Evidence map›Paper›PMID 33176883›Full record

ArticleMicrobiome2020

A comprehensive investigation of metagenome assembly by linked-read sequencing.

Lu Zhang, Xiaodong Fang, Herui Liao, Zhenmiao Zhang, Xin Zhou, Lijuan Han, Yang Chen, Qinwei Qiu, Shuai Cheng Li

Open access · goldAbstract readVideo-Audio Media
In one paragraph

Article in Microbiome, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

10 citing papers in PubMed, 25 citations in OpenAlex.

  1. The Bioinformatic Applications of Hi-C and Linked Reads.Genomics, proteomics & bioinformatics · 2024
    Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Revolutionized virome research using systems microbiology approaches.Experimental biology and medicine (Maywood, N.J.) · 2022
    Review
  8. Article
  9. Article
  10. Bioinformatics advances · 2022
    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

9 authors at 5 institutions in 3 countries.

Lu ZhangDepartment of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China. ericluzhang@hkbu.edu.hk.ORCID 0000-0002-8157-9856
Xiaodong FangDepartment of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong, China.
Herui LiaoKMBGI GeneTech Co., Ltd., Shenzhen, Guangdong, China.
Zhenmiao ZhangDepartment of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China.
Xin ZhouDepartment of Computer Science, Stanford University, Stanford, CA, USA.
Lijuan HanKMBGI GeneTech Co., Ltd., Shenzhen, Guangdong, China.
Yang ChenState Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Qinwei QiuState Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Shuai Cheng LiDepartment of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong, China. shuaicli@cityu.edu.hk.
City University of Hong Kong · HKGuangzhou University of Chinese Medicine · CNHong Kong Baptist University · HKBeike Biotechnology (China) · CNStanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe human microbiota are complex systems with important roles in our physiological activities and diseases. Sequencing the microbial genomes in the microbiota can help in our interpretation of their activities. The vast majority of the microbes in the microbiota cannot be isolated for individual sequencing. Current metagenomics practices use short-read sequencing to simultaneously sequence a mixture of microbial genomes. However, these results are in ambiguity during genome assembly, leading to unsatisfactory microbial genome completeness and contig continuity. Linked-read sequencing is able to remove some of these ambiguities by attaching the same barcode to the reads from a long DNA fragment (10-100 kb), thus improving metagenome assembly. However, it is not clear how the choices for several parameters in the use of linked-read sequencing affect the assembly quality.

resultsWe first examined the effects of read depth (C) on metagenome assembly from linked-reads in simulated data and a mock community. The results showed that C positively correlated with the length of assembled sequences but had little effect on their qualities. The latter observation was corroborated by tests using real data from the human gut microbiome, where C demonstrated minor impact on the sequence quality as well as on the proportion of bins annotated as draft genomes. On the other hand, metagenome assembly quality was susceptible to read depth per fragment (C

conclusionsWe investigated the influence of linked-read sequencing parameters on metagenome assembly comprehensively. While the quality of genome assembly from linked-reads cannot rival that from PacBio CCS long-reads, the case for using linked-read sequencing remains persuasive due to its low cost and high base-quality. Our study revealed that the probable best practice in using linked-reads for metagenome assembly was to merge the linked-reads from multiple libraries, where each had sufficient C

Indexed as

High-Throughput Nucleotide SequencingHumansMetagenomeMetagenomicsMicrobiotaSequence Analysis, DNALinked-readsMetagenome assemblyPacBio CCS long-readsParameter spaceShort-reads

Identifiers

PMID33176883
PMCPMC7659138
OpenAlexW3098103638

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.