Author

Insha Ullah

Australian National UniversityORCID 0000-0002-9476-6837Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:GWAS summary statistics· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Anthony N. PettittiD· 1 shared Benoît LiquetiD· 1 shared Kerrie Lee MengerseniD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

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3 top collaborators · 3 mutual co-author links

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1 shared paperBioinformatics

Anthony N. PettittORCID

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1 paper

Recent·Most cited

Using a supervised principal components analysis for variable selection in high-dimensional datasets reduces false discovery rates

Insha Ullah, Kerrie Lee Mengersen, Anthony N. Pettitt, Benoît Liquet

This paper introduces a supervised principal components analysis method for variable selection in high-dimensional datasets, showing it reduces false discovery rates and improves statistical inference.

Statistics in Medicine · Jun 1, 2025Peer-reviewedBioinformatics