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Anders Lanzén

dblp:68/5381 · DBLP profile ↗
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5ranked-venue papers
1as first author
0since 2021 · last 2020
0000-0002-7138-6364ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 5 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
3 papers
Bioinformatics and computational biology · 84% Computational science and engineering · 16%

Topics — the 8 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › transcriptomics
metatranscriptomics
0.412020
Reconstructing ribosomal genes from large scale total RNA meta-transcriptomic data · Bioinform. 2020
Bioinformatics and computational biology › computational microbiology › microbiome analysis
microbial community analysis
0.112020
Reconstructing ribosomal genes from large scale total RNA meta-transcriptomic data · Bioinform. 2020
Bioinformatics and computational biology › next-generation sequencing
next-generation sequencing simulation
0.112010
Characteristics of 454 pyrosequencing data - enabling realistic simulation with flowsim · Bioinform. 2010
Bioinformatics and computational biology
sequence analysis
0.112010
Characteristics of 454 pyrosequencing data - enabling realistic simulation with flowsim · Bioinform. 2010
Computational science and engineering
scientific workflow
0.112008
The Taverna Interaction Service: enabling manual interaction in workflows · Bioinform. 2008
Computational science and engineering
workflow management
0.112008
The Taverna Interaction Service: enabling manual interaction in workflows · Bioinform. 2008
Bioinformatics and computational biology › sequence analysis › sequence assembly › genome assembly
assembly quality assessment
0.012010
Characteristics of 454 pyrosequencing data - enabling realistic simulation with flowsim · Bioinform. 2010
Bioinformatics and computational biology › sequence analysis › sequence assembly
genome assembly
0.012010
Characteristics of 454 pyrosequencing data - enabling realistic simulation with flowsim · Bioinform. 2010

Methods — techniques the papers use, named apart from their topics

sub-assembly · 0.4read mapping · 0.4iterative assembly · 0.4dereplication · 0.4simulation · 0.1empirical distribution modeling · 0.1workflow engine · 0.1mediation layer · 0.1
YearPublicationVenuePosition
2020 Reconstructing ribosomal genes from large scale total RNA meta-transcriptomic data
abstract
MOTIVATION: Technological advances in meta-transcriptomics have enabled a deeper understanding of the structure and function of microbial communities. 'Total RNA' meta-transcriptomics, sequencing of total reverse transcribed RNA, provides a unique opportunity to investigate both the structure and function of active microbial communities from all three domains of life simultaneously. A major step of this approach is the reconstruction of full-length taxonomic marker genes such as the small subunit ribosomal RNA. However, current tools for this purpose are mainly targeted towards analysis of amplicon and metagenomic data and thus lack the ability to handle the massive and complex datasets typically resulting from total RNA experiments. RESULTS: In this work, we introduce MetaRib, a new tool for reconstructing ribosomal gene sequences from total RNA meta-transcriptomic data. MetaRib is based on the popular rRNA assembly program EMIRGE, together with several improvements. We address the challenge posed by large complex datasets by integrating sub-assembly, dereplication and mapping in an iterative approach, with additional post-processing steps. We applied the method to both simulated and real-world datasets. Our results show that MetaRib can deal with larger datasets and recover more rRNA genes, which achieve around 60 times speedup and higher F1 score compared to EMIRGE in simulated datasets. In the real-world dataset, it shows similar trends but recovers more contigs compared with a previous analysis based on random sub-sampling, while enabling the comparison of individual contig abundances across samples for the first time. AVAILABILITY AND IMPLEMENTATION: The source code of MetaRib is freely available at https://github.com/yxxue/MetaRib. CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Yaxin Xue, Anders Lanzén, Inge Jonassen
Bioinform.2
2011 Characteristics of 454 pyrosequencing data - enabling realistic simulation with flowsim
abstract
Bioinformatics (2010) 26(18), i420–i425. The authors would like to apologize for an error in the calculation of the number of bases, number of flow values and average read length. Our reads turned out to be a lot shorter than previously reported. None of these errors has implications on the method or the results. The corrected table is shown below. Data basis for building the empirical distributions aAfter 454 quality-trimming. bWithout N's. cHomopolymer lengths 1–5, equals to number of homopolymer runs in BLAST results. The error also affects Figure 1b, where the left part of the plot is to be compared with the right set of curves. The corrected figure is shown below. (b) Absolute frequencies of flow values (E.coli). Left: original data, no quality-trimming; right: quality-trimmed. The trimming algorithm enhances the separation of the homopolymer length distributions and levels out discrepancies between the nucleotides such that the curves for the four nucleotides are nearly identical.
Susanne Balzer, Ketil Malde, Anders Lanzén, Animesh Sharma, Inge Jonassen
Bioinform.3
2011 Removing Noise From Pyrosequenced Amplicons
abstract
BACKGROUND: In many environmental genomics applications a homologous region of DNA from a diverse sample is first amplified by PCR and then sequenced. The next generation sequencing technology, 454 pyrosequencing, has allowed much larger read numbers from PCR amplicons than ever before. This has revolutionised the study of microbial diversity as it is now possible to sequence a substantial fraction of the 16S rRNA genes in a community. However, there is a growing realisation that because of the large read numbers and the lack of consensus sequences it is vital to distinguish noise from true sequence diversity in this data. Otherwise this leads to inflated estimates of the number of types or operational taxonomic units (OTUs) present. Three sources of error are important: sequencing error, PCR single base substitutions and PCR chimeras. We present AmpliconNoise, a development of the PyroNoise algorithm that is capable of separately removing 454 sequencing errors and PCR single base errors. We also introduce a novel chimera removal program, Perseus, that exploits the sequence abundances associated with pyrosequencing data. We use data sets where samples of known diversity have been amplified and sequenced to quantify the effect of each of the sources of error on OTU inflation and to validate these algorithms. RESULTS: AmpliconNoise outperforms alternative algorithms substantially reducing per base error rates for both the GS FLX and latest Titanium protocol. All three sources of error lead to inflation of diversity estimates. In particular, chimera formation has a hitherto unrealised importance which varies according to amplification protocol. We show that AmpliconNoise allows accurate estimates of OTU number. Just as importantly AmpliconNoise generates the right OTUs even at low sequence differences. We demonstrate that Perseus has very high sensitivity, able to find 99% of chimeras, which is critical when these are present at high frequencies. CONCLUSIONS: AmpliconNoise followed by Perseus is a very effective pipeline for the removal of noise. In addition the principles behind the algorithms, the inference of true sequences using Expectation-Maximization (EM), and the treatment of chimera detection as a classification or 'supervised learning' problem, will be equally applicable to new sequencing technologies as they appear.
Christopher Quince, Anders Lanzén, Russell J. Davenport, Peter J. Turnbaugh
BMC Bioinform.2
2010 Characteristics of 454 pyrosequencing data - enabling realistic simulation with flowsim
abstract
MOTIVATION: The commercial launch of 454 pyrosequencing in 2005 was a milestone in genome sequencing in terms of performance and cost. Throughout the three available releases, average read lengths have increased to approximately 500 base pairs and are thus approaching read lengths obtained from traditional Sanger sequencing. Study design of sequencing projects would benefit from being able to simulate experiments. RESULTS: We explore 454 raw data to investigate its characteristics and derive empirical distributions for the flow values generated by pyrosequencing. Based on our findings, we implement Flowsim, a simulator that generates realistic pyrosequencing data files of arbitrary size from a given set of input DNA sequences. We finally use our simulator to examine the impact of sequence lengths on the results of concrete whole-genome assemblies, and we suggest its use in planning of sequencing projects, benchmarking of assembly methods and other fields. AVAILABILITY: Flowsim is freely available under the General Public License from http://blog.malde.org/index.php/flowsim/.
Susanne Balzer, Ketil Malde, Anders Lanzén, Animesh Sharma, Inge Jonassen
Bioinform.3
2008 The Taverna Interaction Service: enabling manual interaction in workflows
abstract
UNLABELLED: Taverna is an application that eases the integration of tools and databases for life science research by the construction of workflows. The Taverna Interaction Service extends the functionality of Taverna by defining human interaction within a workflow and acting as a mediation layer between the automated workflow engine and one or more users. AVAILABILITY: Taverna, the Interaction Service plug-in and web application are available as open source and can be downloaded from http://taverna.sourceforge.net/
Anders Lanzén, Thomas M. Oinn
Bioinform.1