We have two samples control and treatment without any replicates. I want to find differentially enriched / expressed transcripts in treatment over control.
I know it is not good to proceed without any replicates but still there are methods which supports samples without replicates. I just want to know which one is trustable ?
The problem is since I don't have any replicates I can't trust any statistical packages (like edgeR, DESeq or cuffdif) which provides us FDR. I have also used GFOLD which gives logFC and gfoldFC, but I don't know how to fix the cutoff from this fold change values and get the top enriched transcripts. Because if I fix some gfoldFC cutoff and use it for geneontology which does not give any biologically relevant processes for the type of sample I used. For example the sample is pull downed RNA from certain cell cycle phase, where I should atleast expect some cell cycle related terms.
But in case of edgeR or DESeq when I filter with logFC and FDR at-least gives some related terms to the samples.
Or Is it fine if I use GSEA preranked test for all the list of protein coding genes with fold change from edgeR, DESeq or GFOLD?
Is there any analysis where I can trust for samples without replicates. Please let me know how to further proceed with this type of data.
In this paper they have compared the availabe differential expression analysis packages. Where DESeq produces less true positives than edgeR in case of less number of replicates.
I know it is not good to proceed without any replicates but still there are methods which supports samples without replicates. I just want to know which one is trustable ?
The problem is since I don't have any replicates I can't trust any statistical packages (like edgeR, DESeq or cuffdif) which provides us FDR. I have also used GFOLD which gives logFC and gfoldFC, but I don't know how to fix the cutoff from this fold change values and get the top enriched transcripts. Because if I fix some gfoldFC cutoff and use it for geneontology which does not give any biologically relevant processes for the type of sample I used. For example the sample is pull downed RNA from certain cell cycle phase, where I should atleast expect some cell cycle related terms.
But in case of edgeR or DESeq when I filter with logFC and FDR at-least gives some related terms to the samples.
Or Is it fine if I use GSEA preranked test for all the list of protein coding genes with fold change from edgeR, DESeq or GFOLD?
Is there any analysis where I can trust for samples without replicates. Please let me know how to further proceed with this type of data.
In this paper they have compared the availabe differential expression analysis packages. Where DESeq produces less true positives than edgeR in case of less number of replicates.
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