|Specify that the position in the data file is 0-based (e.g. UCSC files) rather than 1-based.|
|-b, --begin INT|
|Column of start chromosomal position. |
|-c, --comment CHAR|
|Skip lines started with character CHAR. [#]|
|-C, --csi||Skip lines started with character CHAR. [#]|
|-e, --end INT|
|Column of end chromosomal position. The end column can be the same as the start column. |
|Force to overwrite the index file if it is present.|
|set minimal interval size for CSI indices to 2^INT |
|-p, --preset STR|
|Input format for indexing. Valid values are: gff, bed, sam, vcf. 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, --sequence 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. |
|-S, --skip-lines INT|
Skip first INT lines in the data file. 
-h, --print-header Print also the header/meta lines. -H, --only-header Print only the header/meta lines. -l, --list-chroms List the sequence names stored in the index file. -r, --reheader FILE Replace the header with the content of FILE -R, --regions FILE Restrict to regions listed in the FILE. The FILE can be BED file (requires .bed, .bed.gz, .bed.bgz file name extension) or a TAB-delimited file with CHROM, POS, and, optionally, POS_TO columns, where positions are 1-based and inclusive. When this option is in use, the input file may not be sorted. regions. -T, --targets FILE Similar to -R but the entire input will be read sequentially and regions not listed in FILE will be skipped.
(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.
|htslib-1.3||TABIX (1)||15 December 2015|