Demo Data from EDBT 2026 / reviewers in the wild / expert
D. Williams Parsons
dblp:294/5574
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
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 › cancer genomics › copy number analysis
copy number variation detection |
0.1 | 1 | 2021 | reconCNV: interactive visualization of copy number data from high-throughput sequencing · Bioinform. 2021 |
Bioinformatics and computational biology › genomics
high-throughput sequencing |
0.1 | 1 | 2021 | reconCNV: interactive visualization of copy number data from high-throughput sequencing · Bioinform. 2021 |
Methods — techniques the papers use, named apart from their topics
web-based visualization · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | reconCNV: interactive visualization of copy number data from high-throughput sequencingabstractSUMMARY: Copy number variation (CNV) is an important category of unbalanced structural rearrangement. While methods for detecting CNV in high-throughput targeted sequencing have become increasingly sophisticated, dedicated tools for interactive and dynamic visualization of CNV from these data are still lacking. We describe reconCNV, a tool that produces an interactive and annotated web-based dashboard for viewing and summarizing CNVs detected in next-generation sequencing (NGS) data. reconCNV is designed to work with delimited result files from most NGS CNV callers with minor adjustments to the configuration file. The reconCNV output is an HTML file that is viewable on any modern web browser, requires no backend server, and can be readily appended to existing analysis pipelines. In addition to a standard CNV track for visualizing relative fold change and absolute copy number, the tool includes an auxiliary variant allele fraction track for visualizing underlying allelic imbalance and loss of heterozygosity. A feature to mask assay-specific technical artifacts and a direct HTML link out to the UCSC Genome Browser are also included to augment the reviewer experience. By providing a light-weight plugin for interactive visualization to existing NGS CNV pipelines, reconCNV can facilitate efficient NGS CNV visualization and interpretation in both research and clinical settings. AVAILABILITY AND IMPLEMENTATION: The source code and documentation including a tutorial can be accessed at https://github.com/rghu/reconCNV as well as a Docker image at https://hub.docker.com/repository/docker/raghuc1990/reconcnv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Raghu Chandramohan, Nipun Kakkar, Angshumoy Roy, D. Williams Parsons |
Bioinform. | 4 |