ArticleBioinformatics (Oxford, England)2015
iDoComp: a compression scheme for assembled genomes.
Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 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
- Bioinformatics tools for the sequence complexity estimates.Biophysical reviews · 2023Review
- Efficient compression of SARS-CoV-2 genome data using Nucleotide Archival Format.Patterns (New York, N.Y.) · 2022Review
- 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
- Efficient DNA sequence compression with neural networks.GigaScience · 2020Article
- Information Theory in Computational Biology: Where We Stand Today.Entropy (Basel, Switzerland) · 2020Article
- Sketch distance-based clustering of chromosomes for large genome database compression.BMC genomics · 2019Article
- HRCM: An Efficient Hybrid Referential Compression Method for Genomic Big Data.BioMed research international · 2019Article
- Algorithms designed for compressed-gene-data transformation among gene banks with different references.BMC bioinformatics · 2018Article
- Comparison of Compression-Based Measures with Application to the Evolution of Primate Genomes.Entropy (Basel, Switzerland) · 2018Article
- NRGC: a novel referential genome compression algorithm.Bioinformatics (Oxford, England) · 2016Article
- Comment on: 'ERGC: an efficient referential genome compression algorithm'.Bioinformatics (Oxford, England) · 2016Article
- ERGC: an efficient referential genome compression algorithm.Bioinformatics (Oxford, England) · 2015Article
- GDC 2: Compression of large collections of genomes.Scientific reports · 2015Article
- Sequence Factorization with Multiple References.PloS one · 2015Article
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Authors and funding
3 authors.
Funding
Abstract
motivationWith the release of the latest next-generation sequencing (NGS) machine, the HiSeq X by Illumina, the cost of sequencing a Human has dropped to a mere $4000. Thus we are approaching a milestone in the sequencing history, known as the $1000 genome era, where the sequencing of individuals is affordable, opening the doors to effective personalized medicine. Massive generation of genomic data, including assembled genomes, is expected in the following years. There is crucial need for compression of genomes guaranteed of performing well simultaneously on different species, from simple bacteria to humans, which will ease their transmission, dissemination and analysis. Further, most of the new genomes to be compressed will correspond to individuals of a species from which a reference already exists on the database. Thus, it is natural to propose compression schemes that assume and exploit the availability of such references.
resultsWe propose iDoComp, a compressor of assembled genomes presented in FASTA format that compresses an individual genome using a reference genome for both the compression and the decompression. In terms of compression efficiency, iDoComp outperforms previously proposed algorithms in most of the studied cases, with comparable or better running time. For example, we observe compression gains of up to 60% in several cases, including H.sapiens data, when comparing with the best compression performance among the previously proposed algorithms. AVAILABILITY: iDoComp is written in C and can be downloaded from: http://www.stanford.edu/~iochoa/iDoComp.html (We also provide a full explanation on how to run the program and an example with all the necessary files to run it.).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.