ArticleScientific reports2015
GDC 2: Compression of large collections of genomes.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Vertical lossless genomic data compression tools for assembled genomes: A systematic literature review.PloS one · 2020Pooled it
- MBGC2: Boosting compression via efficient encoding of approximate matches in genome collections.GigaScience · 2026Article
- Reference-based genome compression using the longest matched substrings with parallelization consideration.BMC bioinformatics · 2023Article
- AGC: compact representation of assembled genomes with fast queries and updates.Bioinformatics (Oxford, England) · 2023Article
- SparkGC: Spark based genome compression for large collections of genomes.BMC bioinformatics · 2022Article
- A Hybrid Data-Differencing and Compression Algorithm for the Automotive Industry.Entropy (Basel, Switzerland) · 2022Article
- MBGC: Multiple Bacteria Genome Compressor.GigaScience · 2022Article
- Constructing small genome graphs via string compression.Bioinformatics (Oxford, England) · 2021Article
- Efficient DNA sequence compression with neural networks.GigaScience · 2020Article
- Sketch distance-based clustering of chromosomes for large genome database compression.BMC genomics · 2019Article
- Tackling the Challenges of FASTQ Referential Compression.Bioinformatics and biology insights · 2019Article
- HRCM: An Efficient Hybrid Referential Compression Method for Genomic Big Data.BioMed research international · 2019Article
- Comparison of Compression-Based Measures with Application to the Evolution of Primate Genomes.Entropy (Basel, Switzerland) · 2018Article
- Comment on: 'ERGC: an efficient referential genome compression algorithm'.Bioinformatics (Oxford, England) · 2016Article
- Sequence Factorization with Multiple References.PloS one · 2015Article
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Authors and funding
3 authors.
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Abstract
The fall of prices of the high-throughput genome sequencing changes the landscape of modern genomics. A number of large scale projects aimed at sequencing many human genomes are in progress. Genome sequencing also becomes an important aid in the personalized medicine. One of the significant side effects of this change is a necessity of storage and transfer of huge amounts of genomic data. In this paper we deal with the problem of compression of large collections of complete genomic sequences. We propose an algorithm that is able to compress the collection of 1092 human diploid genomes about 9,500 times. This result is about 4 times better than what is offered by the other existing compressors. Moreover, our algorithm is very fast as it processes the data with speed 200 MB/s on a modern workstation. In a consequence the proposed algorithm allows storing the complete genomic collections at low cost, e.g., the examined collection of 1092 human genomes needs only about 700 MB when compressed, what can be compared to about 6.7 TB of uncompressed FASTA files. The source code is available at http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&project=gdc&subpage=about.
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