1 tabix(1) Bioinformatics tools tabix(1)
6 bgzip - Block compression/decompression utility
8 tabix - Generic indexer for TAB-delimited genome position files
11 bgzip [-cdh] [-b virtualOffset] [-s size] [file]
13 tabix [-0] [-p gff|bed|sam|vcf] [-s seqCol] [-b begCol] [-e endCol] [-S
14 lineSkip] [-c metaChar] in.tab.bgz [region1 [region2 [...]]]
18 Tabix indexes a TAB-delimited genome position file in.tab.bgz and cre-
19 ates an index file in.tab.bgz.tbi when region is absent from the com-
20 mand-line. The input data file must be position sorted and compressed
21 by bgzip which has a gzip(1) like interface. After indexing, tabix is
22 able to quickly retrieve data lines overlapping regions specified in
23 the format "chr:beginPos-endPos". Fast data retrieval also works over
24 network if URI is given as a file name and in this case the index file
25 will be downloaded if it is not present locally.
29 -p STR Input format for indexing. Valid values are: gff, bed, sam,
30 vcf and psltab. This option should not be applied together
31 with any of -s, -b, -e, -c and -0; it is not used for data
32 retrieval because this setting is stored in the index file.
35 -s INT Column of sequence name. Option -s, -b, -e, -S, -c and -0 are
36 all stored in the index file and thus not used in data
39 -b INT Column of start chromosomal position. [4]
41 -e INT Column of end chromosomal position. [5]
43 -S INT Skip first INT lines in the data file. [0]
45 -c CHAR Skip lines started with character CHAR. [#]
47 -0 Specify that the position in the data file is 0-based (e.g.
48 UCSC files) rather than 1-based.
52 grep -v ^"#" unsorted.gff | sort -k1,1 -k4,4n | bgzip -c >
55 tabix -p gff sorted.gff.gz;
57 tabix sorted.gff.gz chr1:10,000,000-20,000,000;
61 It is straightforward to achieve overlap queries using the standard B-
62 tree index (with or without binning) implemented in all SQL databases,
63 or the R-tree index in PostgreSQL and Oracle. But there are still many
64 reasons to use tabix. Firstly, tabix directly works with a lot of
65 widely used TAB-delimited formats such as GFF/GTF and BED. We do not
66 need to design database schema or specialized binary formats. Data do
67 not need to be duplicated in different formats, either. Secondly, tabix
68 works on compressed data files while most SQL databases do not. The
69 GenCode annotation GTF can be compressed down to 4%. Thirdly, tabix is
70 fast. The same indexing algorithm is known to work efficiently for an
71 alignment with a few billion short reads. SQL databases probably cannot
72 easily handle data at this scale. Last but not the least, tabix sup-
73 ports remote data retrieval. One can put the data file and the index at
74 an FTP or HTTP server, and other users or even web services will be
75 able to get a slice without downloading the entire file.
79 Tabix was written by Heng Li. The BGZF library was originally imple-
80 mented by Bob Handsaker and modified by Heng Li for remote file access
81 and in-memory caching.
89 tabix-0.1.0 2 November 2009 tabix(1)