Hi,
I just got my first RNA-seq dataset alignment results today, and I am wondering what would be considered a "good run".
This is a pilot experiment, whose objective is to determine how many samples we can multiplex in one lane of Illumina HiSeq to get the information we want and the best trade off between cost, specificity and sensitivity.
This are mouse brain samples, I am getting 75 million read pairs, of which 85% map consistently (the fwd and rw read map to the same place) and uniquely. I get 97% of the reads mapped in total.
I am concerned about the coverage, I get about 10% of the bases in the mouse genome covered by unique mappers and 3% by non-unique mappers.
Is this typical? When people talk about 30X coverage of RNA-seq datasets, what is the coverage relative to? RefSeq mRNA?
Right now I am running 3 samples per lane, and want to know whether this coverage is enough for basic transcriptome analysis, whether I can multiplex more or if I should run less samples per lane
thanks for the help
I just got my first RNA-seq dataset alignment results today, and I am wondering what would be considered a "good run".
This is a pilot experiment, whose objective is to determine how many samples we can multiplex in one lane of Illumina HiSeq to get the information we want and the best trade off between cost, specificity and sensitivity.
This are mouse brain samples, I am getting 75 million read pairs, of which 85% map consistently (the fwd and rw read map to the same place) and uniquely. I get 97% of the reads mapped in total.
I am concerned about the coverage, I get about 10% of the bases in the mouse genome covered by unique mappers and 3% by non-unique mappers.
Is this typical? When people talk about 30X coverage of RNA-seq datasets, what is the coverage relative to? RefSeq mRNA?
Right now I am running 3 samples per lane, and want to know whether this coverage is enough for basic transcriptome analysis, whether I can multiplex more or if I should run less samples per lane
thanks for the help
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