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bgzip - Online in the Cloud

Run bgzip in OnWorks free hosting provider over Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator

This is the command bgzip that can be run in the OnWorks free hosting provider using one of our multiple free online workstations such as Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator

PROGRAM:

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.

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