Demo Data from VLDB 2026 / reviewers in the wild / expert
Barbara Mascialino
dblp:99/1759
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2008
0000-0003-4154-4728ORCID · reported
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › gene expression analysis
differential expression analysis |
0.1 | 1 | 2008 | Unequal group variances in microarray data analyses · Bioinform. 2008 |
Bioinformatics and computational biology › gene expression analysis
microarray data analysis |
0.1 | 1 | 2008 | Unequal group variances in microarray data analyses · Bioinform. 2008 |
Methods — techniques the papers use, named apart from their topics
moderated welch test · 0.1false discovery rate estimation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | Unequal group variances in microarray data analysesabstractMOTIVATION: In searching for differentially expressed (DE) genes in microarray data, we often observe a fraction of the genes to have unequal variability between groups. This is not an issue in large samples, where a valid test exists that uses individual variances separately. The problem arises in the small-sample setting, where the approximately valid Welch test lacks sensitivity, while the more sensitive moderated t-test assumes equal variance. METHODS: We introduce a moderated Welch test (MWT) that allows unequal variance between groups. It is based on (i) weighting of pooled and unpooled standard errors and (ii) improved estimation of the gene-level variance that exploits the information from across the genes. RESULTS: When a non-trivial proportion of genes has unequal variability, false discovery rate (FDR) estimates based on the standard t and moderated t-tests are often too optimistic, while the standard Welch test has low sensitivity. The MWT is shown to (i) perform better than the standard t, the standard Welch and the moderated t-tests when the variances are unequal between groups and (ii) perform similarly to the moderated t, and better than the standard t and Welch tests when the group variances are equal. These results mean that MWT is more reliable than other existing tests over wider range of data conditions. AVAILABILITY: R package to perform MWT is available at http://www.meb.ki.se/~yudpaw Meaza Demissie, Barbara Mascialino, Stefano Calza, Yudi Pawitan |
Bioinform. | 2 |