480532 Pos5 0 + 127479365 127480532 255,0,0
chr7 127480532 127481699 Neg4 0 - 127480532 127481699 0,0,255
Click here to display this track in the Genome Browser.
Example:
It is also possible to color items by strand in a BED track using the colorByStrand
attribute in the track line as shown below.
For BED tracks, this attribute functions only for custom tracks with 6 to 8 fields (i.e. BED6
through BED8). NOTE: The track and data lines in this example have been reformatted for
documentation purposes. This example can be pasted into the browser without editing.
browser position chr7:127471196-127495720
browser hide all
track name="ColorByStrandDemo" description="Color by strand demonstration" visibility=2 colorByStrand="255,0,0 0,0,255"
chr7 127471196 127472363 Pos1 0 +
chr7 127472363 127473530 Pos2 0 +
chr7 127473530 127474697 Pos3 0 +
chr7 127474697 127475864 Pos4 0 +
chr7 127475864 127477031 Neg1 0 -
chr7 127477031 127478198 Neg2 0 -
chr7 127478198 127479365 Neg3 0 -
chr7 127479365 127480532 Pos5 0 +
chr7 127480532 127481699 Neg4 0 -
Click here to display this track in the Genome Browser.
The bigBed format stores annotation items that can either be simple, or a linked collection of
exons, much as bed files do. BigBed files are created initially from bed
type files, using the program bedToBigBed. The resulting bigBed files are in an indexed
binary format. The main advantage of the bigBed files is that only the portions of the files needed
to display a particular region are transferred to UCSC, so for large data sets bigBed is
considerably faster than regular bed files. The bigBed file remains on your web accessible server
(http, https, or ftp), not on the UCSC server.
Click here for more information on the bigBed format.
This is an extension of BED format. BED detail uses the first 4 to 12 columns of BED format, plus 2 additional fields that are used to enhance the track details pages. The first additional field is an ID, which can be used in place of the name field for creating links from the details pages. The second additional field is a description of the item, which can be a long description and can consist of html, including tables and lists.
Requirements for BED detail custom tracks are: fields must be tab-separated, "type=bedDetail" must be included in the track line, and the name and position fields should uniquely describe items so that the correct ID and description will be displayed on the details pages.
Example:
This example uses the first 4 columns of BED format, but up to 12 may be used. Click
here to view this track in the Genome Browser.
track name=HbVar type=bedDetail description="HbVar custom track" db=hg19 visibility=3 url="http://globin.bx.psu.edu/cgi-bin/hbvar/query_vars3?display_format=page&mode=output&id=$$"
chr11 5246919 5246920 Hb_North_York 2619 Hemoglobin variant
chr11 5255660 5255661 HBD c.1 G>A 2659 delta0 thalassemia
chr11 5247945 5247946 Hb Sheffield 2672 Hemoglobin variant
chr11 5255415 5255416 Hb A2-Lyon 2676 Hemoglobin variant
chr11 5248234 5248235 Hb Aix-les-Bains 2677 Hemoglobin variant The bedGraph format allows display of continuous-valued data in track format. This display type is useful for probability scores and transcriptome data. This track type is similar to the WIG format, but unlike the WIG format, data exported in the bedGraph format are preserved in their original state. This can be seen on export using the table browser. For more information about the bedGraph format, please see the bedGraph details page.
If you have a very large data set and you would like to keep it on your own server, you should use the bigWig format.
PSL lines represent alignments, and are typically taken from files generated by BLAT or psLayout. See the BLAT documentation for more details. All of the following fields are required on each data line within a PSL file:
Example:
Here is an example of an annotation track in PSL format.
browser position chr22:13073000-13074000
browser hide all
track name=fishBlats description="Fish BLAT" visibility=2 useScore=1
59 9 0 0 1 823 1 96 +- FS_CONTIG_48080_1 1955 171 1062 chr22 47748585 13073589 13073753 2 48,20, 171,1042, 34674832,34674976,
59 7 0 0 1 55 1 55 +- FS_CONTIG_26780_1 2825 2456 2577 chr22 47748585 13073626 13073747 2 21,45, 2456,2532, 34674838,34674914,
59 7 0 0 1 55 1 55 -+ FS_CONTIG_26780_1 2825 2455 2676 chr22 47748585 13073727 13073848 2 45,21, 249,349, 13073727,13073827, Click here to display this track in the Genome Browser.
Be aware that the coordinates for a negative strand in a dna query PSL line are handled in a special way. In the qStart and qEnd fields, the coordinates indicate the position where the query matches from the point of view of the forward strand, even when the match is on the reverse strand. However, in the qStarts list, the coordinates are reversed.
Example:
Here is a 61-mer containing 2 blocks that align on the minus strand and 2 blocks that align on the
plus strand (this sometimes happens due to assembly errors):
0 1 2 3 4 5 6 tens position in query
0123456789012345678901234567890123456789012345678901234567890 ones position in query
++++++++++++++ +++++ plus strand alignment on query
------------------ -------------------- minus strand alignment on query
0987654321098765432109876543210987654321098765432109876543210 ones position in query negative strand coordinates
6 5 4 3 2 1 0 tens position in query negative strand coordinates
Plus strand:
qStart=22
qEnd=61
blockSizes=14,5
qStarts=22,56
Minus strand:
qStart=4
qEnd=56
blockSizes=20,18
qStarts=5,39 Essentially, the minus strand blockSizes and qStarts are what you would get if you reverse-complemented the query. However, the qStart and qEnd are not reversed. Use the following formulas to convert one to the other:
Negative-strand-coordinate-qStart = qSize - qEnd = 61 - 56 = 5
Negative-strand-coordinate-qEnd = qSize - qStart = 61 - 4 = 57
BLAT this actual sequence against hg19 for a real-world example:
CCCC
GGGTAAAATGAGTTTTTT
GGTCCAATCTTTTA
ATCCACTCCCTACCCTCCTA
GCAAGLook for the alignment on the negative strand (-) of chr21, which conveniently aligns to the window chr21:10,000,001-10,000,061.
Browser window coordinates are 1-based [start,end] while PSL coordinates are 0-based [start,end), so a start of 10,000,001 in the browser corresponds to a start of 10,000,000 in the PSL. Subtracting 10,000,000 from the target (chromosome) position in PSL gives the query negative strand coordinate above.
The 4, 14, and 5 bases at beginning, middle, and end were chosen to not match with the genome at the corresponding position.
Translated Queries:
Translated queries translate both the query and target dna into amino acids for greater sensitivity.
They are also used for protein search, although in that case the query does not need to be translated.
For these search types, the strand field lists two values, the first for the query strand (qStrand) and the second for the target strand (tStrand).
The following rules apply, where x can be q or t:
If xStrand is negative, the xStarts list has negative-strand coordinates.
However, the xStart,xEnd values are always given in positive-strand coordinates, regardless of xStrand.
Protein Query:
A protein query consists of amino acids. To align amino acids against a database of nucleic acids,
each target chromosome is first translated into amino acids for each of the six different reading
frames. The resulting protein PSL is a hybrid; the query fields are all in amino acid coordinates
and sizes, while the target database fields are in nucleic acid chromosome coordinates and sizes.
The fields shared by query and target are blockCount and blockSizes. But blockSizes differ between
query (AA) and target (NA), so a single field cannot represent both. A choice was therefore made
to report the blockSizes field in amino acids since it is a protein query.
To find the size of a target exon in nucleic acids, use the formula:
blockSizes[exonNumber]*3Or, to find the end position of a target exon, use the formula:
tStarts[exonNumber] + (blockSizes[exonNumber]*3)GFF (General Feature Format) lines are based on the Sanger GFF2 specification. GFF lines have nine required fields that must be tab-separated. If the fields are separated by spaces instead of tabs, the track will not display correctly. For more information on GFF format, refer to Sanger's GFF page.
Note that there is also a GFF3 specification that is not currently supported by the Browser. All GFF tracks must be formatted according to Sanger's GFF2 specification.
If you would like to obtain browser data in GFF (GTF) format, please refer to Genes in gtf or gff format on the Wiki.
Here is a brief description of the GFF fields:
Example:
Here's an example of a GFF-based track. This data format require tabs and some operating systems convert tabs to spaces. If pasting doesn't work, this example's contents or the url itself can be pasted into the custom track text box.
browser position chr22:10000000-10025000
browser hide all
track name=regulatory description="TeleGene(tm) Regulatory Regions" visibility=2
chr22 TeleGene enhancer 10000000 10001000 500 + . touch1
chr22 TeleGene promoter 10010000 10010100 900 + . touch1
chr22 TeleGene promoter 10020000 10025000 800 - . touch2
Click here to display this track in the Genome Browser.
GTF (Gene Transfer Format, GTF2.2) is an extension to, and backward compatible with, GFF2. The first eight GTF fields are the same as GFF. The feature field is the same as GFF, with the exception that it also includes the following optional values: 5UTR, 3UTR, inter, inter_CNS, and intron_CNS. The group field has been expanded into a list of attributes. Each attribute consists of a type/value pair. Attributes must end in a semi-colon, and be separated from any following attribute by exactly one space.
The attribute list must begin with the two mandatory attributes:
Example:
Here is an example of the ninth field in a GTF data line:
gene_id "Em:U62317.C22.6.mRNA"; transcript_id "Em:U62317.C22.6.mRNA"; exon_number 1The Genome Browser groups together GTF lines that have the same transcript_id value. It only looks at features of type exon and CDS.
For more information regarding the GTF2.2 UCSC supported format, see http://mblab.wustl.edu/GTF22.html. If you would like to obtain browser data in GTF format, please refer to our FAQ on GTF format or our wiki page on generating GTF or GFF gene file
HAL is a graph-based structure to efficiently store and index multiple genome alignments and ancestral reconstructions. HAL files are represented in HDF5 format, an open standard for storing and indexing large, compressed scientific data sets. Genomes within HAL are organized according to the phylogenetic tree that relate them: each genome is segmented into pairwise DNA alignment blocks with respect to its parent and children (if present) in the tree. Note that if the phylogeny is unknown, a star tree can be used. The modularity provided by this tree-based decomposition allows for efficient querying of sub-alignments, as well as the ability to add, remove and update genomes within the alignment with only local modifications to the structure. Another important feature of HAL is reference independence: alignments in this format can be queried with respect to the coordinates of any genome they contain.
HAL files can be created or read with a comprehensive C++ API (click here for source code and manual). A set of command line tools is included to perform basic operations, such as importing and exporting data, identifying mutations, coordinate mapping (liftOver), and comparative assembly hub generation.
HAL is the native output format of the Progressive Cactus alignment pipeline, and is included in the Progressive Cactus installation package.
Hic files are binary files that store contact matrices from chromatin conformation experiments. This format is useful for displaying interactions at a scale and depth that exceeds what can be easily visualized with the interact and bigInteract formats. See the hic Track Format help page for more information on creating and configuring hic tracks. More information on the hic format itself can be found in the documentation on Github. The hic format was created by the Aiden Lab at Baylor College of Medicine.
The interact (and bigInteract) track format displays pairwise interactions as arcs or half-rectangles connecting two genomic regions on the same chromosome. Cross-chromosomal interactions can also be represented in this format. This format is useful for displaying functional element interactions such as SNP/gene interactions, and is also suitable for low-density chromatin interactions, such as ChIA-PET, and other use cases with a limited number of interactions on the genome. It is not suitable for high-density chromatin data such as Hi-C.
Click here for more information on the interact and bigInteract formats.
The longrange track is a bed format-like file type. Each row contains columns that define chromosome, start position (0-based), and end position (not included), and interaction target in this format chr2:333-444,55. For examples, see the source of this format at WashU Epigenome Browser.
Also, review the enhanced interact format for information on how to visualize pairwise interactions as arcs in the browser.
The multiple alignment format stores a series of multiple alignments in a format that is easy to parse and relatively easy to read. This format stores multiple alignments at the DNA level between entire genomes. Previously used formats are suitable for multiple alignments of single proteins or regions of DNA without rearrangements, but would require considerable extension to cope with genomic issues such as forward and reverse strand directions, multiple pieces to the alignment, and so forth.
General Structure
The .maf format is line-oriented. Each multiple alignment ends with a blank line. Each
sequence in an alignment is on a single line, which can get quite long, but there is no length
limit. Words in a line are delimited by any white space. Lines starting with # are considered to be
comments. Lines starting with ## can be ignored by most programs, but contain meta-data of one form
or another.
The file is divided into paragraphs that terminate in a blank line. Within a paragraph, the first word of a line indicates its type. Each multiple alignment is in a separate paragraph that begins with an "a" line and contains an "s" line for each sequence in the multiple alignment. Some MAF files may contain other optional line types:
Parsers may ignore any other types of paragraphs and other types of lines within an alignment paragraph.
Custom Tracks
The first line of a custom MAF track must be a "track" line that contains a name=value
pair specifying the track name. Here is an example of a minimal track line:
track name=sampleThe following variables can be specified in the track line of a custom MAF:
The second line of a custom MAF track must be a header line as described below.
Header Line
The first line of a .maf file begins with ##maf. This word is followed by white-space-separated variable=value pairs. There should be no white space surrounding the "=".
##maf version=1 scoring=tba.v8The currently defined variables are:
Undefined variables are ignored by the parser.
The header line is usually followed by a comment line (it begins with a #) that describes the parameters that were used to run the alignment program:
# tba.v8 (((human chimp) baboon) (mouse rat))Alignment Block Lines (lines starting with "a" -- parameters for a new alignment block)
a score=23262.0Each alignment begins with an "a" line that set variables for the entire alignment block. The "a" is followed by name=value pairs. There are no required name=value pairs. The currently defined variables are:
Lines starting with "s" -- a sequence within an alignment block
s hg16.chr7 27707221 13 + 158545518 gcagctgaaaaca
s panTro1.chr6 28869787 13 + 161576975 gcagctgaaaaca
s baboon 249182 13 + 4622798 gcagctgaaaaca
s mm4.chr6 53310102 13 + 151104725 ACAGCTGAAAATA
The "s" lines together with the "a" lines define a multiple alignment. The "s" lines have the following fields which are defined by position rather than name=value pairs.
Lines starting with "i" -- information about what's happening before and after this block in the aligning species
s hg16.chr7 27707221 13 + 158545518 gcagctgaaaaca
s panTro1.chr6 28869787 13 + 161576975 gcagctgaaaaca
i panTro1.chr6 N 0 C 0
s baboon 249182 13 + 4622798 gcagctgaaaaca
i baboon I 234 n 19 The "i" lines contain information about the context of the sequence lines immediately preceding them. The following fields are defined by position rather than name=value pairs:
The status characters can be one of the following values:
Lines starting with "e" -- information about empty parts of the alignment block
s hg16.chr7 27707221 13 + 158545518 gcagctgaaaaca
e mm4.chr6 53310102 13 + 151104725 I The "e" lines indicate that there isn't aligning DNA for a species but that the current block is bridged by a chain that connects blocks before and after this block. The following fields are defined by position rather than name=value pairs.
The status character can be one of the following values:
Lines starting with "q" -- information about the quality of each aligned base for the species
s hg18.chr1 32741 26 + 247249719 TTTTTGAAAAACAAACAACAAGTTGG
s panTro2.chrUn 9697231 26 + 58616431 TTTTTGAAAAACAAACAACAAGTTGG
q panTro2.chrUn 99999999999999999999999999
s dasNov1.scaffold_179265 1474 7 + 4584 TT----------AAGCA---------
q dasNov1.scaffold_179265 99----------32239--------- The "q" lines contain a compressed version of the actual raw quality data, representing the quality of each aligned base for the species with a single character of 0-9 or F. The following fields are defined by position rather than name=value pairs:
MAF quality value = min( floor(actual quality value/5), 9 )This results in the following mapping:
| MAF quality value | Raw quality score range | Quality level |
|---|---|---|
| 0-8 | 0-44 | Low |
| 9 | 45-97 | High |
| 0 | 98 | Manually assigned |
| F | 99 | Finished |
A Simple Example
Here is a simple example of a three alignment blocks derived from five starting sequences. The first track line is necessary for custom tracks, but should be removed otherwise. Repeats are shown as lowercase, and each block may have a subset of the input sequences. All sequence columns and rows must contain at least one nucleotide (no columns or rows that contain only insertions).
track name=euArc visibility=pack
##maf version=1 scoring=tba.v8
# tba.v8 (((human chimp) baboon) (mouse rat))
a score=23262.0
s hg18.chr7 27578828 38 + 158545518 AAA-GGGAATGTTAACCAAATGA---ATTGTCTCTTACGGTG
s panTro1.chr6 28741140 38 + 161576975 AAA-GGGAATGTTAACCAAATGA---ATTGTCTCTTACGGTG
s baboon 116834 38 + 4622798 AAA-GGGAATGTTAACCAAATGA---GTTGTCTCTTATGGTG
s mm4.chr6 53215344 38 + 151104725 -AATGGGAATGTTAAGCAAACGA---ATTGTCTCTCAGTGTG
s rn3.chr4 81344243 40 + 187371129 -AA-GGGGATGCTAAGCCAATGAGTTGTTGTCTCTCAATGTG
a score=5062.0
s hg18.chr7 27699739 6 + 158545518 TAAAGA
s panTro1.chr6 28862317 6 + 161576975 TAAAGA
s baboon 241163 6 + 4622798 TAAAGA
s mm4.chr6 53303881 6 + 151104725 TAAAGA
s rn3.chr4 81444246 6 + 187371129 taagga
a score=6636.0
s hg18.chr7 27707221 13 + 158545518 gcagctgaaaaca
s panTro1.chr6 28869787 13 + 161576975 gcagctgaaaaca
s baboon 249182 13 + 4622798 gcagctgaaaaca
s mm4.chr6 53310102 13 + 151104725 ACAGCTGAAAATA BAM is the compressed binary version of the Sequence Alignment/Map (SAM) format, a compact and index-able representation of nucleotide sequence alignments. Many next-generation sequencing and analysis tools work with SAM/BAM. For custom track display, the main advantage of indexed BAM over PSL and other human-readable alignment formats is that only the portions of the files needed to display a particular region are transferred to UCSC. This makes it possible to display alignments from files that are so large that the connection to UCSC would time out when attempting to upload the whole file to UCSC. Both the BAM file and its associated index file remain on your web-accessible server (http or ftp), not on the UCSC server. UCSC temporarily caches the accessed portions of the files to speed up interactive display.
Click here for more information about BAM custom tracks.
The CRAM file format is a more dense form of BAM files with the benefit of saving much disk space. While BAM files contain all sequence data within a file, CRAM files are smaller by taking advantage of an additional external "reference sequence" file. This file is needed to both compress and decompress the read information.
Click here for more information on the CRAM format.
Wiggle format (WIG) allows the display of continuous-valued data in a track format. Click here for more information.
The bigWig format is for display of dense, continuous data that will be displayed in the Genome
Browser as a graph. BigWig files are created initially from wiggle (wig) type
files, using the program wigToBigWig. Alternatively, bigWig files can be created from
bedGraph files, using the program
bedGraphToBigWig. In either case, the resulting bigWig files are in an indexed binary
format. The main advantage of the bigWig files is that only the portions of the files needed to
display a particular region are transferred to UCSC, so for large data sets bigWig is considerably
faster than regular wiggle files. The bigWig file remains on your web accessible server (http,
https, or ftp), not on the UCSC server. Only the portion that is needed for the chromosomal position
you are currently viewing is locally cached as a "sparse file".
Click here for more information on the bigWig format.
The datasets for the built-in microarray tracks in the Genome Browser are stored in BED15 format, an extension of BED format that includes three additional fields: expCount, expIds, and expScores. To display correctly in the Genome Browser, microarray tracks require the setting of several attributes in the trackDb file associated with the track's genome assembly. Each microarray track set must also have an associated microarrayGroups.ra configuration file that contains additional information about the data in each of the arrays.
User-created microarray custom tracks are similar in format to BED custom tracks with the addition of three required track line parameters in the header--expNames, expScale, and expStep--that mimic the trackDb and microarrayGroups.ra settings of built-in microarray tracks.
For a complete description of the microarray track format and an explanation of how to construct a microarray custom track, see the Genome Browser Wiki.
A .2bit file stores multiple DNA sequences (up to 4 Gb total) in a compact randomly-accessible format. The file contains masking information as well as the DNA itself.
The file begins with a 16-byte header containing the following fields:
All fields are 32 bits unless noted. If the signature value is not as given, the reader program should byte-swap the signature and check if the swapped version matches. If so, all multiple-byte entities in the file will have to be byte-swapped. This enables these binary files to be used unchanged on different architectures.
The header is followed by a file index, which contains one entry for each sequence. Each index entry contains three fields:
The index is followed by the sequence records, which contain nine fields:
For a complete definition of all fields in the twoBit format, see this description in the source code.
The .nib format pre-dates the .2bit format and is less compact. It describes a DNA sequence by packing two bases into each byte. Each .nib file contains only a single sequence. The file begins with a 32-bit signature that is 0x6BE93D3A in the architecture of the machine that created the file (or possibly a byte-swapped version of the same number on another machine). This is followed by a 32-bit number in the same format that describes the number of bases in the file. Next, the bases themselves are listed, packed two bases to the byte. The first base is packed in the high-order 4 bits (nibble); the second base is packed in the low-order four bits:
byte = (base1<<4) + base2
The numerical representations for the bases are:
0 - T
1 - C
2 - A
3 - G
4 - N (unknown)The most significant bit in a nibble is set if the base is masked.
genePred is a table format commonly used for gene prediction tracks in the Genome Browser. Variations of the genePred format are listed below.
If you would like to obtain browser data in GFF (GTF) format, please refer to Genes in gtf or gff format on the Wiki.
Gene Predictions
The following definition is used for gene prediction tables.In alternative-splicing situations, each transcript has a row in this table.
table genePred
"A gene prediction."
(
string name; "Name of gene"
string chrom; "Chromosome name"
char[1] strand; "+ or - for strand"
uint txStart; "Transcription start position"
uint txEnd; "Transcription end position"
uint cdsStart; "Coding region start"
uint cdsEnd; "Coding region end"
uint exonCount; "Number of exons"
uint[exonCount] exonStarts; "Exon start positions"
uint[exonCount] exonEnds; "Exon end positions"
)
Gene Predictions (Extended)
The following definition is used for extended gene prediction tables. In alternative-splicing situations, each transcript has a row in this table. The refGene table is an example of the genePredExt format.
table genePredExt
"A gene prediction with some additional info."
(
string name; "Name of gene (usually transcript_id from GTF)"
string chrom; "Chromosome name"
char[1] strand; "+ or - for strand"
uint txStart; "Transcription start position"
uint txEnd; "Transcription end position"
uint cdsStart; "Coding region start"
uint cdsEnd; "Coding region end"
uint exonCount; "Number of exons"
uint[exonCount] exonStarts; "Exon start positions"
uint[exonCount] exonEnds; "Exon end positions"
int score; "Score"
string name2; "Alternate name (e.g. gene_id from GTF)"
string cdsStartStat; "Status of CDS start annotation (none, unknown, incomplete, or complete)"
string cdsEndStat; "Status of CDS end annotation (none, unknown, incomplete, or complete)"
lstring exonFrames; "Exon frame offsets {0,1,2}"
)
Gene Predictions and RefSeq Genes with Gene Names
A version of genePred that associates the gene name with the gene prediction information. In alternative-splicing situations, each transcript has a row in this table.
table refFlat
"A gene prediction with additional geneName field."
(
string geneName; "Name of gene as it appears in Genome Browser."
string name; "Name of gene"
string chrom; "Chromosome name"
char[1] strand; "+ or - for strand"
uint txStart; "Transcription start position"
uint txEnd; "Transcription end position"
uint cdsStart; "Coding region start"
uint cdsEnd; "Coding region end"
uint exonCount; "Number of exons"
uint[exonCount] exonStarts; "Exon start positions"
uint[exonCount] exonEnds; "Exon end positions"
)
bigGenePred is a table format commonly used for gene prediction tracks in the Genome Browser. bigGenePred format is a superset of the genePred text-based format supported using the bigBed format, so it can be efficiently accessed over a network.
Click here for more information on the bigGenePred format.
The barChart (and bigBarChart) track format displays a graph of category-specific values over genomic regions, similar to the GTEx Gene track. This format is useful for displaying gene expression and other datasets where it is desirable to compare a set of variables over genomic regions.
Click here for more information on the barChart and bigBarChart formats.
bigPsl is a table format commonly used to store alignments in the Genome Browser. bigPsl format is a superset of the PSL text-based format supported using the bigBed format, so it can be efficiently accessed over a network.
Click here for more information on the bigPsl format.
bigMaf is a table format commonly used to store multiple alignments in the Genome Browser. bigMaf format is a superset of the MAF text-based format supported using the bigBed format, so it can be efficiently accessed over a network.
Click here for more information on the bigMaf format.
bigChain is a table format commonly used to store pairwise alignments in the Genome Browser. bigChain format is a superset of the chain text-based format supported using the bigBed format, so it can be efficiently accessed over a network.
Click here for more information on the bigChain format.
bigNarrowPeak is a format used to provide called peaks of signal enrichment based on pooled, normalized (interpreted) data. It is a BED6+4 format. bigNarrowPeak format is equivalent to the narrowPeak text-based format supported using the bigBed format, so it can be efficiently accessed over a network.
Click here for more information on the bigNarrowPeak format.
bigLolly is a format used to draw a lollipop chart. The data format is a standard bigBed format where by default the score is used to decide how high to draw the lollipop. There are also trackDb options to specify which fields to use for the height and width of the lollipop, as well as to draw lines on the graph.
Click here for more information on the bigLolly format.
This format is for displaying SNPs from personal genomes. It is the same as is used for the Genome Variants and Population Variants tracks.
In the Genome Browser, when viewing the forward strand of the reference genome (the normal case), the displayed alleles are relative to the forward strand. When viewing the reverse strand of the reference genome (via the "<--" or "reverse" button), the displayed alleles are reverse-complemented to match the reverse strand. If the allele frequencies are given, the coloring of the box will reflect the frequency for each allele.
The details pages for this track type will automatically compute amino acid changes for coding SNPs as well as give a chart of amino acid properties if there is a non-synonymous change. (The Sift and PolyPhen predictions that are in some of the Genome Variants subtracks are not available.)
Example:
Here is an example of an annotation track in Personal Genome SNP format. The first SNP using a
"-" is an insertion; the second is a deletion. The last 4 SNPs are in a coding region.
track type=pgSnp visibility=3 db=hg19 name="pgSnp" description="Personal Genome SNP example"
browser position chr21:31811924-31812937
chr21 31812007 31812008 T/G 2 21,70 90,70
chr21 31812031 31812032 T/G/A 3 9,60,7 80,80,30
chr21 31812035 31812035 -/CGG 2 20,80 0,0
chr21 31812088 31812093 -/CTCGG 2 30,70 0,0
chr21 31812277 31812278 T 1 15 90
chr21 31812771 31812772 A 1 36 80
chr21 31812827 31812828 A/T 2 15,5 0,0
chr21 31812879 31812880 C 1 0 0
chr21 31812915 31812916 - 1 0 0
Variant Call Format (VCF) is a flexible and extendable format (now maintained by the GA4GH) for variation data such as single nucleotide variants, insertions/deletions, copy number variants and structural variants. When a VCF file is compressed and indexed using tabix, and made web-accessible, the Genome Browser can fetch only the portions of the file necessary to display items in the viewed region. This makes it possible to display alignments from files that are so large that the connection to UCSC would time out when attempting to upload the whole file to UCSC. Both the compressed VCF file and its tabix index file remain on your web-accessible server (http or ftp), not on the UCSC server. UCSC temporarily caches the accessed portions of the files to speed up interactive display.
Go to the VCF Track Format page for more information about VCF custom tracks.
This format is used to provide called peaks of signal enrichment based on pooled, normalized (interpreted) data. It is a BED6+4 format.
Here is an example of narrowPeak format:
track type=narrowPeak visibility=3 db=hg19 name="nPk" description="ENCODE narrowPeak Example"
browser position chr1:9356000-9365000
chr1 9356548 9356648 . 0 . 182 5.0945 -1 50
chr1 9358722 9358822 . 0 . 91 4.6052 -1 40
chr1 9361082 9361182 . 0 . 182 9.2103 -1 75
This format is used to provide called regions of signal enrichment based on pooled, normalized (interpreted) data. It is a BED 6+3 format.
Here is an example of broadPeak format:
track type=broadPeak visibility=3 db=hg19 name="bPk" description="ENCODE broadPeak Example"
browser position chr1:798200-800700
chr1 798256 798454 . 116 . 4.89716 3.70716 -1
chr1 799435 799507 . 103 . 2.46426 1.54117 -1
chr1 800141 800596 . 107 . 3.22803 2.12614 -1
This format is used to provide called regions of signal enrichment based on pooled, normalized (interpreted) data where the regions may be spliced or incorporate gaps in the genomic sequence. It is a BED12+3 format.
Here is an example of gappedPeak format:
track name=gappedPeakExample type=gappedPeak
chr1 171000 171600 Anon_peak_1 55 . 0 0 0 2 400,100 0,500 4.04761 7.53255 5.52807
tagAlign was used in hg18, but not in subsequent assemblies. Tag Alignment provided genomic mapping of short sequence tags. It is a BED3+3 format.
Here is an example of tagAlign format:
chrX 8823384 8823409 AGAAGGAAAATGATGTGAAGACATA 1000 +
chrX 8823387 8823412 TCTTATGTCTTCACATCATTTTCCT 500 -
pairedTagAlign was used in hg18, but not in subsequent assemblies. Tag Alignment Format for Paired Reads was used to provide genomic mapping of paired-read short sequence tags. It is a BED6+2 format.
The peptide mapping format was used to provide genomic mapping of proteogenomic mappings of peptides to the genome, with information that is appropriate for assessing the confidence of the mapping.
Click here for information about fasta format.
Click here for information about fastq format.