Normalization of FPKMs from Cufflinks

[greener]

Hi there,
I have been using the Tuxedo suite tools , specifically I have been using bowtie, tophat,and cufflinks. Now that I have FPKM values I have a couple of questions.
1. What are the most common ways folks are using to normalize their FPKM data?
2. I am looking into differential expression of the FPKM values across my samples and time points. I have successfully run cuff compare but when I run cuffdiff I get results (Tested id XLOC_000001, locus, etc.) but my gene ids are not in the output. any suggestions people have on why that might be missing? I can always map the tested id with cuff compare results. Any suggestions people have are apprciated. Thanks
-Rich

[reut]

missing gene id

Hi

Regarding question #2 -
If in the annotation gtf file you provide for cuffcompare there is no "gene_name" field, then in cuffdiff output there are no gene names.
For example, when I used ucsc gtf file it has no "gene_name" but Ensembl does have this field.

Regarding question #1 -
As far as I understand, FPKM values are already normalized. but I am not sure about this.

HTH
Reut.

[greener]

Thanks Reut, It was my understanding that one's individual cufflinks run generate normalized FPKMs. I have run multiple cufflinks runs across conditions, time points, and with replicates. I'm curious how folks normalize sets of cufflinks results. Additionally aside from cuffdiff have folks had much luck using LIMMA on FPKMs for differential expression? Thanks!
-Rich

[jp.]

anybody got answer?
My trouble is to make csHeatmap of normalized diff gene's fpkm values.
For example, csHeatmap can be generated using XLOC IDs (cummeRbund gets the real fpkm values and makes heatmap in Log scale). However, to get scale +1 to -1, I have to mannualy get all fpkm values and then convert to Log10 and then normalize them and, finally, generate heatmap using gplots.
Is there any other method which can do it automatically as csHeatmap(cummeRbund) does with Log scale Or any way to normalize using cummeRbund. How others are doing ?
Some solutions Please
thank you