Demo Data from EDBT 2026 / reviewers in the wild / expert
N. Wirth
dblp:73/11537
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none
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 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › statistical genetics
genotype calling |
0.1 | 1 | 2012 | optiCall: a robust genotype-calling algorithm for rare, low-frequency and common variants · Bioinform. 2012 |
Bioinformatics and computational biology › genomics › variant calling
rare variant calling |
0.1 | 1 | 2012 | optiCall: a robust genotype-calling algorithm for rare, low-frequency and common variants · Bioinform. 2012 |
Methods — techniques the papers use, named apart from their topics
sample-wise calling · 0.1SNP-wise calling · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | optiCall: a robust genotype-calling algorithm for rare, low-frequency and common variantsabstractMOTIVATION: Existing microarray genotype-calling algorithms adopt either SNP-by-SNP (SNP-wise) or sample-by-sample (sample-wise) approaches to calling. We have developed a novel genotype-calling algorithm for the Illumina platform, optiCall, that uses both SNP-wise and sample-wise calling to more accurately ascertain genotypes at rare, low-frequency and common variants. RESULTS: Using data from 4537 individuals from the 1958 British Birth Cohort genotyped on the Immunochip, we estimate the proportion of SNPs lost to downstream analysis due to false quality control failures, and rare variants misclassified as monomorphic, is only 1.38% with optiCall, in comparison to 3.87, 7.85 and 4.09% for Illuminus, GenoSNP and GenCall, respectively. We show that optiCall accurately captures rare variants and can correctly account for SNPs where probe intensity clouds are shifted from their expected positions. AVAILABILITY AND IMPLEMENTATION: optiCall is implemented in C++ for use on UNIX operating systems and is available for download at http://www.sanger.ac.uk/resources/software/opticall/. T. S. Shah, Jimmy Zhenli Liu, J. A. B. Floyd, James A. Morris, N. Wirth, Jeffrey C. Barrett, Carl A. Anderson |
Bioinform. | 5 |