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Susanne Balzer

dblp:91/8711 · DBLP profile ↗
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4ranked-venue papers
4as first author
0since 2021 · last 2013
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 4 · 4 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 · 100%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis
sequencing data processing
0.322013
Filtering duplicate reads from 454 pyrosequencing data · Bioinform. 2013
Systematic exploration of error sources in pyrosequencing flowgram data · Bioinform. 2011
Bioinformatics and computational biology › sequence analysis › sequencing read preprocessing
duplicate read removal
0.212013
Filtering duplicate reads from 454 pyrosequencing data · Bioinform. 2013
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
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

simulation · 0.2read clustering · 0.2bayesian distance measures · 0.2empirical distribution modeling · 0.1
YearPublicationVenuePosition
2013 Filtering duplicate reads from 454 pyrosequencing data
abstract
MOTIVATION: Throughout the recent years, 454 pyrosequencing has emerged as an efficient alternative to traditional Sanger sequencing and is widely used in both de novo whole-genome sequencing and metagenomics. Especially the latter application is extremely sensitive to sequencing errors and artificially duplicated reads. Both are common in 454 pyrosequencing and can create a strong bias in the estimation of diversity and composition of a sample. To date, there are several tools that aim to remove both sequencing noise and duplicates. Nevertheless, duplicate removal is often based on nucleotide sequences rather than on the underlying flow values, which contain additional information. RESULTS: With the novel tool JATAC, we present an approach towards a more accurate duplicate removal by analysing flow values directly. Making use of previous findings on 454 flow data characteristics, we combine read clustering with Bayesian distance measures. Finally, we provide a benchmark with an existing algorithm. AVAILABILITY: JATAC is freely available under the General Public License from http://malde.org/ketil/jatac/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Susanne Balzer, Ketil Malde, Markus A. Grohme, Inge Jonassen
Bioinform.1
2011 Systematic exploration of error sources in pyrosequencing flowgram data
abstract
MOTIVATION: 454 pyrosequencing, by Roche Diagnostics, has emerged as an alternative to Sanger sequencing when it comes to read lengths, performance and cost, but shows higher per-base error rates. Although there are several tools available for noise removal, targeting different application fields, data interpretation would benefit from a better understanding of the different error types. RESULTS: By exploring 454 raw data, we quantify to what extent different factors account for sequencing errors. In addition to the well-known homopolymer length inaccuracies, we have identified errors likely to originate from other stages of the sequencing process. We use our findings to extend the flowsim pipeline with functionalities to simulate these errors, and thus enable a more realistic simulation of 454 pyrosequencing data with flowsim. AVAILABILITY: The flowsim pipeline is freely available under the General Public License from http://biohaskell.org/Applications/FlowSim. CONTACT: [email protected].
Susanne Balzer, Ketil Malde, Inge Jonassen
Bioinform.1
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.1
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.1