Evidence map›Paper›PMID 30395202›Full record

ArticleBioinformatics (Oxford, England)2019

High-complexity regions in mammalian genomes are enriched for developmental genes.

Anton Pirogov, Peter Pfaffelhuber, Angelika Börsch-Haubold, Bernhard Haubold

Erratum issuedAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Unbiased anchors for reliable genome-wide synteny detection.Algorithms for molecular biology : AMB · 2025
    Article
  3. Article
  4. Fast detection of unique genomic regions.Computational and structural biotechnology journal · 2025
    Review
  5. Fast, parallel, and cache-friendly suffix array construction.Algorithms for molecular biology : AMB · 2024
    Article
  6. Article
  7. Marker discovery in the large.Bioinformatics advances · 2024
    Article
  8. Review
  9. Fur: Find unique genomic regions for diagnostic PCR.Bioinformatics (Oxford, England) · 2021
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Anton PirogovLehrstuhl für Informatik, RWTH Aachen University, Max-Planck-Institute for Evolutionary Biology, Plön, Germany.
Peter PfaffelhuberDepartment of Mathematical Stochastics, Freiburg University, Germany.
Angelika Börsch-Haubold24306 Plön, Germany.
Bernhard HauboldDepartment of Evolutionary Genetics, Max-Planck-Institute for Evolutionary Biology, Plön, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationUnique sequence regions are associated with genetic function in vertebrate genomes. However, measuring uniqueness, or absence of long repeats, along a genome is conceptually and computationally difficult. Here we use a variant of the Lempel-Ziv complexity, the match complexity, Cm, and augment it by deriving its null distribution for random sequences. We then apply Cm to the human and mouse genomes to investigate the relationship between sequence complexity and function.

resultsWe implemented Cm in the program macle and show through simulation that the newly derived null distribution of Cm is accurate. This allows us to delineate high-complexity regions in the human and mouse genomes. Using our program macle2go, we find that these regions are twofold enriched for genes. Moreover, the genes contained in these regions are more than 10-fold enriched for developmental functions. AVAILABILITY AND IMPLEMENTATION: Source code for macle and macle2go is available from www.github.com/evolbioinf/macle and www.github.com/evolbioinf/macle2go, respectively; Cm browser tracks from guanine.evolbio.mgp.de/complexity. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

GenomeGenomicsAnimalsGenes, DevelopmentalHumansMammalsMiceSoftware

Identifiers

PMID30395202
PMCPMC6546125

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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.