Question: Expression Analysis With 454 Cdna Data
1
gravatar for Litali
10.3 years ago by
Litali10
Litali10 wrote:

How can I perform expression analysis of 454 data?

gene rna • 2.4k views
ADD COMMENTlink modified 9.7 years ago by Michael Dondrup48k • written 10.3 years ago by Litali10
1

Would you mind explaining a little bit more: what exactly do you need, what type of data you have, setup, software, etc.

ADD REPLYlink written 10.3 years ago by Paulo Nuin3.7k

454 cDNA data, I have contigs assembled with the 454 Assembler. I have different experimetns(say different time points) , each run in other time and different size of lanes. Now I want to compare the expression of different genes between the conditions (how many reads each contig received? normalized over the number of total reads in this condition?)

ADD REPLYlink written 10.3 years ago by Litali10
2
gravatar for Chris Miller
10.3 years ago by
Chris Miller21k
Washington University in St. Louis, MO
Chris Miller21k wrote:

TopHat and Cufflinks are often good tools for working with RNAseq data.

In order to give a better answer, though, we're going to need more information about what your data consists of and what your goals are.

ADD COMMENTlink written 10.3 years ago by Chris Miller21k

454 cDNA data, I have contigs assembled with the 454 Assembler. I have different experimetns(say different time points) , each run in other time and different size of lanes. Now I want to compare the expression of different genes between the conditions (how many reads each contig received? normalized over the number of total reads in this condition?)

ADD REPLYlink written 10.3 years ago by Litali10

I think firs of all you need to have your contigs/isotigs annotated (to do so you can use TopHat or Cufflinks if you have a reference genome) and then analyze the expression level of all the genes you've detected in the annotation step and then check it they are differentially expressed. I think the key point is if you have a reference genome or not.

ADD REPLYlink written 9.9 years ago by Marina Manrique1.3k
0
gravatar for Michael Dondrup
10.3 years ago by
Bergen, Norway
Michael Dondrup48k wrote:

Here are some good review papers for you to start with, that will help you find out what's possible and what's not. Also, you can make your live with these data much easier using R & Bioconductor.

Some good resources for R where mentioned here.

I also recommend R-packages DESeq and edgeR.

  1. Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nature reviews. Genetics. 2009;10(1):57-63. Available at: http://www.ncbi.nlm.nih.gov/pubmed/19015660.
  2. Pepke S, Wold B, Mortazavi A. Computation for ChIP-seq and RNA-seq studies. Nature methods. 2009;6(11 Suppl):S22-32. Available at: http://www.ncbi.nlm.nih.gov/pubmed/19844228.
ADD COMMENTlink modified 14 months ago by _r_am31k • written 10.3 years ago by Michael Dondrup48k
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