Demo Data from SIGIR 2026 / reviewers in the wild / expert
Joseph K. Pickrell
dblp:88/7593
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 1 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
3 papers |
Bioinformatics and computational biology · 100% |
Topics — the 8 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
population genetics |
0.2 | 1 | 2016 | Approximately independent linkage disequilibrium blocks in human populations · Bioinform. 2016 |
Bioinformatics and computational biology
genome annotation |
0.1 | 1 | 2011 | False positive peaks in ChIP-seq and other sequencing-based functional assays caused by unannotated high copy number regions · Bioinform. 2011 |
Bioinformatics and computational biology › sequence analysis › sequence assembly
genome assembly |
0.1 | 1 | 2011 | False positive peaks in ChIP-seq and other sequencing-based functional assays caused by unannotated high copy number regions · Bioinform. 2011 |
Bioinformatics and computational biology › epigenomics › ChIP-seq analysis
peak calling |
0.1 | 1 | 2011 | False positive peaks in ChIP-seq and other sequencing-based functional assays caused by unannotated high copy number regions · Bioinform. 2011 |
Bioinformatics and computational biology › gene expression analysis › gene expression quantification
allele-specific expression |
0.1 | 1 | 2009 | Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data · Bioinform. 2009 |
Bioinformatics and computational biology › sequence analysis
read mapping |
0.1 | 1 | 2009 | Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data · Bioinform. 2009 |
Bioinformatics and computational biology › transcriptomics › transcriptome sequencing
RNA sequencing analysis |
0.1 | 1 | 2009 | Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data · Bioinform. 2009 |
Bioinformatics and computational biology › genomics
genome-wide association study |
0.1 | 1 | 2016 | Approximately independent linkage disequilibrium blocks in human populations · Bioinform. 2016 |
Methods — techniques the papers use, named apart from their topics
statistical block detection · 0.2sequencing depth analysis · 0.1masking · 0.1simulation · 0.1read mapping · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Approximately independent linkage disequilibrium blocks in human populationsabstractUNLABELLED: We present a method to identify approximately independent blocks of linkage disequilibrium in the human genome. These blocks enable automated analysis of multiple genome-wide association studies. AVAILABILITY AND IMPLEMENTATION: code: http://bitbucket.org/nygcresearch/ldetect; data: http://bitbucket.org/nygcresearch/ldetect-data. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Tomaz Berisa, Joseph K. Pickrell |
Bioinform. | 2 |
| 2011 | False positive peaks in ChIP-seq and other sequencing-based functional assays caused by unannotated high copy number regionsabstractAbstract Motivation: Sequencing-based assays such as ChIP-seq, DNase-seq and MNase-seq have become important tools for genome annotation. In these assays, short sequence reads enriched for loci of interest are mapped to a reference genome to determine their origin. Here, we consider whether false positive peak calls can be caused by particular type of error in the reference genome: multicopy sequences which have been incorrectly assembled and collapsed into a single copy. Results: Using sequencing data from the 1000 Genomes Project, we systematically scanned the human genome for regions of high sequencing depth. These regions are highly enriched for erroneously inferred transcription factor binding sites, positions of nucleosomes and regions of open chromatin. We suggest a simple masking procedure to remove these regions and reduce false positive calls. Availability: Files for masking out these regions are available at eqtl.uchicago.edu Contact: [email protected]; [email protected]; [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics online. Joseph K. Pickrell, Daniel J. Gaffney, Yoav Gilad, Jonathan K. Pritchard |
Bioinform. | 1 |
| 2009 | Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing dataabstractMOTIVATION: Next-generation sequencing has become an important tool for genome-wide quantification of DNA and RNA. However, a major technical hurdle lies in the need to map short sequence reads back to their correct locations in a reference genome. Here, we investigate the impact of SNP variation on the reliability of read-mapping in the context of detecting allele-specific expression (ASE). RESULTS: We generated 16 million 35 bp reads from mRNA of each of two HapMap Yoruba individuals. When we mapped these reads to the human genome we found that, at heterozygous SNPs, there was a significant bias toward higher mapping rates of the allele in the reference sequence, compared with the alternative allele. Masking known SNP positions in the genome sequence eliminated the reference bias but, surprisingly, did not lead to more reliable results overall. We find that even after masking, approximately 5-10% of SNPs still have an inherent bias toward more effective mapping of one allele. Filtering out inherently biased SNPs removes 40% of the top signals of ASE. The remaining SNPs showing ASE are enriched in genes previously known to harbor cis-regulatory variation or known to show uniparental imprinting. Our results have implications for a variety of applications involving detection of alternate alleles from short-read sequence data. AVAILABILITY: Scripts, written in Perl and R, for simulating short reads, masking SNP variation in a reference genome and analyzing the simulation output are available upon request from JFD. Raw short read data were deposited in GEO (http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE18156. CONTACT: [email protected]; [email protected]; [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Jacob F. Degner, John C. Marioni, Athma A. Pai, Joseph K. Pickrell, Everlyne Nkadori, Yoav Gilad, Jonathan K. Pritchard |
Bioinform. | 4 |