Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • What to do with genes with very low counts in a dataset

    Hi all,
    I have a dataset from a single cell RNASeq project and there are many genes with very few counts (1 or 2 in a few samples) in the data set. While this is important info (tells us that these genes are not expressed), how would one handle them for a differential expression analysis (I use DESeq2)? Should I delete them or keep them? For me this means the difference between having a dataset with either ~17000 genes or ~11,500 genes (if I exclude genes with an average count less than 3).
    Thanks for your thoughts on this!

  • #2
    DESeq2 will filter them out for you, you needn't do it manually.

    Comment


    • #3
      Devon's always got the right answer

      If you want to know more about filtering out genes with few counts, we have a section on this (independent filtering) in the "Theory" part of the DESeq2 vignette.

      A reference on independent filtering:

      Bourgon R, Gentleman R, Huber W.
      "Independent filtering increases detection power for high-throughput experiments."
      Proc Natl Acad Sci U S A. 2010 May 25;107(21):9546-51. doi: 10.1073/pnas.0914005107. Epub 2010 May 11.
      With high-dimensional data, variable-by-variable statistical testing is often used to select variables whose behavior differs across conditions. Such an approach requires adjustment for multiple testing, which can result in low statistical power. A two-stage approach that first filters variables by …

      Comment


      • #4
        Thanks for the quick replies, dpryan and Michael Love!

        Comment

        Latest Articles

        Collapse

        • seqadmin
          Choosing Between NGS and qPCR
          by seqadmin



          Next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR) are essential techniques for investigating the genome, transcriptome, and epigenome. In many cases, choosing the appropriate technique is straightforward, but in others, it can be more challenging to determine the most effective option. A simple distinction is that smaller, more focused projects are typically better suited for qPCR, while larger, more complex datasets benefit from NGS. However,...
          10-18-2024, 07:11 AM
        • seqadmin
          Non-Coding RNA Research and Technologies
          by seqadmin




          Non-coding RNAs (ncRNAs) do not code for proteins but play important roles in numerous cellular processes including gene silencing, developmental pathways, and more. There are numerous types including microRNA (miRNA), long ncRNA (lncRNA), circular RNA (circRNA), and more. In this article, we discuss innovative ncRNA research and explore recent technological advancements that improve the study of ncRNAs.

          Nobel Prize for MicroRNA Discovery
          This week,...
          10-07-2024, 08:07 AM

        ad_right_rmr

        Collapse

        News

        Collapse

        Topics Statistics Last Post
        Started by seqadmin, Yesterday, 06:09 AM
        0 responses
        10 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 10-30-2024, 05:31 AM
        0 responses
        12 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 10-24-2024, 06:58 AM
        0 responses
        21 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 10-23-2024, 08:43 AM
        0 responses
        52 views
        0 likes
        Last Post seqadmin  
        Working...
        X