Hi Everyone,
I am a beginner in RNA-seq and am working on a project dealing with differential gene expression. I am trying to compare the gene expression between two populations each having 2-5 samples.
I am looking for genes that are differentially expressed between these two populations. I thought that it would be interesting to look at genes that have the exact same expression, but have different isoform expression levels. I ran Tophat, and Cufflinks to get my gene.fpkm_tracking and isoform.fpkm_tracking.
I am looking for some advice on statistical tests that I can use to look for genes that are statistically expressed similarly using the FPKM values of the in the gene.fpkm_tracking file, and then compare the FPKM values for the isoforms to see if there is a statistically significant difference between the isoforms.
I was looking online and I found some ideas for tests ranging from t-Tests to Poisson Distributions to negative binomial distribution (which I have no idea about). Another thing that I found is that a lot of existing programs like edgeR or DEseq use the raw read count data but cufflinks only outputs the FPKM values. How should I go about this?
I wasn't sure if CuffDiff would be a good option for what I am trying to do. Also, in general, if I were to compare the differential gene expression using the genes.fpkm_tracking file w/ the FPKM values for each gene from cufflinks, what types of Plots are ideal in this field. I have heard about density plots and heat maps but I am not sure and wanted some advice from anyone else who has done this before. I am familiar with R if that helps
Thanks in advance!!!
I am a beginner in RNA-seq and am working on a project dealing with differential gene expression. I am trying to compare the gene expression between two populations each having 2-5 samples.
I am looking for genes that are differentially expressed between these two populations. I thought that it would be interesting to look at genes that have the exact same expression, but have different isoform expression levels. I ran Tophat, and Cufflinks to get my gene.fpkm_tracking and isoform.fpkm_tracking.
I am looking for some advice on statistical tests that I can use to look for genes that are statistically expressed similarly using the FPKM values of the in the gene.fpkm_tracking file, and then compare the FPKM values for the isoforms to see if there is a statistically significant difference between the isoforms.
I was looking online and I found some ideas for tests ranging from t-Tests to Poisson Distributions to negative binomial distribution (which I have no idea about). Another thing that I found is that a lot of existing programs like edgeR or DEseq use the raw read count data but cufflinks only outputs the FPKM values. How should I go about this?
I wasn't sure if CuffDiff would be a good option for what I am trying to do. Also, in general, if I were to compare the differential gene expression using the genes.fpkm_tracking file w/ the FPKM values for each gene from cufflinks, what types of Plots are ideal in this field. I have heard about density plots and heat maps but I am not sure and wanted some advice from anyone else who has done this before. I am familiar with R if that helps
Thanks in advance!!!
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