Sfasta is a side-project I've been working on. I'm training Transformer models and needed to use large datasets such as reads or databases. Block gzip, even when stored on a ramdisk, is far too slow to keep the GPU full, so I started working on an alternative format that allowed for better random-access. This is that format.
I hope it becomes a more general purpose format, saving space and time, but for me it has been a success for my needs already.
Currently it makes extensive use of bitpacking, as well as ZSTD compression. It supports others, which could be used for archival purposes (such as xz compression), but those functions are not connected to the command-line anymore. Size is generally favorable as-is, although disabling masking and indexing would make it even smaller.
Everything is bincoded, and either bitpacked, or ZSTD compressed.... add more here...
| Compression Type | Random Access | Multithreaded | |:---:|:---:|:----| | NAF | No | No | | ZSTD | No | Yes | | sfasta | Yes | Yes | | bgzip | Yes | Yes |
Samtools index pre-built
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:---|---:|---:|---:|---:|
| samtools faidx uniprot_sprot.fasta.gz "sp\|P10459\|3S1B_LATLA"
| 422.7 ± 4.7 | 417.8 | 433.3 | 3.42 ± 0.25 |
| sfa faidx uniprot_sprot.fasta.sfasta "sp\|P10459\|3S1B_LATLA"
| 123.5 ± 8.9 | 118.3 | 141.6 | 1.00 |
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:---|---:|---:|---:|---:|
| ennaf --protein uniprot_sprot.fasta --temp-dir /tmp
| 966.5 ± 32.2 | 924.6 | 1018.7 | 2.89 ± 0.18 |
| bgzip -k --index -f --threads 7 uniprot_sprot.fasta
| 719.7 ± 7.6 | 706.6 | 731.0 | 2.16 ± 0.12 |
| sfa convert uniprot_sprot.fasta
| 2676.7 ± 105.9 | 2394.8 | 2756.2 | 8.02 ± 0.53 |
| pigz -k -p 7 uniprot_sprot.fasta -f
| 771.5 ± 55.2 | 704.2 | 872.3 | 2.31 ± 0.21 |
| crabz -p 7 Erow_1.0.fasta -f > uniprot_sprot.crabz
| 10688.8 ± 224.7 | 10322.6 | 10990.7 | 32.01 ± 1.82 |
| zstd -k uniprot_sprot.fasta -f -T7
| 333.9 ± 17.6 | 303.4 | 351.6 | 1.00 |
Uncompressed: 282M
| Compression Type | Size | | --- | --- | | NAF | 68M | | bgzip* | 92M | | zstd | 78M | | sfasta | 83M | * Excludes index
Samtools index pre-built
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:---|---:|---:|---:|---:|
| samtools faidx Essy1B.fasta.gz ae278260-d941-45c9-9e76-40f04ef8e56c
| 935.1 ± 13.4 | 923.2 | 959.8 | 10.91 ± 0.65 |
| sfa faidx Essy1B.sfasta ae278260-d941-45c9-9e76-40f04ef8e56c
| 85.7 ± 4.9 | 83.1 | 104.6 | 1.00 |
Uncompressed Size: 8.8G | Compression Type | Size | | --- | --- | | NAF | 2.2G | | bgzip* | 2.6G | | sfasta | 2.6G |
Samtools index pre-built
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:---|---:|---:|---:|---:|
| samtools faidx Erow_1.0.fasta.gz PXIH01S0167520.1
| 184.6 ± 10.6 | 169.0 | 197.4 | 1.38 ± 0.15 |
| sfa faidx Erow_1.0.sfasta PXIH01S0167520.1
| 134.0 ± 12.1 | 118.4 | 154.1 | 1.00 |
| Command | Mean [s] | Min [s] | Max [s] | Relative |
|:---|---:|---:|---:|---:|
| ennaf Erow_1.0.fasta --temp-dir /tmp
| 8.111 ± 0.018 | 8.087 | 8.145 | 3.65 ± 0.11 |
| bgzip -k --index -f --threads 7 Erow_1.0.fasta
| 9.492 ± 0.442 | 8.940 | 9.975 | 4.27 ± 0.24 |
| sfa convert Erow_1.0.fasta
| 7.499 ± 0.477 | 6.914 | 8.345 | 3.37 ± 0.24 |
| pigz -k -p 7 Erow_1.0.fasta -f
| 10.833 ± 0.271 | 10.548 | 11.213 | 4.87 ± 0.19 |
| crabz -p 7 Erow_1.0.fasta > Erow_1.0.crabz
| 10.594 ± 0.171 | 10.387 | 10.971 | 4.76 ± 0.16 |
| zstd -k Erow_1.0.fasta -f -T7
| 2.224 ± 0.067 | 2.087 | 2.291 | 1.00 |
Uncompressed: 2.7G
| Compression Type | Size | |---|--| | NAF | 446M | | sfasta | 596M | | bgzip* | 635M | | Zstd | 663M |
There is plenty of room for additional speed-ups, including adding more threads for specific tasks, CPU affinities, native compilation, and probably using more Cow.
There is likely room to decrease size as well without hurting speed.
As I've refactored much of the library, the CLI code withered and decayed. Need to fix this.
To support FASTQ files
For other applications (such as long term storage)
To make it easier to use in other programs and in python/jupyter
Sfasta is currently optimized for larger files.
NAF has an advantage with 4bit encoding. It's possible to implement this, and use 2bit when possible, to gain additional speed-ups. Further, there is some SIMD support for 2bit and 4bit DNA/RNA encoding.
Graph genome file format is in dire need of an optimized format
NO. This somehow doubled the time it takes to compress binaries. Enable PGO for additional speed-ups