---
_id: '10927'
abstract:
- lang: eng
  text: "Motivation\r\nHigh plasticity of bacterial genomes is provided by numerous
    mechanisms including horizontal gene transfer and recombination via numerous flanking
    repeats. Genome rearrangements such as inversions, deletions, insertions and duplications
    may independently occur in different strains, providing parallel adaptation or
    phenotypic diversity. Specifically, such rearrangements might be responsible for
    virulence, antibiotic resistance and antigenic variation. However, identification
    of such events requires laborious manual inspection and verification of phyletic
    pattern consistency.\r\nResults\r\nHere, we define the term ‘parallel rearrangements’
    as events that occur independently in phylogenetically distant bacterial strains
    and present a formalization of the problem of parallel rearrangements calling.
    We implement an algorithmic solution for the identification of parallel rearrangements
    in bacterial populations as a tool PaReBrick. The tool takes a collection of strains
    represented as a sequence of oriented synteny blocks and a phylogenetic tree as
    input data. It identifies rearrangements, tests them for consistency with a tree,
    and sorts the events by their parallelism score. The tool provides diagrams of
    the neighbors for each block of interest, allowing the detection of horizontally
    transferred blocks or their extra copies and the inversions in which copied blocks
    are involved. We demonstrated PaReBrick’s efficiency and accuracy and showed its
    potential to detect genome rearrangements responsible for pathogenicity and adaptation
    in bacterial genomes."
acknowledgement: "The authors thank the 2020 student class of the Bioinformatics Institute,
  who\r\nused the first versions of the tool and provided many valuable suggestions
  to\r\nimprove usability. They also thank Louisa Gonzalez Somermeyer for manuscript
  proofreading\r\nThis work was supported by the National Center for Cognitive Research
  of\r\nITMO University and JetBrains Research [to A.Z and N.A.]; and the European\r\nUnion’s
  Horizon 2020 Research and Innovation Programme under the Marie\r\nSkłodowska-Curie
  [754411 to O.B.].\r\nPaReBrick is written in Python and is available on GitHub:
  https://github.com/ctlab/parallel-rearrangements."
article_processing_charge: No
article_type: original
author:
- first_name: Alexey
  full_name: Zabelkin, Alexey
  last_name: Zabelkin
- first_name: Yulia
  full_name: Yakovleva, Yulia
  last_name: Yakovleva
- first_name: Olga
  full_name: Bochkareva, Olga
  id: C4558D3C-6102-11E9-A62E-F418E6697425
  last_name: Bochkareva
  orcid: 0000-0003-1006-6639
- first_name: Nikita
  full_name: Alexeev, Nikita
  last_name: Alexeev
citation:
  ama: 'Zabelkin A, Yakovleva Y, Bochkareva O, Alexeev N. PaReBrick: PArallel REarrangements
    and BReaks identification toolkit. <i>Bioinformatics</i>. 2022;38(2):357-363.
    doi:<a href="https://doi.org/10.1093/bioinformatics/btab691">10.1093/bioinformatics/btab691</a>'
  apa: 'Zabelkin, A., Yakovleva, Y., Bochkareva, O., &#38; Alexeev, N. (2022). PaReBrick:
    PArallel REarrangements and BReaks identification toolkit. <i>Bioinformatics</i>.
    Oxford Academic. <a href="https://doi.org/10.1093/bioinformatics/btab691">https://doi.org/10.1093/bioinformatics/btab691</a>'
  chicago: 'Zabelkin, Alexey, Yulia Yakovleva, Olga Bochkareva, and Nikita Alexeev.
    “PaReBrick: PArallel REarrangements and BReaks Identification Toolkit.” <i>Bioinformatics</i>.
    Oxford Academic, 2022. <a href="https://doi.org/10.1093/bioinformatics/btab691">https://doi.org/10.1093/bioinformatics/btab691</a>.'
  ieee: 'A. Zabelkin, Y. Yakovleva, O. Bochkareva, and N. Alexeev, “PaReBrick: PArallel
    REarrangements and BReaks identification toolkit,” <i>Bioinformatics</i>, vol.
    38, no. 2. Oxford Academic, pp. 357–363, 2022.'
  ista: 'Zabelkin A, Yakovleva Y, Bochkareva O, Alexeev N. 2022. PaReBrick: PArallel
    REarrangements and BReaks identification toolkit. Bioinformatics. 38(2), 357–363.'
  mla: 'Zabelkin, Alexey, et al. “PaReBrick: PArallel REarrangements and BReaks Identification
    Toolkit.” <i>Bioinformatics</i>, vol. 38, no. 2, Oxford Academic, 2022, pp. 357–63,
    doi:<a href="https://doi.org/10.1093/bioinformatics/btab691">10.1093/bioinformatics/btab691</a>.'
  short: A. Zabelkin, Y. Yakovleva, O. Bochkareva, N. Alexeev, Bioinformatics 38 (2022)
    357–363.
date_created: 2022-03-27T22:01:46Z
date_published: 2022-01-15T00:00:00Z
date_updated: 2023-08-03T06:21:46Z
day: '15'
ddc:
- '000'
department:
- _id: FyKo
doi: 10.1093/bioinformatics/btab691
ec_funded: 1
external_id:
  isi:
  - '000743380100008'
file:
- access_level: open_access
  checksum: 4b5688ff9ac86180ccdf7f82fa33d926
  content_type: application/pdf
  creator: dernst
  date_created: 2022-03-28T08:07:46Z
  date_updated: 2022-03-28T08:07:46Z
  file_id: '10930'
  file_name: 2022_Bioinformatics_Zabelkin.pdf
  file_size: 3425744
  relation: main_file
  success: 1
file_date_updated: 2022-03-28T08:07:46Z
has_accepted_license: '1'
intvolume: '        38'
isi: 1
issue: '2'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
page: 357-363
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '754411'
  name: ISTplus - Postdoctoral Fellowships
publication: Bioinformatics
publication_identifier:
  eissn:
  - 1460-2059
  issn:
  - 1367-4803
publication_status: published
publisher: Oxford Academic
quality_controlled: '1'
related_material:
  link:
  - relation: software
    url: https://github.com/ctlab/parallel-rearrangements
scopus_import: '1'
status: public
title: 'PaReBrick: PArallel REarrangements and BReaks identification toolkit'
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 38
year: '2022'
...
---
_id: '8645'
abstract:
- lang: eng
  text: 'Epistasis, the context-dependence of the contribution of an amino acid substitution
    to fitness, is common in evolution. To detect epistasis, fitness must be measured
    for at least four genotypes: the reference genotype, two different single mutants
    and a double mutant with both of the single mutations. For higher-order epistasis
    of the order n, fitness has to be measured for all 2n genotypes of an n-dimensional
    hypercube in genotype space forming a ‘combinatorially complete dataset’. So far,
    only a handful of such datasets have been produced by manual curation. Concurrently,
    random mutagenesis experiments have produced measurements of fitness and other
    phenotypes in a high-throughput manner, potentially containing a number of combinatorially
    complete datasets. We present an effective recursive algorithm for finding all
    hypercube structures in random mutagenesis experimental data. To test the algorithm,
    we applied it to the data from a recent HIS3 protein dataset and found all 199
    847 053 unique combinatorially complete genotype combinations of dimensionality
    ranging from 2 to 12. The algorithm may be useful for researchers looking for
    higher-order epistasis in their high-throughput experimental data.'
acknowledgement: 'This work was supported by the European Research Council under the
  European Union’s Seventh Framework Programme (FP7/2007-2013, ERC grant agreement
  335980_EinME) and Startup package to the Ivankov laboratory at Skolkovo Institute
  of Science and Technology. The work was started at the School of Molecular and Theoretical
  Biology 2017 supported by the Zimin Foundation. N.S.B. was supported by the Woman
  Scientists Support Grant in Centre for Genomic Regulation (CRG). '
article_processing_charge: No
article_type: original
author:
- first_name: Laura A
  full_name: Esteban, Laura A
  last_name: Esteban
- first_name: Lyubov R
  full_name: Lonishin, Lyubov R
  last_name: Lonishin
- first_name: Daniil M
  full_name: Bobrovskiy, Daniil M
  last_name: Bobrovskiy
- first_name: Gregory
  full_name: Leleytner, Gregory
  last_name: Leleytner
- first_name: Natalya S
  full_name: Bogatyreva, Natalya S
  last_name: Bogatyreva
- first_name: Fyodor
  full_name: Kondrashov, Fyodor
  id: 44FDEF62-F248-11E8-B48F-1D18A9856A87
  last_name: Kondrashov
  orcid: 0000-0001-8243-4694
- first_name: 'Dmitry N '
  full_name: 'Ivankov, Dmitry N '
  last_name: Ivankov
citation:
  ama: 'Esteban LA, Lonishin LR, Bobrovskiy DM, et al. HypercubeME: Two hundred million
    combinatorially complete datasets from a single experiment. <i>Bioinformatics</i>.
    2020;36(6):1960-1962. doi:<a href="https://doi.org/10.1093/bioinformatics/btz841">10.1093/bioinformatics/btz841</a>'
  apa: 'Esteban, L. A., Lonishin, L. R., Bobrovskiy, D. M., Leleytner, G., Bogatyreva,
    N. S., Kondrashov, F., &#38; Ivankov, D. N. (2020). HypercubeME: Two hundred million
    combinatorially complete datasets from a single experiment. <i>Bioinformatics</i>.
    Oxford Academic. <a href="https://doi.org/10.1093/bioinformatics/btz841">https://doi.org/10.1093/bioinformatics/btz841</a>'
  chicago: 'Esteban, Laura A, Lyubov R Lonishin, Daniil M Bobrovskiy, Gregory Leleytner,
    Natalya S Bogatyreva, Fyodor Kondrashov, and Dmitry N  Ivankov. “HypercubeME:
    Two Hundred Million Combinatorially Complete Datasets from a Single Experiment.”
    <i>Bioinformatics</i>. Oxford Academic, 2020. <a href="https://doi.org/10.1093/bioinformatics/btz841">https://doi.org/10.1093/bioinformatics/btz841</a>.'
  ieee: 'L. A. Esteban <i>et al.</i>, “HypercubeME: Two hundred million combinatorially
    complete datasets from a single experiment,” <i>Bioinformatics</i>, vol. 36, no.
    6. Oxford Academic, pp. 1960–1962, 2020.'
  ista: 'Esteban LA, Lonishin LR, Bobrovskiy DM, Leleytner G, Bogatyreva NS, Kondrashov
    F, Ivankov DN. 2020. HypercubeME: Two hundred million combinatorially complete
    datasets from a single experiment. Bioinformatics. 36(6), 1960–1962.'
  mla: 'Esteban, Laura A., et al. “HypercubeME: Two Hundred Million Combinatorially
    Complete Datasets from a Single Experiment.” <i>Bioinformatics</i>, vol. 36, no.
    6, Oxford Academic, 2020, pp. 1960–62, doi:<a href="https://doi.org/10.1093/bioinformatics/btz841">10.1093/bioinformatics/btz841</a>.'
  short: L.A. Esteban, L.R. Lonishin, D.M. Bobrovskiy, G. Leleytner, N.S. Bogatyreva,
    F. Kondrashov, D.N. Ivankov, Bioinformatics 36 (2020) 1960–1962.
date_created: 2020-10-11T22:01:14Z
date_published: 2020-03-15T00:00:00Z
date_updated: 2023-08-22T09:57:29Z
day: '15'
ddc:
- '000'
- '570'
department:
- _id: FyKo
doi: 10.1093/bioinformatics/btz841
ec_funded: 1
external_id:
  isi:
  - '000538696800054'
  pmid:
  - '31742320'
file:
- access_level: open_access
  checksum: 21d6f71839deb3b83e4a356193f72767
  content_type: application/pdf
  creator: dernst
  date_created: 2020-10-12T12:02:09Z
  date_updated: 2020-10-12T12:02:09Z
  file_id: '8649'
  file_name: 2020_Bioinformatics_Esteban.pdf
  file_size: 308341
  relation: main_file
  success: 1
file_date_updated: 2020-10-12T12:02:09Z
has_accepted_license: '1'
intvolume: '        36'
isi: 1
issue: '6'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: 1960-1962
pmid: 1
project:
- _id: 26120F5C-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '335980'
  name: Systematic investigation of epistasis in molecular evolution
publication: Bioinformatics
publication_identifier:
  eissn:
  - 1460-2059
  issn:
  - 1367-4803
publication_status: published
publisher: Oxford Academic
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'HypercubeME: Two hundred million combinatorially complete datasets from a
  single experiment'
tmp:
  image: /images/cc_by_nc.png
  legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode
  name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
  short: CC BY-NC (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 36
year: '2020'
...