Author

Shannon Ellis

Johns Hopkins UniversityORCID 0000-0002-9231-0481Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genomics· 2 Bioinformatics· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 4 Organism:human· 4 Assay:bulk RNA-seq· 3 Research Focus:database / resource· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:gene regulatory network inference· 2 Approach:benchmark study· 1

Frequent Co-Authors

Andrew E. JaffeiD· 2 shared Jeffrey T. LeekiD· 2 shared Leonardo Collado‐TorresiD· 2 shared Andrew B. West· 1 shared Andrew P. FeinbergiD· 1 shared Ashkaun Razmara· 1 shared Brooke K. SheppardiD· 1 shared Christine Ladd‐AcostaiD· 1 shared

Activity by Year

2016-2019 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 16 mutual co-author links

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2 shared papersGenomics

Andrew E. JaffeORCID

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4 papers

Recent·Most cited

recount-brain: a curated repository of human brain RNA-seq datasets metadata

Ashkaun Razmara, Shannon Ellis, Dustin Sokolowski, Sean R. Davis, Michael D. Wilson, Jeffrey T. Leek, Andrew E. Jaffe, Leonardo Collado‐Torres

The paper curates a database of human brain RNA-seq metadata to improve reproducibility and analysis of gene expression data.

bioRxiv · Apr 24, 2019 · PreprintGenomics

Improving the value of public RNA-seq expression data by phenotype prediction

Shannon Ellis, Leonardo Collado‐Torres, Andrew E. Jaffe, Jeffrey T. Leek

The paper predicts missing phenotype annotations for public RNA-seq data using well-annotated datasets, enabling better analysis of large-scale genomic data.

Nucleic Acids Research · Feb 15, 2018Peer-reviewedBioinformatics

Cross-tissue integration of genetic and epigenetic data offers insight into autism spectrum disorder

Shan V. Andrews, Shannon Ellis, Kelly M. Bakulski, Brooke K. Sheppard, Lisa Croen, Irva Hertz‐Picciotto, Craig J. Newschaffer, Andrew P. Feinberg, Dan E. Arking, Christine Ladd‐Acosta, M. Daniele Fallin

The paper integrates genetic and epigenetic data to identify ASD-associated SNPs enriched in tissue-specific meQTLs and reveals immune-related pathways and psychiatric condition links.

Nature Communications · Oct 12, 2017Peer-reviewedGenomics

Transcriptome Analysis of Cortical Tissue Reveals Shared Sets of Down-Regulated Genes in Autism and Schizophrenia

Shannon E. Ellis, Rebecca Panitch, Andrew B. West, Dan E. Arking

The paper analyzes transcriptomic data from cortical tissues of individuals with autism, schizophrenia, and bipolar disorder to identify shared gene expression patterns and potential common mechanisms.

bioRxiv · Feb 18, 2016 · PreprintGenetics