Ayshwarya Subramanian

Molecular Biology · 2018–2021

A researcher in the Science corpus: 5 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ayshwarya Subramanian trusts overall

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

  1. Yoav Benjamini

Papers from Ayshwarya Subramanian's perspective

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

  1. Controlling the false discovery rate: a practical and powerful approach to multiple testing
  2. Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments (Statistical Applications in Genetics and Molecular Biology)
  3. voom: precision weights unlock linear model analysis tools for RNA-seq read counts (Genome Biology)
  4. Integrating diverse genomic data using gene sets (Genome Biology)
  5. limma powers differential expression analyses for RNA-sequencing and microarray studies
  6. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
  7. On the Adaptive Control of the False Discovery Rate in Multiple Testing With Independent Statistics
  8. MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data (Genome Biology)
  9. Diffusion pseudotime robustly reconstructs lineage branching
  10. Discovering the false discovery rate

Their papers