Entering edit mode
23 months ago
Jahnavi • 0
I am new to bioinformatics and was recently playing around with tophat. I wanted to know how to analyse the results. Also, if the results state, 97% high-quality filter reads mapped on the reference genome, what does it signify?
If you could help out with the same for fast qc results where again results are over 99%
What can we say other than "Good" or "high-quality results".
Thank you so much!
welcome to the field.
and immediately a word of caution: TopHat is no longer the go-to tool for RNAseq mapping. There are more modern and better tools around (even the original authors of TopHat don't adivse it anymore). You should look into things like: HiSat2, STAR, BBMAP, ...
oh ok, that's helpful! i'll try experimenting with HiSAT2 after this round of results!
I don't understand your question. What do you want to know? If your data is "good" enough to do downstream analysis?? Yes, your data looks good. But with "I wanted to know how to analyse the results", what do you want to see with your data? What is your biological question? Is human data? Is always good to elaborate your question first. You can explain the type of data you have, the analysis you have done and what do you want to address. I'm very happy to help if further information is given
So the RNA-seq data has been mapped on the chickpea genome. I will be future analysing it under stressed conditions such as heat, cold, etc and looking into the DEG. As of now I was just questing every step and trying to understand the rationale behind it. I was wondering about the significance of the 99%. That being, high contamination of the sample or low-quality reads and what factors can increase or decrease this percentage.
What do you mean "for fastqc results where again results are over 99% "? In which section? As suggested above try other mapping tools. I personally use STAR for RNAseq data. Then run again fastqc as you did, and if you have troubles to understand the results you can upload the plots here. Later you can use DESeq2 in R for DEG, the manual has a lot of information.