Andrew McDavid

Molecular Biology · 2011–2019

A researcher in the Science corpus: 4 papers; trusts 1 researcher and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 64 citations into it; #9,137 of 17,773 by trust here, #3,184 by citations
• Genetics — 56 citations into it

Whom Andrew McDavid trusts overall

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

1. Gordon K. Smyth
2. Thomas D. Schmittgen
3. Jeffrey T. Leek
4. Jo Vandesompele
5. K. Livak
6. Daniel Ramsköld
7. Yoav Benjamini
8. Mark D. Robinson
9. Bo Li
10. Diabetes-Ling Wu

Who trusts Andrew McDavid overall

1. Valentine Svensson
2. Allon Wagner
3. Wei Vivian Li
4. Laleh Haghverdi
5. Christopher S. McGinnis
6. Rahul Satija
7. Romain Lopez
8. Aviv Regev
9. Fabian J Theis
10. Karthik Shekhar

Papers from Andrew McDavid's perspective

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

1. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data (Bioinform.)
2. Controlling the false discovery rate: a practical and powerful approach to multiple testing
3. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome (BMC Bioinformatics)
4. Normalization of RNA-seq data using factor analysis of control genes or samples (Nature Biotechnology)
5. Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments (Statistical Applications in Genetics and Molecular Biology)
6. voom: precision weights unlock linear model analysis tools for RNA-seq read counts (Genome Biology)
7. Bioconductor: open software development for computational biology and bioinformatics (Genome Biology)
8. Accounting for technical noise in single-cell RNA-seq experiments (Nature Methods)
9. svaseq: removing batch effects and other unwanted noise from sequencing data (bioRxiv)
10. Single cell RNA Seq reveals dynamic paracrine control of cellular variation (Nature)

Their papers

• MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data (2015) — 2,717 citations
• Data exploration, quality control and testing in single-cell qPCR-based gene expression experiments (2012) — 376 citations
• Common variants in MS4A4/MS4A6E, CD2uAP, CD33, and EPHA1 are associated with late-onset Alzheimer’s disease (2011) — 1,887 citations
• Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing (2019) — 2,422 citations