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Gerard A. Bouland

dblp:258/2870 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

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
gene expression analysis
0.412020
NACHO: an R package for quality control of NanoString nCounter data · Bioinform. 2020
Bioinformatics and computational biology › gene expression analysis › gene expression data preprocessing
gene expression normalization
0.412020
NACHO: an R package for quality control of NanoString nCounter data · Bioinform. 2020

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

quality control pipeline · 0.4
YearPublicationVenuePosition
2020 NACHO: an R package for quality control of NanoString nCounter data
abstract
SUMMARY: The NanoStringTM nCounter® is a platform for the targeted quantification of expression data in biofluids and tissues. While software by the manufacturer is available in addition to third parties packages, they do not provide a complete quality control (QC) pipeline. Here, we present NACHO ('NAnostring quality Control dasHbOard'), a comprehensive QC R-package. The package consists of three subsequent steps: summarize, visualize and normalize. The summarize function collects all the relevant data and stores it in a tidy format, the visualize function initiates a dashboard with plots of the relevant QC outcomes. It contains QC metrics that are measured by default by the manufacturer, but also calculates other insightful measures, including the scaling factors that are needed in the normalization step. In this normalization step, different normalization methods can be chosen to optimally preprocess data. Together, NACHO is a comprehensive method that optimizes insight and preprocessing of nCounter® data. AVAILABILITY AND IMPLEMENTATION: NACHO is available as an R-package on CRAN and the development version on GitHub https://github.com/mcanouil/NACHO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Mickaël Canouil, Gerard A. Bouland, Amélie Bonnefond, Philippe Froguel, Leen M. 't Hart, Roderick C. Slieker
Bioinform.2