Statistical Analysis

PathwaySeq – Pathway analysis for RNA-Seq data

rna-seq

A variety of pathway/gene-set approaches have been proposed to provide evidence of higher-level biological phenomena in the association of expression with experimental condition or clinical outcome. Among these approaches, it has been repeatedly shown that resampling methods are far preferable ...

Read More »

Understanding the differences between microarray and RNA-Seq technologies for measuring gene expression is necessary for informed design of experiments and choice of data analysis methods

rna-seq

Previous comparisons between microarrays and RNA-Seq have come to sometimes contradictory conclusions, which researchers from Princeton University suggest result from a lack of attention to the intensity-dependent nature of variation generated by the technologies. To examine this trend, they carried ...

Read More »

The impact of quality filter for RNA-Seq

rna-seq

With the emergence of large-scale sequencing platforms since 2005, there has been a great revolution regarding methods for decoding DNA sequences, which have also affected quantitative and qualitative gene expression analyses through the RNA-Sequencing technique. However, issues related to the ...

Read More »

Reduction of Gene Expression Variability from Single Cells to Populations follows Simple Statistical Laws

rna-seq

Recent studies on single cells and population transcriptomics have revealed striking differences in global gene expression distributions. Single cells display highly variable expressions between cells, while cell populations present deterministic global patterns. The mechanisms governing the reduction of transcriptome-wide variability ...

Read More »