Genozip FASTQ files¶
Compressing a FASTQ file
While Genozip is technically capable of compressing FASTQ files without using a reference, in practice, to achieve good compression ratios, compression should always be done against a reference genome.
Preparing the reference file is a one-time step (per-species), where the input file is a FASTA file representing the reference genome.
If the species has multiple versions of its reference genome FASTA, any one of them will work.
If there is no reference genome for the target species, a reference genome of a closely related species may be used.
For meta-genomic applications, it is possible to use a reference FASTA that contains sequences from multiple species, up to a total of 4 Gbp.
$ genozip --make-reference hs37d5.fa.gz # this generates the file hs37d5.ref.genozip
Once a reference file is prepared, we can compress the FASTQ files:
Compressing a single FASTQ file:
$ genozip --reference hs37d5.ref.genozip myfile.fq.gz genozip myfile.fq.gz : Done (31 seconds, FASTQ compression ratio: 22.5 - better than .fq.gz by a factor of 4.5) $ ls -l myfile* -rwxrwxrwx 1 divon divon 1640641 Aug 21 12:28 myfile.fq.genozip -rwxrwxrwx 1 divon divon 7338338 Aug 21 12:02 myfile.fq.gz
Note: supported input file extensions include
.fq.xz and also
.fastq.xz. For FASTQ files with a different extension, use
--input fastq to inform Genozip that this is FASTQ data.
--REFERENCE instead of
--reference to store the reference data as part of the compressed file, obliviating the need for a separate reference file when uncompressing. This is in particular beneficial when binding multiple files together with –output, see Archiving.
Compressing a paired-end FASTQ files
For paired-end FASTQ files, it is advisable to compress the two files together, as this improves the compression ratio:
$ genozip --reference hs37d5.ref.genozip --pair myfile-R1.fq.gz myfile-R2.fq.gz genozip myfile-R1.fq.gz : Done (2 seconds) genozip myfile-R2.fq.gz : Done (8 seconds, FASTQ compression ratio: 20.3 - better than .fq.gz by a factor of 4.3) $ ls -l myfile* -rwxrwxrwx 1 divon divon 3624227 Aug 21 12:50 myfile-R1+2.fastq.genozip -rwxrwxrwx 1 divon divon 7338338 Aug 21 12:02 myfile-R1.fq.gz -rwxrwxrwx 1 divon divon 8232187 Aug 21 12:02 myfile-R2.fq.gz
genocat myfile-R1+2.fq.genozip --component 1
genocat myfile-R1+2.fq.genozip --component 2
Many downstream bioinforamtics tools can accept paired-end FASTQ data in interleaved format, for example bwa mem -p. To access the data in interleaved format:
genocat myfile-R1+2.fq.genozip --interleaved
Some useful command line options (for a full list, see genozip manual):
genozip --test myfile.fq.gz: after completing the compression, the file is uncompressed in memory, and its MD5 is compared to that of the original file.
genozip --replace myfile.fq.gz: the original file is removed after successful compression
Compressing multiple files into a tar archive
genozip *.fq.gz --reference hs37d5.ref.genozip --tar mydata.tar.
These are options that modify the file in ways that improve compression.
--optimize is an umbrella option that activates all optimization options.
genozip myfile.fq.gz --reference hs37d5.ref.genozip --optimize-DESC
Replaces the description line with @filename:read_number. Also - if the 3rd line (the ‘+’ line) contains a copy of the description it is shortened to just ‘+’.
genozip myfile.fq.gz --reference hs37d5.ref.genozip --optimize-QUAL
The quality data is optimized as follows:
--stats can be used in
genocat to get a better understanding of the information content of the file. For example:
$ genocat --stats myfile-R1+2.fastq.genozip FASTQ files (paired): myfile-R1.fq.gz myfile-R2.fq.gz Reference: hs37d5.ref.genozip Sequences: 200,000 Dictionaries: 25 Vblocks: 6 x 16 MB Sections: 132 Genozip version: 12.0.30 github Date compressed: 2021-08-21 18:34:02 Cen. Australia Daylight Time License v12.0.29 granted to: ***** accepted by:***** on 2021-08-18 20:30:56 Cen. Australia Daylight Time from IP=***** Sections (sorted by % of genozip file): NAME GENOZIP % TXT % RATIO QUAL 2.0 MB 58.3% 28.3 MB 40.3% 14.1X SEQ 1.3 MB 37.5% 28.3 MB 40.3% 21.9X DESC 144.9 KB 4.1% 12.5 MB 17.8% 88.2X Other 1.1 KB 0.0% 1.1 MB 1.6% 1097.9X TXT_HEADER 696 B 0.0% - 0.0% 0.0X LINE3 246 B 0.0% - 0.0% 0.0X BGZF 112 B 0.0% - 0.0% 0.0X GENOZIP vs BGZF 3.5 MB 100.0% 14.8 MB 100.0% 4.3X GENOZIP vs TXT 3.5 MB 100.0% 70.3 MB 100.0% 20.4X
In this paritcular example, we observe that the quality line consumes 58.3% of the total compressed file size. Therefore, we can expect that
--optimize-QUAL will significantly reduce the compressed file size. In contrast, the description line, in this case, consumes only 4.1% of the compressed file size. Therefore, we can expect that
--optimize-DESC will not significantly reduce the compressed file size.
Uncompresses a file.
Uncompresses a file into stdout (i.e. the terminal).
genounzip --index myfile.fq.genozip
Uncompresses a file and also generates a FAI index file, using samtools faidx. samtools needs to be installed for this option to work.
genounzip --output newname.fq.gz myfile.fq.genozip
Uncompressing to a particular name. Whether or not the name has a
.gz extension detemines whether the output file is BGZF-compressed.
genocat --bgzf 6 myfile.fq.genozip
genounzip --bgzf 6 myfile.fq.genozip
Sets the level BGZF compression (for .fq.gz output format) - from 0 (no compression) to 12 (best yet slowest compression). Absent this option,
genounzip attemps to recover the BGZF compression level of the original file, while
genocat uncompresses without BGZF compression.
Using in a pipeline
my-pipeline | genozip - --input fastq --output myfile.fq.genozip
genocat myfile.fq.genozip | my-pipeline # not paired-end
genocat myfile.R1+2.fq.genozip --interleaved | my-pipeline # paired-end
Showing only the Description, Sequence or Quality line for each read
genocat --header-only myfile.fq.genozip
genocat --seq-only myfile.fq.genozip
genocat --qual-only myfile.fq.genozip
genocat --downsample 10,0 myfile.fq.genozip
Displays only the first (#0) read in every 10 reads.
genocat --grep ACCTTAAT myfile.fq.genozip
Displays reads with the string “ACCTTAAT” anywhere in the read (description, seqeuence or quality lines) - possibly a substring of a longer string.
genocat --grep-w ACCTTAAT myfile.fq.genozip
Displays reads with the string “ACCTTAAT” exactly matching a component of the description, or the entire sequence line or the entire quality line.
Filtering non-ACTGN “bases”
genocat --bases ACGTN myfile.fq.genozip
Displays only reads in which all characters of the sequence are one of A,C,G,T,N
genocat --bases ^ACGTN myfile.fq.genozip
Displays only reads in which NOT all characters of the sequence are one of A,C,G,T,N
Note: The list of IUPAC chacacters can be found here: IUPAC codes
Filtering reads by species
Genozip has the ability to filter FASTQ files by species (taxonomy id). See Filtering BAM or FASTQ reads by species using kraken2.
genocat --idxstats myfile.fq.genozip
Per-contig coverage and depth
genocat --show-coverage myfile.fq.genozip
An experimental feature for calculating coverage and depth directly from a FASTQ file, see Coverage and Depth.
genocat --show-sex myfile.fq.genozip
An experimental feature for determining the sex of a sample from a FASTQ file, see Sex assignment.
By default, Genozip attempts to utilize as many cores as available. For that, it sets the number of threads to be a bit more than the number of cores (a practice known as “over-subscription”), as at any given moment some threads might be idle, waiting for a resource to become available. The
--threads <number> option allows explicit specification of the number of “compute threads” to be used (in addition a small number of I/O threads is used too, usually 1 or 2).
Memory (RAM) consumption
genozip, each compute thread is assigned a segment of the input file, known as a VBlock. By default, the size of the VBlock for most FASTQ files is 16MB, however it may be set explicitly with
genozip --vblock <megabytes> (<megabytes> is an integer between 1 and 2048). A larger VBlock usually results in better compression while a smaller VBlock causes
genozip to consume less RAM. The VBlock size can be observed at the top of the
genozip’s memory consumption is linear with (VBlock-size X number-of-threads).
genounzip also consume memory linearly with (VBlock-size X number-of-threads), where VBlock-size is the value used by
genozip of the particular file (it cannot be modified
genounzip consume significantly less memory compared to
When using a reference file, it is loaded to memory too. If multiple
genounzip processes are running in parallel, only one copy of the reference file is loaded to memory and shared between all processes, and depending on how busy the computer is, that reference file data might persist in RAM even between consecutive runs, saving Genozip the need to load it again from disk. All this all happens behind the scenes.