Author: Stephanie C Hicks

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Preprints

When to use Quantile Normalization?

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Missing Data and Technical Variability in Single-Cell RNA- Sequencing Experiments

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Feature Selection and Dimension Reduction for Single Cell RNA-Seq based on a Multinomial Model

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Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex

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A practical guide to methods controlling false discoveries in computational biology

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Orchestrating Single-Cell Analysis with Bioconductor

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A Systematic Evaluation of Single-cell RNA-sequencing Imputation Methods

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  • In genomics: 495
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Smooth Quantile Normalization

• Downloaded 1,689 times
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  • In genomics: 1,015
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Varying-Censoring Aware Matrix Factorization for Single Cell RNA-Sequencing

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Analysis And Correction Of Compositional Bias In Sparse Sequencing Count Data

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Co-expression analysis is biased by a mean-correlation relationship

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Single-nucleus transcriptome analysis reveals cell type-specific molecular signatures across reward circuitry in the human brain

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Technology-independent estimation of cell type composition using differentially methylated regions

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mbkmeans: fast clustering for single cell data using mini-batch k-means

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SpatialExperiment: infrastructure for spatially resolved transcriptomics data in R using Bioconductor

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Genetic demultiplexing of pooled single-cell RNA-sequencing samples in cancer facilitates effective experimental design

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