Christina Kendziorski

发表

EBSeq-HMM: a Bayesian approach for identifying gene-expression changes in ordered RNA-seq experiments

Yuan Li, Colin N. Dewey, Ning Leng, 2015, Bioinform..

Enhancing biological signals and detection rates in single-cell RNA-seq experiments with cDNA library equalization

James A. Thomson, Christina Kendziorski, Rhonda Bacher, 2020, bioRxiv.

A Compositional Model to Assess Expression Changes from Single-Cell Rna-Seq Data

Christina Kendziorski, By Xiuyu Ma, Keegan Korthauer, 2019, bioRxiv.

Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis

Bret Duffin, James A. Thomson, Christina Kendziorski, 2020, PloS one.

EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments

Ning Leng, James A. Thomson, Ron M. Stewart, 2013, Bioinform..

SCnorm: A quantile-regression based approach for robust normalization of single-cell RNA-seq data

Ning Leng, James A. Thomson, Christina Kendziorski, 2016, bioRxiv.

Parametric Empirical Bayes Methods for Microarrays

Christina Kendziorski, Michael A. Newton, M. Newton, 2003 .

OEFinder: A user interface to identify and visualize ordering effects in single-cell RNA-seq data

James A. Thomson, Christina Kendziorski, Li-Fang Chu, 2015 .

EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments

Ning Leng, James A. Thomson, Ron M. Stewart, 2013, Bioinform..

Trendy: segmented regression analysis of expression dynamics in high-throughput ordered profiling experiments

Ning Leng, James A. Thomson, Christina Kendziorski, 2018, BMC Bioinformatics.

MADGiC: a model-based approach for identifying driver genes in cancer

Christina Kendziorski, Keegan D. Korthauer, C. Kendziorski, 2015, Bioinform..

Statistical Applications in Genetics and Molecular Biology

Christina Kendziorski, Michael A. Newton, M. Newton, 2011 .

Trendy: Segmented regression analysis of expression dynamics for high-throughput ordered profiling experiments

James A. Thomson, Christina Kendziorski, Li-Fang Chu, 2017 .

An Empirical Bayesian Approach for Identifying Differential Coexpression in High‐Throughput Experiments

Christina Kendziorski, John A Dawson, C. Kendziorski, 2012, Biometrics.

Automated minute scale RNA-seq of pluripotent stem cell differentiation reveals early divergence of human and mouse gene expression kinetics

Brian E. McIntosh, Christina Kendziorski, Cara Argus, 2019, PLoS Comput. Biol..

Statistical methods for gene set co-expression analysis

Christina Kendziorski, YounJeong Choi, C. Kendziorski, 2009, Bioinform..

Normalization by distributional resampling of high throughput single-cell RNA-sequencing data

Christina Kendziorski, Rhonda Bacher, Zijian Ni, 2020, bioRxiv.

A Model-Based Analysis to Infer the Functional Content of a Gene List

Michael A Newton, Christina Kendziorski, Qiuling He, 2012, Statistical applications in genetics and molecular biology.

CHARTS: a web application for characterizing and comparing tumor subpopulations in publicly available single-cell RNA-seq data sets

Christina Kendziorski, Ron Stewart, Matthew N. Bernstein, 2020, BMC Bioinformatics.

Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis

Bret Duffin, James A. Thomson, Christina Kendziorski, 2019, PloS one.

EBSeq: improving mixing computations for multi-group differential expression analysis

Christina Kendziorski, Michael A. Newton, Xiuyu Ma, 2020, bioRxiv.

On Differential Variability of Expression Ratios: Improving Statistical Inference about Gene Expression Changes from Microarray Data

Christina Kendziorski, Frederick R. Blattner, M. A. Newton, 2001, J. Comput. Biol..

CB2 distinguishes cells from background barcodes in 10x Genomics data

Shuyang Chen, Christina Kendziorski, Zijian Ni, 2019, bioRxiv.

OEFinder: a user interface to identify and visualize ordering effects in single-cell RNA-seq data

Ning Leng, James A. Thomson, Ron M. Stewart, 2016, Bioinform..

R/EBcoexpress: an empirical Bayesian framework for discovering differential co-expression

Christina Kendziorski, John A. Dawson, Shuyun Ye, 2012, Bioinform..

A compositional model to assess expression changes from single-cell RNA-seq data

Christina Kendziorski, Michael A. Newton, Keegan Korthauer, 2021, The Annals of Applied Statistics.

CHARTS: a web application for characterizing and comparing tumor subpopulations in publicly available single-cell RNA-seq data sets

Ron M. Stewart, Christina Kendziorski, Matthew N. Bernstein, 2021, BMC Bioinform..

scDD: A statistical approach for identifying differential distributions in single-cell RNA-seq experiments

James A. Thomson, Christina Kendziorski, Li-Fang Chu, 2016 .

A Statistical Framework for Expression Quantitative Trait Loci Mapping

Christina Kendziorski, C. Kendziorski, Meng Chen, 2007, Genetics.

Combined Expression Trait Correlations and Expression Quantitative Trait Locus Mapping

Christina Kendziorski, Robert W. Williams, B. Yandell, 2006, PLoS genetics.

SCPattern: A statistical approach to identify and classify expression changes in single cell RNA-seq experiments with ordered conditions

Ning Leng, James A. Thomson, Christina Kendziorski, 2016, bioRxiv.

Identification and Correction of Sample Mix-Ups in Expression Genetic Data: A Case Study

Karl W Broman, Christina Kendziorski, Śaunak Sen, 2014, G3: Genes, Genomes, Genetics.

The Dissection of Expression Quantitative Trait Locus Hotspots

Karl W Broman, Christina Kendziorski, Jianan Tian, 2015, Genetics.

Cycle Regulation in Islets with Diabetes Susceptibility a Gene Expression Network Model of Type 2 Diabetes Links Cell P

Eric E Schadt, Ping Wang, Christina Kendziorski, 2008 .

Hidden Markov Models for Microarray Time Course Data in Multiple Biological Conditions

Christina Kendziorski, Ming Yuan, C. Kendziorski, 2006 .

Exenatide blocks JAK1-STAT1 in pancreatic beta cells.

Christina Kendziorski, Matthew Hanson, Ping Wang, 2007, Metabolism: clinical and experimental.

A review of statistical methods for expression quantitative trait loci mapping

Ping Wang, Christina Kendziorski, C. Kendziorski, 2006, Mammalian Genome.

EBSeq: An R package for di(cid:27)erential expression analysis using RNA-seq data

Ning Leng, Christina Kendziorski, Ning Leng, 2013 .

Pathway index models for construction of patient‐specific risk profiles

Christina Kendziorski, Kevin H Eng, Sijian Wang, 2013, Statistics in medicine.

Oscope identifies oscillatory genes in unsynchronized single cell RNA-seq experiments

Ning Leng, James A. Thomson, Ron M. Stewart, 2015, Nature Methods.

An efficient method for identifying statistical interactors in gene association networks.

Christina Kendziorski, C. Kendziorski, A. Andrei, 2009, Biostatistics.

Genetic Networks of Liver Metabolism Revealed by Integration of Metabolic and Transcriptional Profiling

Elias Chaibub Neto, Ping Wang, Christina Kendziorski, 2008, PLoS genetics.

The Collaborative Cross, a community resource for the genetic analysis of complex traits

Nengjun Yi, Fei Zou, Karl W Broman, 2004, Nature Genetics.

Discovery of structural alterations in solid tumor oligodendroglioma by single molecule analysis

Deepayan Sarkar, Michael A Newton, Christina Kendziorski, 2013, BMC Genomics.

Single-cell RNA sequencing reveals intrinsic and extrinsic regulatory heterogeneity in yeast responding to stress

Megan N. McClean, Christina Kendziorski, Stephen R Quake, 2017, PLoS biology.