NAME

       bgzip - Block compression/decompression utility

       tabix - Generic indexer for TAB-delimited genome position files

SYNOPSIS

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

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

DESCRIPTION

       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". 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.

INDEXING OPTIONS

       -0, --zero-based
                 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. [4]

       -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. [5]

       -f, --force
                 Force to overwrite the index file if it is present.

       -m, --min-shiftINT
                 set minimal interval size for CSI indices to 2^INT [14]

       -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. [1]

       -S, --skip-lines INT
                 Skip first INT lines in the data file. [0]

QUERYING AND OTHER OPTIONS

       -h, --print-header
              Print also the header/meta lines.

       -H, --only-header
              Print only the header/meta lines.

       -i, --file-info
              Print file format info.

       -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.

EXAMPLE

       (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;

NOTES

       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.

AUTHOR

       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.

SEE ALSO

       samtools(1)