Alla Lapidus

Prof. Dr. Alla Lapidus

Center for Bioinformatics and Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia
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Academic Career Length

30Years (1997-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 June 2020 in Current Protocols in Bioinformatics
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Journal Article
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APAndrey Prjibelski
Andrey Prjibelski
DADmitry Antipov
Dmitry Antipov
DMDmitry Meleshko
Dmitry Meleshko
Alla LapidusAlla Lapidus
Alla Lapidus
AKAnton Korobeynikov
Anton Korobeynikov
SPAdes—St. Petersburg genome Assembler—was originally developed for de novo assembly of genome sequencing data produced for cultivated microbial isolates and for single‐cell genomic DNA sequencing. With time, the functionality of SPAdes was extended to enable assembly of IonTorrent data, as well as hybrid assembly from short and long reads (PacBio and Oxford Nanopore). In this article we present protocols for five different assembly pipelines that comprise the SPAdes package and that are used for assembly of metagenomes and transcriptomes as well as assembly of putative plasmids and biosynthetic gene clusters from whole‐genome sequencing and metagenomic datasets. In addition, we present guidelines for understanding results with use cases for each pipeline, and several additional support protocols that help in using SPAdes properly. © 2020 Wiley Periodicals LLC.Basic Protocol 1: Assembling isolate bacterial datasetsBasic Protocol 2: Assembling metagenomic datasetsBasic Protocol 3: Assembling sets of putative plasmidsBasic Protocol 4: Assembling transcriptomesBasic Protocol 5: Assembling putative biosynthetic gene clustersSupport Protocol 1: Installing SPAdesSupport Protocol 2: Providing input via command lineSupport Protocol 3: Providing input data via YAML formatSupport Protocol 4: Restarting previous runSupport Protocol 5: Determining strand‐specificity of RNA‐seq data
20 November 1997 in Nature
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Journal Article
Open access
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FKF. Kunst
F. Kunst
NON. Ogasawara
N. Ogasawara
IMI. Moszer
I. Moszer
AAA. M. Albertini
A. M. Albertini
GAG. Alloni
G. Alloni
ADAntoine Danchin
Antoine Danchin
Bacillus subtilis is the best-characterized member of the Gram-positive bacteria. Its genome of 4,214,810 base pairs comprises 4,100 protein-coding genes. Of these protein-coding genes, 53% are represented once, while a quarter of the genome corresponds to several gene families that have been greatly expanded by gene duplication, the largest family containing 77 putative ATP-binding transport proteins. In addition, a large proportion of the genetic capacity is devoted to the utilization of a variety of carbon sources, including many plant-derived molecules. The identification of five signal peptidase genes, as well as several genes for components of the secretion apparatus, is important given the capacity of Bacillus strains to secrete large amounts of industrially important enzymes. Many of the genes are involved in the synthesis of secondary metabolites, including antibiotics, that are more typically associated with Streptomyces species. The genome contains at least ten prophages or remnants of prophages, indicating that bacteriophage infection has played an important evolutionary role in horizontal gene transfer, in particular in the propagation of bacterial pathogenesis.
1 August 2017 in Nature Biotechnology
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RBRobert M Bowers
Robert M Bowers
NKNikos C Kyrpides
Nikos C Kyrpides
RSRamunas Stepanauskas
Ramunas Stepanauskas
MHMiranda Harmon-Smith
Miranda Harmon-Smith
DDDevin Doud
Devin Doud
TWTanja Woyke
Tanja Woyke
We present two standards developed by the Genomic Standards Consortium (GSC) for reporting bacterial and archaeal genome sequences. Both are extensions of the Minimum Information about Any (x) Sequence (MIxS). The standards are the Minimum Information about a Single Amplified Genome (MISAG) and the Minimum Information about a Metagenome-Assembled Genome (MIMAG), including, but not limited to, assembly quality, and estimates of genome completeness and contamination. These standards can be used in combination with other GSC checklists, including the Minimum Information about a Genome Sequence (MIGS), Minimum Information about a Metagenomic Sequence (MIMS), and Minimum Information about a Marker Gene Sequence (MIMARKS). Community-wide adoption of MISAG and MIMAG will facilitate more robust comparative genomic analyses of bacterial and archaeal diversity.
1 October 2013 in Journal of Computational Biology
Verified
Journal Article
Closed access
SNSergey Nurk
Sergey Nurk
ABAnton Bankevich
Anton Bankevich
DADmitry Antipov
Dmitry Antipov
Alexey GurevichAlexey Gurevich
Alexey Gurevich
AKAnton Korobeynikov
Anton Korobeynikov
PPPavel A. Pevzner
Pavel A. Pevzner
Recent advances in single-cell genomics provide an alternative to largely gene-centric metagenomics studies, enabling whole-genome sequencing of uncultivated bacteria. However, single-cell assembly projects are challenging due to (i) the highly nonuniform read coverage and (ii) a greatly elevated number of chimeric reads and read pairs. While recently developed single-cell assemblers have addressed the former challenge, methods for assembling highly chimeric reads remain poorly explored. We present algorithms for identifying chimeric edges and resolving complex bulges in de Bruijn graphs, which significantly improve single-cell assemblies. We further describe applications of the single-cell assembler SPAdes to a new approach for capturing and sequencing “microbial dark matter” that forms small pools of randomly selected single cells (called a mini-metagenome) and further sequences all genomes from the mini-metagenome at once. On single-cell bacterial datasets, SPAdes improves on the recently developed E+V-SC and IDBA-UD assemblers specifically designed for single-cell sequencing. For standard (cultivated monostrain) datasets, SPAdes also improves on A5, ABySS, CLC, EULER-SR, Ray, SOAPdenovo, and Velvet. Thus, recently developed single-cell assemblers not only enable single-cell sequencing, but also improve on conventional assemblers on their own turf. SPAdes is available for free online download under a GPLv2 license.
1 September 2019 in GigaScience
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Journal Article
Open access
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EBElena Bushmanova
Elena Bushmanova
DADmitry Antipov
Dmitry Antipov
Alla LapidusAlla Lapidus
Alla Lapidus
APAndrey Prjibelski
Andrey Prjibelski
The possibility of generating large RNA-sequencing datasets has led to development of various reference-based and de novo transcriptome assemblers with their own strengths and limitations. While reference-based tools are widely used in various transcriptomic studies, their application is limited to the organisms with finished and well-annotated genomes. De novo transcriptome reconstruction from short reads remains an open challenging problem, which is complicated by the varying expression levels across different genes, alternative splicing, and paralogous genes. Herein we describe the novel transcriptome assembler rnaSPAdes, which has been developed on top of the SPAdes genome assembler and explores computational parallels between assembly of transcriptomes and single-cell genomes. We also present quality assessment reports for rnaSPAdes assemblies, compare it with modern transcriptome assembly tools using several evaluation approaches on various RNA-sequencing datasets, and briefly highlight strong and weak points of different assemblers. Based on the performed comparison between different assembly methods, we infer that it is not possible to detect the absolute leader according to all quality metrics and all used datasets. However, rnaSPAdes typically outperforms other assemblers by such important property as the number of assembled genes and isoforms, and at the same time has higher accuracy statistics on average comparing to the closest competitors.
7 November 2019 in Nucleic Acids Research
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Journal Article
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AMAlex L Mitchell
Alex L Mitchell
AAAlexandre Almeida
Alexandre Almeida
MBMartin Beracochea
Martin Beracochea
MBMiguel Boland
Miguel Boland
JBJosephine Burgin
Josephine Burgin
RFRobert D Finn
Robert D Finn
MGnify (http://www.ebi.ac.uk/metagenomics) provides a free to use platform for the assembly, analysis and archiving of microbiome data derived from sequencing microbial populations that are present in particular environments. Over the past 2 years, MGnify (formerly EBI Metagenomics) has more than doubled the number of publicly available analysed datasets held within the resource. Recently, an updated approach to data analysis has been unveiled (version 5.0), replacing the previous single pipeline with multiple analysis pipelines that are tailored according to the input data, and that are formally described using the Common Workflow Language, enabling greater provenance, reusability, and reproducibility. MGnify's new analysis pipelines offer additional approaches for taxonomic assertions based on ribosomal internal transcribed spacer regions (ITS1/2) and expanded protein functional annotations. Biochemical pathways and systems predictions have also been added for assembled contigs. MGnify's growing focus on the assembly of metagenomic data has also seen the number of datasets it has assembled and analysed increase six-fold. The non-redundant protein database constructed from the proteins encoded by these assemblies now exceeds 1 billion sequences. Meanwhile, a newly developed contig viewer provides fine-grained visualisation of the assembled contigs and their enriched annotations.