Omega: an Overlap-graph<i>de novo</i>Assembler for Metagenomics is a research paper published in Bioinformatics (2014). On theSindex it has a DataRank of 4.1. It has been cited 96 times, with 89 citing works in its 1-hop citation network.
MotivationMetagenomic sequencing allows reconstruction of microbial genomes directly from environmental samples. Omega (overlap-graph metagenome assembler) was developed for assembling and scaffolding Illumina sequencing data of microbial communities.ResultsOmega found overlaps between reads using a prefix/suffix hash table. The overlap graph of reads was simplified by removing transitive edges and trimming short branches. Unitigs were generated based on minimum cost flow analysis of the overlap graph and then merged to contigs and scaffolds using mate-pair information. In comparison with three de Bruijn graph assemblers (SOAPdenovo, IDBA-UD and MetaVelvet), Omega provided comparable overall performance on a HiSeq 100-bp dataset and superior performance on a MiSeq 300-bp dataset. In comparison with Celera on the MiSeq dataset, Omega provided more continuous assemblies overall using a fraction of the computing time of existing overlap-layout-consensus assemblers. This indicates Omega can more efficiently assemble longer Illumina reads, and at deeper coverage, for metagenomic datasets.Availability and implementationImplemented in C++ with source code and binaries freely available at http://omega.omicsbio.org.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.686
From this paper's citation signal
Citation Network Contribution
3.4
From 73 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 17% comes from its base citations and 83% from the citation network (73 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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