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Markus W. Löffler

dblp:209/7697 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
0000-0003-2513-1317ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 1

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
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
cancer genomics
0.312017
A comprehensive quality control workflow for paired tumor-normal NGS experiments · Bioinform. 2017
Bioinformatics and computational biology › genomics
next-generation sequencing data analysis
0.312017
A comprehensive quality control workflow for paired tumor-normal NGS experiments · Bioinform. 2017

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

qcML · 0.3ontology-based quality metrics · 0.3
YearPublicationVenuePosition
2017 A comprehensive quality control workflow for paired tumor-normal NGS experiments
abstract
SUMMARY: Quality control (QC) is an important part of all NGS data analysis stages. Many available tools calculate QC metrics from different analysis steps of single sample experiments (raw reads, mapped reads and variant lists). Multi-sample experiments, as sequencing of tumor-normal pairs, require additional QC metrics to ensure validity of results. These multi-sample QC metrics still lack standardization. We therefore suggest a new workflow for QC of DNA sequencing of tumor-normal pairs. With this workflow well-known single-sample QC metrics and additional metrics specific for tumor-normal pairs can be calculated. The segmentation into different tools offers a high flexibility and allows reuse for other purposes. All tools produce qcML, a generic XML format for QC of -omics experiments. qcML uses quality metrics defined in an ontology, which was adapted for NGS. AVAILABILITY AND IMPLEMENTATION: All QC tools are implemented in C ++ and run both under Linux and Windows. Plotting requires python 2.7 and matplotlib. The software is available under the 'GNU General Public License version 2' as part of the ngs-bits project: https://github.com/imgag/ngs-bits. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Christopher M. Schroeder, Franz J. Hilke, Markus W. Löffler, Michael Bitzer, Florian Lenz, Marc Sturm
Bioinform.3