bgzip [-cdhB] [-b virtualOffset] [-s size] [file]

tabix [-0lf] [-p gff|bed|sam|vcf] [-s seqCol] [-b begCol] [-e endCol] [-S lineSkip] [-c metaChar] [region1 [region2 [...]]]


Tabix indexes a TAB-delimited genome position file and creates an index file when region is absent from the command-line. The input data file must be position sorted and compressed by bgzip which has a gzip(1) like interface. After indexing, tabix is able to quickly retrieve data lines overlapping regions specified in the format "chr:beginPos-endPos". Fast data retrieval also works over network if URI is given as a file name and in this case the index file will be downloaded if it is not present locally.


-p STR

Input format for indexing. Valid values are: gff, bed, sam, vcf and psltab. This option should not be applied together with any of -s, -b, -e, -c and -0; it is not used for data retrieval because this setting is stored in the index file. [gff]

-s INT

Column of sequence name. Option -s, -b, -e, -S, -c and -0 are all stored in the index file and thus not used in data retrieval. [1]

-b INT

Column of start chromosomal position. [4]

-e INT

Column of end chromosomal position. The end column can be the same as the start column. [5]


Skip first INT lines in the data file. [0]


Skip lines started with character CHAR. [#]


Specify that the position in the data file is 0-based (e.g. UCSC files) rather than 1-based.


Print the header/meta lines.


The second argument is a BED file. When this option is in use, the input file may not be sorted or indexed. The entire input will be read sequentially. Nonetheless, with this option, the format of the input must be specificed correctly on the command line.


Force to overwrite the index file if it is present.


List the sequence names stored in the index file.


(grep ^"#" in.gff; grep -v ^"#" in.gff | sort -k1,1 -k4,4n) | bgzip > sorted.gff.gz;

tabix -p gff sorted.gff.gz;

tabix sorted.gff.gz chr1:10,000,000-20,000,000;


It is straightforward to achieve overlap queries using the standard B-tree index (with or without binning) implemented in all SQL databases, or the R-tree index in PostgreSQL and Oracle. But there are still many reasons to use tabix. Firstly, tabix directly works with a lot of widely used TAB-delimited formats such as GFF/GTF and BED. We do not need to design database schema or specialized binary formats. Data do not need to be duplicated in different formats, either. Secondly, tabix works on compressed data files while most SQL databases do not. The GenCode annotation GTF can be compressed down to 4%. Thirdly, tabix is fast. The same indexing algorithm is known to work efficiently for an alignment with a few billion short reads. SQL databases probably cannot easily handle data at this scale. Last but not the least, tabix supports remote data retrieval. One can put the data file and the index at an FTP or HTTP server, and other users or even web services will be able to get a slice without downloading the entire file.


Tabix was written by Heng Li. The BGZF library was originally implemented by Bob Handsaker and modified by Heng Li for remote file access and in-memory caching.