MCUIUC - A new framework for metagenomic read compression

Jonathan G. Ligo, Minji Kim, Amin Emad, Olgica Milenkovic, Venugopal V. Veeravalli

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Metagenomics is an emerging field of molecular biology concerned with analyzing the genomes of environmental samples comprising many different diverse organisms. Given the nature of metagenomic data, one usually has to sequence the genomic material of all organisms in a batch, leading to a mix of reads coming from different DNA sequences. In deep high-throughput sequencing experiments, the volume of the raw reads is extremely high, frequently exceeding 600 Gb. With an ever increasing demand for storing such reads for future studies, the issue of efficient metagenomic compression becomes of paramount importance. We present the first known approach to metagenome read compression, termed MCUIUC (Metagenomic Compression at UIUC). The gist of the proposed algorithm is to perform classification of reads based on unique organism identifiers, followed by reference-based alignment of reads for individually identified organisms, and metagenomic assembly of unclassified reads. Once assembly and classification are completed, lossless reference based compression is performed via positional encoding. We evaluate the performance of the algorithm on moderate sized synthetic metagenomic samples involving 15 randomly selected organisms and describe future directions for improving the proposed compression method.

Original languageEnglish (US)
Title of host publication2013 IEEE Information Theory Workshop, ITW 2013
StatePublished - 2013
Event2013 IEEE Information Theory Workshop, ITW 2013 - Seville, Spain
Duration: Sep 9 2013Sep 13 2013

Publication series

Name2013 IEEE Information Theory Workshop, ITW 2013


Other2013 IEEE Information Theory Workshop, ITW 2013

ASJC Scopus subject areas

  • Information Systems


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