Pages that link to "Item:Q100304"
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The following pages link to Detecting differential expression in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates (Q100304):
Displaying 28 items.
- QuasiSeq (Q23305) (← links)
- What if we ignore the random effects when analyzing RNA-seq data in a multifactor experiment (Q306675) (← links)
- A Markov random field-based approach for joint estimation of differentially expressed genes in mouse transcriptome data (Q306683) (← links)
- Shrinkage of dispersion parameters in the binomial family, with application to differential exon skipping (Q312910) (← links)
- A two-stage Poisson model for testing RNA-Seq data (Q458254) (← links)
- Estimation and testing of gene expression heterosis (Q489924) (← links)
- Controlling the false-discovery rate by procedures adapted to the length bias of RNA-seq (Q684055) (← links)
- A semi-parametric Bayesian approach for differential expression analysis of RNA-seq data (Q906075) (← links)
- Detecting differentially expressed genes with RNA-seq data using backward selection to account for the effects of relevant covariates (Q906078) (← links)
- Hierarchical modeling and differential expression analysis for RNA-seq experiments with inbred and hybrid genotypes (Q906080) (← links)
- Empirical Bayes analysis of RNA-seq data for detection of gene expression heterosis (Q906083) (← links)
- MSIQ: joint modeling of multiple RNA-seq samples for accurate isoform quantification (Q1647636) (← links)
- Modifying SAMseq to account for asymmetry in the distribution of effect sizes when identifying differentially expressed genes (Q1670284) (← links)
- A penalized likelihood approach for robust estimation of isoform expression (Q1747466) (← links)
- Detecting rare and faint signals via thresholding maximum likelihood estimators (Q1750291) (← links)
- Generate gene expression profile from high-throughput sequencing data (Q1946952) (← links)
- Zero-inflated quantile rank-score based test (ZIQRank) with application to scRNA-seq differential gene expression analysis (Q2078276) (← links)
- Sample size calculations for the differential expression analysis of RNA-seq data using a negative binomial regression model (Q2324965) (← links)
- No counts, no variance: allowing for loss of degrees of freedom when assessing biological variability from RNA-seq data (Q2406178) (← links)
- Modeling overdispersion heterogeneity in differential expression analysis using mixtures (Q2827191) (← links)
- Dynamic linear model for the identification of miRNAs in next-generation sequencing data (Q2893375) (← links)
- Removing technical variability in RNA-seq data using conditional quantile normalization (Q3303808) (← links)
- An Enhanced Quantile Approach for Assessing Differential Gene Expressions (Q3506489) (← links)
- Detection of differentially expressed genes in discrete single‐cell RNA sequencing data using a hurdle model with correlated random effects (Q5121015) (← links)
- Large scale maximum average power multiple inference on time‐course count data with application to RNA‐seq analysis (Q5128768) (← links)
- Simultaneous inference of gene isoform expression for RNA sequencing data (Q5142043) (← links)
- Transcriptomics: Quantifying Non-Uniform Read Distribution Using MapReduce (Q5384628) (← links)
- Empirical likelihood tests for nonparametric detection of differential expression from RNA-seq data (Q5962705) (← links)
