Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • tejajo
    Junior Member
    • Feb 2011
    • 2

    Normalization: merging Illumina GA and HiSeq RNA-seq datasets for DE analysis

    Hi,
    I have two sets of samples sequenced using Illumina GA(II) and Illumina HiSeq. I would like to merge above two datasets so that I have more power to my differential expression analysis between two biological groups.

    I am wondering whether the technical differences between two technologies (as shown in "Evaluation of genomic high-throughput sequencing data generated on Illumina HiSeq and Genome Analyzer systems") can be minimized or made comparable by a normal MDS scaling following a normalization by library sizes.

    What are you opinions about that ?

    Thanks in advance.
  • Simon Anders
    Senior Member
    • Feb 2010
    • 995

    #2
    Not sure how you could get normalization factors from MDS.

    The better idea might be to fit an additional covariate. In the DESeq vignette, for example, we combine data from single-end and paired-end libraries. As we have both library types among both the control and the treatment samples, we can use a two-way ANOVA. You can follow exactly the same scheme as in the vignette, just by putting your two sequencing platforms instead of the two library types.

    Comment

    Latest Articles

    Collapse

    • SEQadmin2
      Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
      by SEQadmin2



      Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
      ...
      07-09-2026, 11:10 AM
    • SEQadmin2
      Cancer Drug Resistance: The Lingering Barrier to Rising Survival
      by SEQadmin2



      Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

      There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
      07-08-2026, 05:17 AM
    • GATTACAT
      Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
      by GATTACAT
      Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
      07-01-2026, 11:43 AM

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by SEQadmin2, 07-13-2026, 10:26 AM
    0 responses
    20 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-09-2026, 10:04 AM
    0 responses
    30 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-08-2026, 10:08 AM
    0 responses
    17 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-07-2026, 11:05 AM
    0 responses
    34 views
    0 reactions
    Last Post SEQadmin2  
    Working...