Evidence map›Paper›PMID 35579554›Full record

ArticleGigaScience2022

Generation and application of pseudo-long reads for metagenome assembly.

Mikang Sim, Jongin Lee, Suyeon Wy, Nayoung Park, Daehwan Lee, Daehong Kwon, Jaebum Kim

Abstract read
In one paragraph

Article in GigaScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

5 citing papers in PubMed.

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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

7 authors.

Mikang SimDepartment of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Republic of Korea.ORCID 0000-0002-8772-7071
Jongin LeeDepartment of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Republic of Korea.ORCID 0000-0001-7870-1526
Suyeon WyDepartment of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Republic of Korea.ORCID 0000-0003-1461-4815
Nayoung ParkDepartment of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Republic of Korea.ORCID 0000-0003-2722-0639
Daehwan LeeDepartment of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Republic of Korea.ORCID 0000-0002-1246-748X
Daehong KwonDepartment of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Republic of Korea.ORCID 0000-0003-2545-0430
Jaebum KimDepartment of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Republic of Korea.ORCID 0000-0002-2287-9760

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetagenomic assembly using high-throughput sequencing data is a powerful method to construct microbial genomes in environmental samples without cultivation. However, metagenomic assembly, especially when only short reads are available, is a complex and challenging task because mixed genomes of multiple microorganisms constitute the metagenome. Although long read sequencing technologies have been developed and have begun to be used for metagenomic assembly, many metagenomic studies have been performed based on short reads because the generation of long reads requires higher sequencing cost than short reads.

resultsIn this study, we present a new method called PLR-GEN. It creates pseudo-long reads from metagenomic short reads based on given reference genome sequences by considering small sequence variations existing in individual genomes of the same or different species. When applied to a mock community data set in the Human Microbiome Project, PLR-GEN dramatically extended short reads in length of 101 bp to pseudo-long reads with N50 of 33 Kbp and 0.4% error rate. The use of these pseudo-long reads generated by PLR-GEN resulted in an obvious improvement of metagenomic assembly in terms of the number of sequences, assembly contiguity, and prediction of species and genes.

conclusionsPLR-GEN can be used to generate artificial long read sequences without spending extra sequencing cost, thus aiding various studies using metagenomes.

Indexed as

MetagenomeMicrobiotaHigh-Throughput Nucleotide SequencingHumansMetagenomicsSequence Analysis, DNAmetagenomic assemblynext-generation sequencingpseudo–long read

Identifiers

PMID35579554
PMCPMC9112764

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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.