Demo Data from EDBT 2026 / reviewers in the wild / expert
James A. Morris
dblp:75/5073
· DBLP profile ↗
4ranked-venue papers
3as 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 · 4 · 3 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
4 papers |
Bioinformatics and computational biology · 100% |
Topics — the 8 heaviest of 9, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
genomics |
0.3 | 2 | 2012 | Olorin: combining gene flow with exome sequencing in large family studies of complex disease · Bioinform. 2012 Evoker: a visualization tool for genotype intensity data · Bioinform. 2010 |
Bioinformatics and computational biology › statistical genetics
complex disease genetics |
0.1 | 1 | 2012 | Olorin: combining gene flow with exome sequencing in large family studies of complex disease · Bioinform. 2012 |
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 › statistical genetics
pedigree analysis |
0.1 | 1 | 2012 | Olorin: combining gene flow with exome sequencing in large family studies of complex disease · 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 |
Bioinformatics and computational biology › statistical genetics
variant prioritization |
0.1 | 1 | 2012 | Olorin: combining gene flow with exome sequencing in large family studies of complex disease · Bioinform. 2012 |
Bioinformatics and computational biology › genomics
genome-wide association study |
0.1 | 1 | 2010 | Evoker: a visualization tool for genotype intensity data · Bioinform. 2010 |
Bioinformatics and computational biology › statistical genetics › genotype data analysis
genotype quality control |
0.1 | 1 | 2010 | Evoker: a visualization tool for genotype intensity data · Bioinform. 2010 |
Methods — techniques the papers use, named apart from their topics
sample-wise calling · 0.1gene flow analysis · 0.1exome sequencing integration · 0.1SNP-wise calling · 0.1data visualization · 0.1object-oriented programming · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Olorin: combining gene flow with exome sequencing in large family studies of complex diseaseabstractMOTIVATION: The existence of families with many individuals affected by the same complex disease has long suggested the possibility of rare alleles of high penetrance. In contrast to Mendelian diseases, however, linkage studies have identified very few reproducibly linked loci in diseases such as diabetes and autism. Genome-wide association studies have had greater success with such diseases, but these results explain neither the extreme disease load nor the within-family linkage peaks, of some large pedigrees. Combining linkage information with exome or genome sequencing from large complex disease pedigrees might finally identify family-specific, high-penetrance mutations. RESULTS: Olorin is a tool, which integrates gene flow within families with next generation sequencing data to enable the analysis of complex disease pedigrees. Users can interactively filter and prioritize variants based on haplotype sharing across selected individuals and other measures of importance, including predicted functional consequence and population frequency. James A. Morris, Jeffrey C. Barrett |
Bioinform. | 1 |
| 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. | 4 |
| 2010 | Evoker: a visualization tool for genotype intensity dataabstractSUMMARY: Genome-wide association studies (GWAS), which produce huge volumes of data, are now being carried out by many groups around the world, creating a need for user-friendly tools for data quality control (QC) and analysis. One critical aspect of GWAS QC is evaluating genotype cluster plots to verify sensible genotype calling in putatively associated single nucleotide polymorphisms (SNPs). Evoker is a tool for visualizing genotype cluster plots, and provides a solution to the computational and storage problems related to working with such large datasets. AVAILABILITY: http://www.sanger.ac.uk/resources/software/evoker/ James A. Morris, Joshua C. Randall, Julian B. Maller, Jeffrey C. Barrett |
Bioinform. | 1 |
| 2008 | A suite of Perl modules for handling microarray dataabstractUNLABELLED: We describe PerlMAT, a Perl microarray toolkit providing easy to use object-oriented methods for the simplified manipulation, management and analysis of microarray data. The toolkit provides objects for the encapsulation of microarray spots and reporters, several common microarray data file formats and GAL files. In addition, an analysis object provides methods for data processing, and an image object enables the visualisation of microarray data. This important addition to the Perl developer's library will facilitate more widespread use of Perl for microarray application development within the bioinformatics community. The coherent interface and well-documented code enables rapid analysis by even inexperienced Perl developers. AVAILABILITY: Software is available at http://sourceforge.net/projects/perlmat James A. Morris, Simon A. Gayther, Ian J. Jacobs, Christopher Jones 0005 |
Bioinform. | 1 |