Differentially expressed microRNA analysis using bowtie2-cufflink-cuffdiff
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7.3 years ago
illinois.ks ▴ 200

Hello all,

I am working on the differentially expressed microRNAs analysis.

I have used the bowtie2-cufflink-cuffdiff pipeline. (for the reference I downloaded from UCSC site)

I have two questions.

  1. When running cufflinks, I have ran two ways (with -g xxx.gtf option, without -g option). I know it should only makes small difference. But results look somehow different. Especially, the fpkm value as well as the status of significance. So, I will get different DEGs based on the existence of -g option. Does it make sense?
  2. Second, even though it is the fastq file of miRNAs, from the output file gene_exp.diff of cuffdiff, I can see some of reads are mapping to genes instead of miRNAs.. I may guess it is true since our experimental data can have some of mRNAs even though it intends to include microRNAs. Among 83 significantly differentially expressed ones, only 27 are mapped to microRNAs. Is it reasonable number? Or Do I miss something?
microRNA DEG cufflinks cuffdiff bowtie2 • 2.4k views
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you can check once without cufflinks

run featureCount/htseq-count providing only miRNA unique gtf

calculate counts per million,

you can also normalize with DEseq2, and see if you get reasonable DEGs 

Entering edit mode

In addition, among the gene_exp.diff results , there are some transcripts (genes) having status of significance is "NO" because one of fpkm of samples is zero so log fold change is -inf/inf..

In my result, I have  approximately 40 miRNAs having zero fpkm for Sample 2 (i.e log foldchange is -inf) and approximantely 90 miRNAS having zero fpkm for Sample 1 (i.e. log foldchange is in) .. 

Do I also have to include those miRNAs as Differentilaly expresed ones by recalculating the logfoldchange after replacing the zero to 1 or something else???  




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