SEQanswers

Go Back   SEQanswers > General



Similar Threads
Thread Thread Starter Forum Replies Last Post
DEXSeq error in estimateDispersions: match.arg(start.method, c("log(y)", "mean")) fpadilla Bioinformatics 14 07-03-2013 02:11 PM
"allele balance ratio" and "quality by depth" in VCF files efoss Bioinformatics 2 10-25-2011 11:13 AM
The position file formats ".clocs" and "_pos.txt"? Ist there any difference? elgor Illumina/Solexa 0 06-27-2011 07:55 AM
"Systems biology and administration" & "Genome generation: no engineering allowed" seb567 Bioinformatics 0 05-25-2010 12:19 PM
SEQanswers second "publication": "How to map billions of short reads onto genomes" ECO Literature Watch 0 06-29-2009 11:49 PM

Reply
 
Thread Tools
Old 07-02-2013, 11:06 AM   #1
medalofhonour
Member
 
Location: Brighton

Join Date: Jul 2011
Posts: 18
Default Please explain the concept of "spike in controls" for NGS analysis

As a Bioinformatics person, I am currently having trouble in grasping the concept and biology behind using "spike in controls" for various kinds of next gen sequencing experiments.

From what I have read, I understand that it is used as a quality control measure , however I am struggling to understand how.

If someone could explain this concept in fairly simple language, it would be greatly appreciated.

Thank you so much.
medalofhonour is offline   Reply With Quote
Old 07-02-2013, 11:32 AM   #2
GenoMax
Senior Member
 
Location: East Coast USA

Join Date: Feb 2008
Posts: 7,076
Default

This should be simple enough: http://en.wikipedia.org/wiki/RNA_spike-in

Even though this refers to microarrays the principle stays the same for NGS.
GenoMax is offline   Reply With Quote
Old 07-04-2013, 06:41 AM   #3
syfo
Just a member
 
Location: Southern EU

Join Date: Nov 2012
Posts: 103
Default

This looks relevant too:
Synthetic spike-in standards for RNA-seq experiments.
syfo is offline   Reply With Quote
Old 07-05-2013, 08:40 AM   #4
jparsons
Member
 
Location: SF Bay Area

Join Date: Feb 2012
Posts: 62
Default

Your confusion around 'how' to use spike-in controls as a QC tool is understandable. It seems that the majority of users are in the dark as to how to use the data.

The first step is to understand what was spiked in, when, and how. In the basic case, the spike in consists of a pool of synthetic transcripts that cover a range of concentrations. For example, there may be 1 molecule of A, 2 of B, 32 of E, and so on. You would hope and expect to find that the number of counts in an RNA-seq experiment would mirror the concentration range - if you do not, you know that something went very wrong in your experiment.

Using more complicated spike-in mixtures, you can get more interesting information. The 'exfold' pools allow you to determine a measure of confidence in Ratio Detection, so you can finally give an answer (albeit a very qualified one) to the question of "where should I set my FPKM cutoff?" These and other analyses that can be performed with spike-in data will be detailed in an upcoming (est. 1-3 months) "ERCC dashboard" paper and automated in an R package.
jparsons is offline   Reply With Quote
Reply

Tags
spike in control ngs

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 04:17 AM.


Powered by vBulletin® Version 3.8.9
Copyright ©2000 - 2020, vBulletin Solutions, Inc.
Single Sign On provided by vBSSO