W. Johnson

Molecular Biology · Biostatistics · 2006–2020

A researcher in the Science corpus: 4 papers; trusts 6 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

Whom W. Johnson trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Mark D. Robinson
  2. Jeffrey T. Leek
  3. Zhijin Wu
  4. Rafael A. Irizarry
  5. Davis J. McCarthy

Who trusts W. Johnson overall

  1. Romain Lopez
  2. Jean-Philippe Fortin
  3. Christoph Bock
  4. Jianguo Xia
  5. Malte D. Luecken
  6. Charlotte Soneson
  7. Jeffrey C. Regier
  8. Sonja Hänzelmann
  9. Yong Zhang
  10. Jian Zhou

Papers from W. Johnson's perspective

Ordered by how strongly the researchers W. Johnson trusts endorse each paper. Same corpus, a different order for every researcher.

  1. A scaling normalization method for differential expression analysis of RNA-seq data (Genome Biology)
  2. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data (Bioinform.)
  3. Normalization of RNA-seq data using factor analysis of control genes or samples (Nature Biotechnology)
  4. voom: precision weights unlock linear model analysis tools for RNA-seq read counts (Genome Biology)
  5. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation (Nucleic Acids Research)
  6. Multiple-laboratory comparison of microarray platforms (Nature Methods)
  7. svaseq: removing batch effects and other unwanted noise from sequencing data (bioRxiv)
  8. Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression. (Proceedings of the National Academy of Sciences of the United States of America)
  9. Tackling the widespread and critical impact of batch effects in high-throughput data
  10. A Model-Based Background Adjustment for Oligonucleotide Expression Arrays

Their papers