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Old 08-22-2017, 02:34 AM   #1
katiadt
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Location: Italy

Join Date: Aug 2017
Posts: 2
Default assembly vs mapping results

Hi guys, I performed RNA-seq analysis of bacterial transcriptome in four different stressed conditions, mapping the reads on its own genome available in NCBI. Then I used FeatureCounts for reads counting and finally I performed differential analysis with NOISeq R package, because of the absence of replicates.
Before that, my tutor submitted the analysis to a famous company requiring a de novo assembly (they used the trinity pipeline for assembly and differential analysis).
I used the same fastq files, and finally I found a larger number of DE genes, but my results are the opposite of company's results. How is it possible? I know that mapping is better than assembly when a reference genome is available and above all I know that the trinity pipeline have some problems for differential analysis, because it uses DESeq or edgeR after quantification by RSEM.
What do you think about?
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