EDBT 2026 Demo / reviewers in the wild / expert
Joseph L. McClay
dblp:53/4629
· DBLP profile ↗
3ranked-venue papers
0as first author
1since 2021 · last 2026
0000-0002-3628-2447ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 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
2 papers |
Bioinformatics and computational biology · 100% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
functional genomics |
1.0 | 1 | 2026 | Beyond blacklists: a critical assessment of exclusion set generation strategies and alternative approaches · Bioinform. 2026 |
Bioinformatics and computational biology › sequence analysis › sequence assembly
genome assembly |
1.0 | 1 | 2026 | Beyond blacklists: a critical assessment of exclusion set generation strategies and alternative approaches · Bioinform. 2026 |
Bioinformatics and computational biology › sequence analysis
sequencing data processing |
1.0 | 1 | 2026 | Beyond blacklists: a critical assessment of exclusion set generation strategies and alternative approaches · Bioinform. 2026 |
Bioinformatics and computational biology › genomics
genome-wide association study |
0.1 | 1 | 2009 | Estimating the posterior probability that genome-wide association findings are true or false · Bioinform. 2009 |
Bioinformatics and computational biology
statistical genetics |
0.1 | 1 | 2009 | Estimating the posterior probability that genome-wide association findings are true or false · Bioinform. 2009 |
Mathematical optimization › statistical estimation
maximum likelihood estimation |
0.0 | 1 | 2009 | Estimating the posterior probability that genome-wide association findings are true or false · Bioinform. 2009 |
Methods — techniques the papers use, named apart from their topics
sponge sequences · 1.0read alignment · 1.0blacklist exclusion sets · 1.0mixture model · 0.2maximum likelihood estimation · 0.2local false discovery rate · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Beyond blacklists: a critical assessment of exclusion set generation strategies and alternative approachesabstractMOTIVATION: Short-read sequencing data can be affected by alignment artifacts in certain genomic regions. Removing reads overlapping these exclusion regions, previously known as Blacklists, help to potentially improve biological signal. Alternatively, "sponge" or decoy sequences have been proposed to reduce alignment artifacts. RESULTS: We examined the widely used Blacklist software and found that pre-generated exclusion sets were difficult to reproduce due to sensitivity to input data, aligner choice, and read length. We further explored the use of "sponge" sequences-unassembled genomic regions such as satellite DNA, ribosomal DNA, and mitochondrial DNA-as an alternative approach. We additionally investigated the effect of the T2T-CHM13 genome assembly on improving biological signals. Aligning reads to a genome that includes sponge sequences reduced signal correlation in ChIP-seq data comparably to Blacklist-derived exclusion sets while preserving biological signal. Sponge-based alignment also had minimal impact on RNA-seq gene counts, suggesting broader applicability beyond chromatin profiling. These results highlight the limitations of fixed exclusion sets, and recommend the use of the T2T-CHM13 assembly or, for the hg38 genome assembly, "sponge" sequences as an alignment-guided strategy for reducing artifacts and improving functional genomics analyses. Brydon P. G. Wall, Jonathan D. Ogata, My Nguyen, Amy L. Olex, Konstantinos V. Floros, Anthony C. Faber, Joseph L. McClay, J. Chuck Harrell, Mikhail G. Dozmorov |
Bioinform. | 7 |
| 2013 | Estimation of CpG coverage in whole methylome next-generation sequencing studiesabstractBACKGROUND: Methylation studies are a promising complement to genetic studies of DNA sequence. However, detailed prior biological knowledge is typically lacking, so methylome-wide association studies (MWAS) will be critical to detect disease relevant sites. A cost-effective approach involves the next-generation sequencing (NGS) of single-end libraries created from samples that are enriched for methylated DNA fragments. A limitation of single-end libraries is that the fragment size distribution is not observed. This hampers several aspects of the data analysis such as the calculation of enrichment measures that are based on the number of fragments covering the CpGs. RESULTS: We developed a non-parametric method that uses isolated CpGs to estimate sample-specific fragment size distributions from the empirical sequencing data. Through simulations we show that our method is highly accurate. While the traditional (extended) read count methods resulted in severely biased coverage estimates and introduces artificial inter-individual differences, through the use of the estimated fragment size distributions we could remove these biases almost entirely. Furthermore, we found correlations of 0.999 between coverage estimates obtained using fragment size distributions that were estimated with our method versus those that were "observed" in paired-end sequencing data. CONCLUSIONS: We propose a non-parametric method for estimating fragment size distributions that is highly precise and can improve the analysis of cost-effective MWAS studies that sequence single-end libraries created from samples that are enriched for methylated DNA fragments. Edwin J. C. G. van den Oord, József Bukszár, Gábor Rudolf, Srilaxmi Nerella, Joseph L. McClay, Lin Y. Xie, Karolina A. Åberg |
BMC Bioinform. | 5 |
| 2009 | Estimating the posterior probability that genome-wide association findings are true or falseabstractMOTIVATION: A limitation of current methods used to declare significance in genome-wide association studies (GWAS) is that they do not provide clear information about the probability that GWAS findings are true of false. This lack of information increases the chance of false discoveries and may result in real effects being missed. RESULTS: We propose a method to estimate the posterior probability that a marker has (no) effect given its test statistic value, also called the local false discovery rate (FDR), in the GWAS. A critical step involves the estimation the parameters of the distribution of the true alternative tests. For this, we derived and implemented the real maximum likelihood function, which turned out to provide us with significantly more accurate estimates than the widely used mixture model likelihood. Actual GWAS data are used to illustrate properties of the posterior probability estimates empirically. In addition to evaluating individual markers, a variety of applications are conceivable. For instance, posterior probability estimates can be used to control the FDR more precisely than Benjamini-Hochberg procedure. AVAILABILITY: The codes are freely downloadable from the web site http://www.people.vcu.edu/~jbukszar. József Bukszár, Joseph L. McClay, Edwin J. C. G. van den Oord |
Bioinform. | 2 |