Evidence map›Paper›PMID 25514851›Full record

ArticleGenome biology2014

Determining the quality and complexity of next-generation sequencing data without a reference genome.

Seyed Yahya Anvar, Lusine Khachatryan, Martijn Vermaat, Michiel van Galen, Irina Pulyakhina, Yavuz Ariyurek, Ken Kraaijeveld, Johan T den Dunnen, Peter de Knijff, Peter A C 't Hoen and 1 more

Abstract read
In one paragraph

Article in Genome biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
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  5. Factorial estimating assembly base errors usingNAR genomics and bioinformatics · 2020
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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

11 authors.

Seyed Yahya Anvar
Lusine Khachatryan
Martijn Vermaat
Michiel van Galen
Irina Pulyakhina
Yavuz Ariyurek
Ken Kraaijeveld
Johan T den Dunnen
Peter de Knijff
Peter A C 't Hoen
Jeroen F J Laros

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We describe an open-source kPAL package that facilitates an alignment-free assessment of the quality and comparability of sequencing datasets by analyzing k-mer frequencies. We show that kPAL can detect technical artefacts such as high duplication rates, library chimeras, contamination and differences in library preparation protocols. kPAL also successfully captures the complexity and diversity of microbiomes and provides a powerful means to study changes in microbial communities. Together, these features make kPAL an attractive and broadly applicable tool to determine the quality and comparability of sequence libraries even in the absence of a reference sequence. kPAL is freely available at https://github.com/LUMC/kPAL webcite.

Indexed as

AlgorithmsComputational BiologyGene LibraryGenome, HumanHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNASoftware

Identifiers

PMID25514851
PMCPMC4298064

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.