Evidence map›Paper›PMID 31523495›Full record

ArticlePeerJ2019

The RIPper, a web-based tool for genome-wide quantification of Repeat-Induced Point (RIP) mutations.

Stephanie van Wyk, Christopher H Harrison, Brenda D Wingfield, Lieschen De Vos, Nicolaas A van der Merwe, Emma T Steenkamp

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
10.8field-weighted citation impact, top 2% 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

46 citing papers in PubMed, 84 citations in OpenAlex.

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  20. Comparative genomics of the extremophileFrontiers in fungal biology · 2024
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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

6 authors at 1 institution in 1 country.

Stephanie van WykDepartment of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, Gauteng, South Africa.
Christopher H HarrisonDepartment of product and software development, Amplo PTY, Pretoria, Gauteng, South Africa.
Brenda D WingfieldDepartment of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, Gauteng, South Africa.
Lieschen De VosDepartment of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, Gauteng, South Africa.
Nicolaas A van der MerweDepartment of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, Gauteng, South Africa.
Emma T SteenkampDepartment of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, Gauteng, South Africa.
University of Pretoria · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe RIPper (http://theripper.hawk.rocks) is a set of web-based tools designed for analyses of Repeat-Induced Point (RIP) mutations in the genome sequences of Ascomycota. The RIP pathway is a fungal genome defense mechanism that is aimed at identifying repeated and duplicated motifs, into which it then introduces cytosine to thymine transition mutations. RIP thus serves to deactivate and counteract the deleterious consequences of selfish or mobile DNA elements in fungal genomes. The occurrence, genetic context and frequency of RIP mutations are widely used to assess the activity of this pathway in genomic regions of interest. Here, we present a bioinformatics tool that is specifically fashioned to automate the investigation of changes in RIP product and substrate nucleotide frequencies in fungal genomes.

resultsWe demonstrated the ability of The RIPper to detect the occurrence and extent of RIP mutations in known RIP affected sequences. Specifically, a sliding window approach was used to perform genome-wide RIP analysis on the genome assembly of

conclusionThis software identified RIP targeted genomic regions and provided RIP statistics for an entire genome assembly, including the genomic proportion affected by RIP. Here, we present The RIPper as an efficient tool for genome-wide RIP analyses.

Indexed as

Fine-scale RIP analysesGenome-wide quantificationLarge RIP affected regionsRepeat-Induced Point mutationsRIPRIP profileThe RIPperWeb-based tool

Identifiers

PMID31523495
PMCPMC6714961
OpenAlexW2969727734

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.