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Selective inference for multiple pairs of clusters after k-means clustering
Y Yun, Y He - arxiv preprint arxiv:2405.16379, 2024 - arxiv.org
If the same data is used for both clustering and for testing a null hypothesis that is formulated
in terms of the estimated clusters, then the traditional hypothesis testing framework often fails …
in terms of the estimated clusters, then the traditional hypothesis testing framework often fails …
Running in circles: practical limitations for real-life application of data fission and data thinning in post-clustering differential analysis
Post-clustering inference in scRNA-seq analysis presents significant challenges in
controlling Type I error during Differential Expression Analysis. Data fission, a promising …
controlling Type I error during Differential Expression Analysis. Data fission, a promising …
False Discovery Rate Control via Data Splitting for Testing-after-Clustering
Testing for differences in features between clusters in various applications often leads to
inflated false positives when practitioners use the same dataset to identify clusters and then …
inflated false positives when practitioners use the same dataset to identify clusters and then …
Clustering et analyse différentielle de données d'expression génique
B Hivert - 2024 - theses.hal.science
Les analyses des données d'expression génique issues du séquençage de l'ARN (RNA-
seq) en masse (bulk RNA-seq) ou en cellule unique (scRNA-seq) sont devenues courantes …
seq) en masse (bulk RNA-seq) ou en cellule unique (scRNA-seq) sont devenues courantes …