Pages that link to "Item:Q5128768"
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The following pages link to Large scale maximum average power multiple inference on time‐course count data with application to RNA‐seq analysis (Q5128768):
Displaying 6 items.
- 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)
- A simulation framework for correlated count data of features subsets in high-throughput sequencing or proteomics experiments (Q521444) (← links)
- Detecting rare and faint signals via thresholding maximum likelihood estimators (Q1750291) (← links)
- A semiparametric latent factor model for large scale temporal data with heteroscedasticity (Q2237806) (← links)
- An optimal test with maximum average power while controlling FDR with application to RNA-seq data (Q2861943) (← links)