tabix(1) | Bioinformatics tools | tabix(1) |
tabix - Generic indexer for TAB-delimited genome position files
tabix [-0lf] [-p gff|bed|sam|vcf] [-s seqCol] [-b begCol] [-e endCol] [-S lineSkip] [-c metaChar] in.tab.bgz [region1 [region2 [...]]]
Tabix indexes a TAB-delimited genome position file in.tab.bgz and creates an index file (in.tab.bgz.tbi or in.tab.bgz.csi) 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". (Coordinates specified in this region format are 1-based and inclusive.)
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.
The tabix (.tbi) and BAI index formats can handle individual chromosomes up to 512 Mbp (2^29 bases) in length. If your input file might contain data lines with begin or end positions greater than that, you will need to use a CSI index.
This is of most benefit when the -R option is used, which can cause blocks to be read more than once. Setting the size to 0 will disable the cache.
(grep "^#" in.gff; grep -v "^#" in.gff | sort -t"`printf '\t'`" -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.
18 August 2022 | htslib-1.16 |