Which transcriptome assembler is recommended for short-read cancer transcriptome data?
Hello!
I would like to do a de-novo transcriptome assembly on human control/cancer, short-read RNA-seq datasets. I would like to identify possible unannotated (cancer-specific) transcripts. Which assembler software would you recommend to use in this case?
Our server has 24 cores, 94 Gb RAM, so any softwares like Trinity would not be possible.
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Benedek Dankó •
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Trinity is the best, it can reduce memory if you: - run samples separately - use normalization
Alternatively, rnaSPAdes can be used
Also, you can use some strategies to detect novel genes and fused genes using genome alignments.
Trinity needs a GB of RAM per million reads. How many million reads do you have?
Around 30 million (paired-end) per sample but there are samples with more (eg. 60-70 million).
You should be able to get them to run with hardware you have.