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Integrating gene expression profiles across different platforms

Integrating gene expression profiles across different platforms

Determining differentially expressed genes (DEGs) between biological samples is the key to understand how genotype gives rise to phenotype. RNA-seq and microarray are two main technologies for profiling gene expression levels. However, considerable discrepancy has been found between DEGs detected ...

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Parallel single-cell sequencing

Parallel single-cell sequencing

from Nature Reviews Genetics by Linda Koch A new single-cell analysis method called scM&T-seq comprises the simultaneous genome-wide sequencing of the methylome and the transcriptome from one cell, enabling detailed analyses of how epigenetic heterogeneity relates to gene expression output ...

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Isoform-level gene expression patterns in single-cell RNA-sequencing data

Isoform-level gene expression patterns in single-cell RNA-sequencing data

RNA-sequencing of single-cells enables characterization of transcriptional heterogeneity in seemingly homogenous cell populations. In this study, reseachers from the Karolinska Institute propose and apply a novel method, ISOform-Patterns (ISOP), based on mixture modeling, to characterize the expression patterns of pairs ...

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Understanding changes in gene expression at the single-cell level

Understanding changes in gene expression at the single-cell level

Single-cell RNA sequencing (scRNA-seq) can be used to characterise differences in gene expression patterns between pre-specified populations of cells. Traditionally, differential expression tools are restricted to the study of changes in overall expression between cell populations. However, such analyses do ...

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