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iDoComp: a compression scheme for assembled genomes.

Idoia Ochoa1, Mikel Hernaez1, Tsachy Weissman1

  • 1Department of Electrical Engineering, Stanford University, 350 Serra Mall, Stanford, CA.

Bioinformatics (Oxford, England)
|October 26, 2014
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Summary
This summary is machine-generated.

The new iDoComp tool offers significant genome compression, achieving up to 60% gains by utilizing reference genomes. This advancement aids in the transmission, dissemination, and analysis of massive genomic data for personalized medicine.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • The advent of next-generation sequencing (NGS) technologies, such as Illumina's HiSeq X, has drastically reduced sequencing costs, ushering in the era of the $1000 genome.
  • This reduction in cost facilitates personalized medicine and is expected to generate massive amounts of genomic data.
  • Efficient compression methods are crucial for managing, transmitting, and analyzing this growing volume of genomic information, especially when reference genomes are available.

Purpose of the Study:

  • To develop and present iDoComp, a novel algorithm for compressing assembled genomes in FASTA format.
  • To leverage the availability of reference genomes for enhanced compression efficiency.
  • To provide a tool that facilitates the storage, transmission, and analysis of large-scale genomic datasets.

Main Methods:

  • iDoComp utilizes a reference genome for both the compression and decompression of individual genomes.
  • The algorithm is implemented in C.
  • The software, along with usage instructions and example files, is publicly available.

Main Results:

  • iDoComp demonstrates superior compression efficiency compared to existing algorithms in most tested scenarios.
  • Compression gains of up to 60% were observed, including for Homo sapiens data.
  • The tool offers comparable or improved running times alongside its enhanced compression performance.

Conclusions:

  • iDoComp provides a highly effective solution for compressing assembled genomes, particularly when reference genomes are available.
  • The algorithm's performance surpasses previous methods, offering significant compression ratios.
  • This tool will aid researchers in managing and analyzing the increasing volume of genomic data generated by modern sequencing technologies.