To detect differentially expressed genes under two conditions, statistical methods such as Poisson distributions are often used. However, to accurately detect differential expression of gene with low expression levels, more powerful statistical methods are desirable. In statistical literature, several methods have been proposed to compare two Poisson means (rates).

Through simulation study and real data analysis, the authors find that the Wald test with the data being log transformed is more powerful than other methods, including the likelihood ratio test, the variance stabilizing transformation test, the conditional exact test and the Fisher exact test.

When the count data in RNA-seq can be reasonably modelled as Poisson distribution, the Wald-Log test is more powerful and should be used to detect the differentially expressed genes.

  • Chen et al. (2011) Statistical methods on detecting differentially expressed genes for RNA-seq data. BMC Systems Biology 5(Suppl 3), S1. [article]

Incoming search terms:

  • why rna-seq is poisson distribution
  • waldlog
  • rnaseq poisson
  • david wald illumina
  • poisson RNA-seq
  • wald test differential expression
  • poisson distribution sequencing rna
  • most powerful statistical tools
  • testmost metod
  • statistical methods for rna seq data analysis

Comments

Leave a Reply




  • Social Networking Pages

    Linkedin Group

  • Follow Me on Pinterest
  • RSS SEQanswers – RNA Sequencing

    • standard of clean data May 21, 2013
      Hi all I recently got my prokaryotes RNA-seq data report back. the standard filter steps of the raw data set by our local sequencing center is as... […]
      Pengfei Liu
    • Problem with cummeRbund diffData() May 20, 2013
      Hi all, I'm running Tophat/cufflinks/cuffdiff for differential gene expression and analysis with cummeRbund (v 2.0.0). I'm having an issue with... […]
      Enrique Zudaire
    • How to increase rowsize in heatmap? May 16, 2013
      Hi, I am a complete newbie to all things cummeRbund and am currently fighting with generating readable heatmaps. When I use ... […]
      Mags
    • novoalign mapping May 15, 2013
      Hi, I want to use novoalign to map reads - allowing up to 15 mismatches for 100 bp paired-end reads I am new to novoalign(went through the... […]
      abh
    • Design of expt across multiple lanes May 15, 2013
      Hi, I am performing an RNA-seq experiment to look at differential expression. The design is as follows: 2 populations x 3 biological... […]
      jbono
    • RNA kinds expected in RNA-seq results May 15, 2013
      Hi, We use RNA isolation and library preparation protocols which capture polyadenylated RNA. My question is what kinds of RNA can we expect to... […]
      Kocur
  • RSS Biostar – RNA-Seq

    • How do TopHat options -g , --supress-hits, and Bowtie options interplay?
      Hi, I am currently using TopHat2 to map RNA-seq runs. I think there have been some changes pertaining the -g option. Does anyone know how it works now? I used to think that setting -g would look for n alignments for a given read, report them [if top-scoring] and discard those reads that had more than g [top scoring] alignments. Now, the description sounds mo […]
    • What happened to -k in TopHat for multiple-mapping reads?
      Selecting -g n in tophat does not discard reads mapping more than n, but instead only reports n alignments for those out all all their TOP scoring alignments. I think there used to be an option -k that would allow one to discard reads that topped x alignments -- whatever happened to that? I only see -g in the tophat 2 manual, no reporting options like before […]
    • Does tophat use the library-type information for mapping, or just for the XS flag?
      When I specify library-type to TopHat, i.e., first-strand, second-strand, unstranded, TopHat appends a value + or - to the XS:A tag, which is useful for subsequent analyses, such as annotation. However, does this information influence the "mappability" of reads, or is this unaffected? My guess is that the information will be considered for mapping […]
    • Purpose of Y-shaped adapters in Illumina Sequencing?
      Hi all, Y adapters different sequences to be annealed to the 5' and 3' ends of each molecule in a library. The arms of the Y are unique, and the middle part, connected to the DNA fragment, is complementary. What are the advantages of this? My take of this over having fully-complementary adapters (ADAPTER1 - - - - - ADAPTER1) is that: -Upon primer a […]
    • Cell Type composition in a tissue based on gene marker expression
      I am not sure if the following would even make sense.... Tissues are composed of composite cell types, and often there are studies such as microarray/NGS where we perform a collective sampling of cells from these tissues. Information about the composition (say percentage of cell type) is not taken into consideration. In some case (such as brain/cancer), ther […]
    • Which SNP caller / method to use after aligning RNA-seq with TopHat
      Which SNP caller / method can / should I use after aligning RNA-seq data with TopHat? For genomic data I use GATK, but supposedly it is not just as easy as running GATK on the TopHat RNA-seq data. The team from Broad has no information / documentation on how to use GATK for RNA-seq data. I don't have any variants yet from DNA re-sequencing. […]