Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • drea11
    Junior Member
    • Aug 2014
    • 9

    WGS batch effects

    Hi All,

    I'm relatively new to whole genome sequencing, and have a background in 16S based typing of bacteria using NGS. I am collecting data on a set of closely related organism, using illumina, identifying SNPs, and clustering them into a phylogenetic tree based on the differences between strains. I am wondering whether I need to worry about a 'batch effect' in these samples (either the extraction batch, or sequencing run or library prep or other). If so, it's not really feasible for us to sequence each sample multiple times, what might be the best way to go about first of all, identifying that batch effects may be present, and second, accounting for these in the analysis?

    Thanks!
  • lorendarith

    #2
    Hi, I would generally say that WGS is insensitive to these issues.

    I'm also doing metagenomics and 16S, so I can see where you're coming from... However, you should not see any differences if you resequence a library on the same machine or prepare another one from the same DNA pool, or extract DNA from the same or an identical sample. Eventual differences could come from source DNA degradation over time, changing the polymerases in the PCR (for GC-low and -high regions), sequencing chemistry upgrade and so on... which seems kinda obvious, no? As long as you keep all steps the same, there should not be any differences. Some days the sequencer can have a bad day so you might just get less and cappier data. If something is really wrong with your adapter ligation and subsequent PCR enrichment you can end up with more primer dimers and chimeric sequences, but the biologically relevant and correct sequences should perform equally well as before.

    What you can see is an adapter effect, depending on what kits you use and how experienced you are with plates. Especially if you are using custom designed adapters, there might be some combinations which are less balanced than others, so you'll just end up with a more obvious difference in the number of reads for each particular adapter sequence.

    Just, my experience til now.

    Comment

    Latest Articles

    Collapse

    • 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
    • SEQadmin2
      Nine Things a Sample Prep Scientist Thinks About Before Sequencing
      by SEQadmin2


      I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.

      Here are nine questions we think about, in roughly the order they matter, before...
      06-18-2026, 07:11 AM

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by SEQadmin2, 07-02-2026, 11:08 AM
    0 responses
    18 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 06-30-2026, 05:37 AM
    0 responses
    19 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 06-26-2026, 11:10 AM
    0 responses
    21 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 06-17-2026, 06:09 AM
    0 responses
    54 views
    0 reactions
    Last Post SEQadmin2  
    Working...