Evidence map›Paper›PMID 38085033›Full record

ArticleGenome biology and evolution2023

Patchwork: Alignment-Based Retrieval and Concatenation of Phylogenetic Markers from Genomic Data.

Felix Thalén, Clara G Köhne, Christoph Bleidorn

Abstract read
In one paragraph

Article in Genome biology and evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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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

3 authors.

Felix ThalénDepartment for Animal Evolution and Biodiversity, Georg-August-Universität Göttingen, Göttingen 37073, Germany.
Clara G KöhneDepartment for Animal Evolution and Biodiversity, Georg-August-Universität Göttingen, Göttingen 37073, Germany.
Christoph BleidornDepartment for Animal Evolution and Biodiversity, Georg-August-Universität Göttingen, Göttingen 37073, Germany.ORCID 0000-0001-7295-6616

Funding

Max Planck SocietyUniversity of Göttingen
6 · The paper itself

Abstract

Low-coverage whole-genome sequencing (also known as "genome skimming") is becoming an increasingly affordable approach to large-scale phylogenetic analyses. While already routinely used to recover organellar genomes, genome skimming is rather rarely utilized for recovering single-copy nuclear markers. One reason might be that only few tools exist to work with this data type within a phylogenomic context, especially to deal with fragmented genome assemblies. We here present a new software tool called Patchwork for mining phylogenetic markers from highly fragmented short-read assemblies as well as directly from sequence reads. Patchwork is an alignment-based tool that utilizes the sequence aligner DIAMOND and is written in the programming language Julia. Homologous regions are obtained via a sequence similarity search, followed by a "hit stitching" phase, in which adjacent or overlapping regions are merged into a single unit. The novel sliding window algorithm trims away any noncoding regions from the resulting sequence. We demonstrate the utility of Patchwork by recovering near-universal single-copy orthologs within a benchmarking study, and we additionally assess the performance of Patchwork in comparison with other programs. We find that Patchwork allows for accurate retrieval of (putatively) single-copy genes from genome skimming data sets at different sequencing depths with high computational speed, outperforming existing software targeting similar tasks. Patchwork is released under the GNU General Public License version 3. Installation instructions, additional documentation, and the source code itself are all available via GitHub at https://github.com/fethalen/Patchwork.

Indexed as

GenomeGenomicsHigh-Throughput Nucleotide SequencingPhylogenySequence Analysis, DNASoftwaregenome skimminglow-coverage sequencingmuseomicsphylogenomicsshort readssingle-copy genes

Identifiers

PMID38085033
PMCPMC10735302

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LicenceCC BY
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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.