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Article
Open AccessscFSNN: a feature selection method based on neural network for single-cell RNA-seq data
While single-cell RNA sequencing (scRNA-seq) allows researchers to analyze gene expression in individual cells, its unique characteristics like over-dispersion, zero-inflation, high gene-gene correlation, and ...
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Article
Open AccessA statistical normalization method and differential expression analysis for RNA-seq data between different species
High-throughput techniques bring novel tools and also statistical challenges to genomic research. Identifying genes with differential expression between different species is an effective way to discover evolut...
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Article
Open AccessStability of methods for differential expression analysis of RNA-seq data
As RNA-seq becomes the assay of choice for measuring gene expression levels, differential expression analysis has received extensive attentions of researchers. To date, for the evaluation of DE methods, most a...
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Article
Open AccessHigh-resolution RNA alleloty** along the inactive X chromosome: evidence of RNA polymerase III in regulating chromatin configuration
We carried out padlock capture, a high-resolution RNA alleloty** method, to study X chromosome inactivation (XCI). We examined the gene reactivation pattern along the inactive X (**), after **st (X-inactive spe...
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Article
Open AccessLFCseq: a nonparametric approach for differential expression analysis of RNA-seq data
With the advances in high-throughput DNA sequencing technologies, RNA-seq has rapidly emerged as a powerful tool for the quantitative analysis of gene expression and transcript variant discovery. In comparativ...