Hi,
I plan on analysing the following RNA seq data: cca 30M reads/sample, 15 samples, human data. The aim is to do differential expression analysis. I plan to perform alignment with HISAT2 and I wonder if my computer (specifications below) suitable for this?
If not I, what would my best option be - additional RAM (how much?) on this computer, different alignment tool, cloud computing (like AWS), galaxy?
Any input or experience is helpful! Thanks, Nina
You could use kallisto : https://pachterlab.github.io/kallisto/about . It uses minimal RAM with similar sensitivity as more "standard" "align-then-count" methods. In general less than 4Gb RAM per sample is required
From kallisto website :
On benchmarks with standard RNA-Seq data, kallisto can quantify 30 million human reads in less than 3 minutes on a Mac desktop computer using only the read sequences and a transcriptome index that itself takes less than 10 minutes to build.
it would better say pseudo-mapping or pseudo-alignment tha mapping methods ;)
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AFAIK, HISAT2 is the best alignment tool for low RAM. 1 TB is way enought to stock your data and output data. I would say, give it a try and if the alignment step failed, look at the output error to know if it is a memory issue or something else. If it is a memory issus you can try to add more RAM or run your alignment under a cluster. I have no experience with galaxy.