Evidence map›Paper›PMID 27586129›Full record

ArticleBMC genomics2016

BASE: a practical de novo assembler for large genomes using long NGS reads.

Binghang Liu, Chi-Man Liu, Dinghua Li, Yingrui Li, Hing-Fung Ting, Siu-Ming Yiu, Ruibang Luo, Tak-Wah Lam

Abstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Draft genome sequence data ofData in brief · 2024
    Article
  2. Genome sequence ofMicrobiology resource announcements · 2024
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Binghang LiuBioinformatics Algorithms Research Laboratory, Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong.
Chi-Man LiuBioinformatics Algorithms Research Laboratory, Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong.
Dinghua LiBioinformatics Algorithms Research Laboratory, Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong.
Yingrui LiBioinformatics Algorithms Research Laboratory, Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong.
Hing-Fung TingBioinformatics Algorithms Research Laboratory, Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong.
Siu-Ming YiuBioinformatics Algorithms Research Laboratory, Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong.
Ruibang LuoBioinformatics Algorithms Research Laboratory, Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong. rbluo@cs.hku.hk.
Tak-Wah LamBioinformatics Algorithms Research Laboratory, Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong. twlam@cs.hku.hk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDe novo genome assembly using NGS data remains a computation-intensive task especially for large genomes. In practice, efficiency is often a primary concern and favors using a more efficient assembler like SOAPdenovo2. Yet SOAPdenovo2, based on de Bruijn graph, fails to take full advantage of longer NGS reads (say, 150 bp to 250 bp from Illumina HiSeq and MiSeq). Assemblers that are based on string graphs (e.g., SGA), though less popular and also very slow, are more favorable for longer reads.

methodsThis paper shows a new de novo assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs.

resultsExperiments on two bacteria and four human datasets shows the advantage of BASE in both contig quality and speed in dealing with longer reads. In the experiment on bacteria, two datasets with read length of 100 bp and 250 bp were used.. Especially for the 250 bp dataset, BASE gives much better quality than SOAPdenovo2 and SGA and is simlilar to SPAdes. Regarding speed, BASE is consistently a few times faster than SPAdes and SGA, but still slower than SOAPdenovo2. BASE and Soapdenov2 are further compared using human datasets with read length 100 bp, 150 bp and 250 bp. BASE shows a higher N50 for all datasets, while the improvement becomes more significant when read length reaches 250 bp. Besides, BASE is more-meory efficent than SOAPdenovo2 when sequencing data with error rate.

conclusionsBASE is a practically efficient tool for constructing contig, with significant improvement in quality for long NGS reads. It is relatively easy to extend BASE to include scaffolding.

Indexed as

High-Throughput Nucleotide SequencingAlgorithmsHumansSequence Analysis, DNASoftwareStaphylococcus aureusVibrio parahaemolyticus

Identifiers

PMID27586129
PMCPMC5009518

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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.