Go Back   SEQanswers > Applications Forums > RNA Sequencing

Similar Threads
Thread Thread Starter Forum Replies Last Post
Normalize small RNA data with spike-in controls? jazz Bioinformatics 4 04-28-2017 04:19 AM
how to extract miRNA spike-in controls from smallRNAseq data heso Bioinformatics 1 09-29-2014 05:48 AM
Please explain the concept of "spike in controls" for NGS analysis medalofhonour General 3 07-05-2013 09:40 AM
ERCC spike in controls for illumina? onconaut Illumina/Solexa 5 11-26-2012 07:47 AM

Thread Tools
Old 12-04-2015, 07:04 PM   #1
Junior Member
Location: Los Angeles

Join Date: Dec 2015
Posts: 1
Default Bacterial RNA-seq Spike-in Controls


I recently learned of RNA spike-in controls and am interested in incorporating them into my sequencing runs. I primarily use RNA-seq to measure gene expression levels in E. coli.

My question is, are their RNA spike-in controls similar to those by the ERCC available for bacterial studies? If not, could you provide me with a suggestion on how to control for batch effects between sequencing runs?

Thank you
gurtecho is offline   Reply With Quote
Old 12-04-2015, 08:26 PM   #2
Senior Member
Location: Montreal

Join Date: May 2013
Posts: 367

I'm very skeptical on the value of ERCC spike-ins.
I don't see the value of a control that cannot be fully trusted.

More than one study has questioned the validity of ERCC spike-ins.

My own, albeit limited, experience with spike-ins confirms the results of these studies.

What is the point of the extra cost of adding the spike-ins, to end up with unreliable data requiring extra analysis?

It's a nice concept, but I don't think the real-world results support the wide-spread use of the ERCC spike-ins.

NGS is not like microarrays either. The batch effect is not as huge a problem between sequencing runs as it is for microarrays prepared at different times. Any batch effect, if present, would be more likely to result from manipulations prior to the sequencing itself.


One way of controlling for any potential batch effect, albeit perhaps not cost-effective, would be to distribute the replicates across the sequencing runs. If you could verify that the replicates within the same sequencing run had the same correlation as replicates across sequencing runs, you could confidently discount any batch effect. Even if you did pick up a batch effect, in theory, it would be possible to correct it. I've used Combat, with some success in the past, to reduce the batch effect in microarray samples with replicates distributed thus between the different preparation times. Again, this may be too expensive for NGS, and less necessary, given the reduced batch effect.

Last edited by blancha; 12-04-2015 at 08:35 PM.
blancha is offline   Reply With Quote
Old 02-21-2019, 05:23 AM   #3
Junior Member
Location: Israel

Join Date: Jan 2019
Posts: 4
Default I'm wondering if anything changed...

Anyone has an updated answer?
Adiro is offline   Reply With Quote

Thread Tools

Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off

All times are GMT -8. The time now is 03:17 AM.

Powered by vBulletin® Version 3.8.9
Copyright ©2000 - 2021, vBulletin Solutions, Inc.
Single Sign On provided by vBSSO