Go Back   SEQanswers > Bioinformatics > Bioinformatics

Similar Threads
Thread Thread Starter Forum Replies Last Post
advice/critique on my RNA-seq workflow slavailn Bioinformatics 3 12-15-2011 05:20 PM
RNA-seq Galaxy workflow for PE barcoded samples? jjw14 Bioinformatics 0 04-19-2011 01:58 PM
RNA-seq workflow foxyg Bioinformatics 1 11-11-2010 04:26 PM
New! Ovation WGA FFPE and RNA-Seq FFPE workflow solutions from NuGEN Technologies NuGEN Vendor Forum 0 11-03-2010 10:02 AM
Splicing Analysis in Partek RNA-Seq workflow xguo Bioinformatics 1 12-21-2009 10:06 AM

Thread Tools
Old 02-09-2012, 08:50 AM   #1
Location: LA

Join Date: May 2008
Posts: 78
Default Genomatix RNA-Seq workflow


has anyone used Genomatix for RNA-Seq analysis?
I am particularly interested in the interpretation of the output of the Audic-Claverie algorithm for differential gene expression analysis described here:
Can someone tell me how is calculated the "NE value" for differential expression?
How it relates to RPKM?

Thank you!
rebrendi is offline   Reply With Quote
Old 02-13-2012, 08:13 AM   #2
Junior Member
Location: germany

Join Date: Feb 2012
Posts: 1


The NE is explained at:

Normalized expression/enrichment value (NE-value)
The NE-value is calculated based on the following formula:

NE = c * #readsregion / (#readsmapped * lengthregion)

where NE is the normalized expression or enrichment value,
#readsregion: the reads (sum of base pairs) falling into either the transcript or the cluster region,
#readsmapped: all mapped reads (in base pairs),
lengthregion: the transcript or cluster length in base pairs
and c a normalization constant set to 10E7.

This is quite similar to RPKM.

Regarding Audic & Claverie statistics: This was originally designed for the count data in cDNA / Sage libraries. "The Significance of Digital Gene Expression Profiles" Audic & Claverie, 1997.
The idea is to calculate the conditional probability to find y counts for your sequence feature (gene, transcript, ChIP region) in your treatment data when you saw x counts in the control for the same sequence feature.

However, for NGS data this calculation overestimates the number of significantly deviant features, since it is based on a Poisson model. As discussed here several times the Poisson model doesn't fit well for NGS data.

If replicates are available I strongly recommend using DESeq or EdgeR. For ChIP-seq clusters however, you must merge or intersect the clusters from your replicates. The workflow is explained at:

Bernward 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 10:27 PM.

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