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help design experiments using MiSeq
How many treatments can I have in a line RNA sequencing using MiSeq?
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Depends on level of coverage you want. For reference, a MiSeq run will generate 25 M+ paired end reads of up to 300 bp each. You can use that yield to calculate theoretical coverage you will get. You can mix tens (or even hundreds) of properly barcodes samples. There is no limit there. -
This depends on three questions:
Which type of RNA are you going to sequence?
Are you going to prepare the samples?
How much coverage do you want for your experiment?
The first question relies on the prep kit you need, if it is going to seq smRNA or mRNA, there are specialized kits.
The second question is if you have in mind to prep your libraries, then you only have the size indexing. The truseq RNA has a dual index system, which you may index up to 96 samples at the same time.
But... if you are going to aquire an external service, this technical prep is not up to you.
The third question relies on the biological meaning of your experimental design. what are you going to do? variant calling? exon sequencing? differential expression? splicing? Do you have target genes in mind? de novo transcriptomic profiling? low-expression transcripts? regulational rna? siRNA? lncRNA?Comment
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Thank you very much for answering. He had thought the experiment for six libraries . but not how to calculate coverage. Again thanks and greetings .Comment
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The experiment aims to analyze the expression of genes in a plant pathogen interaction. if possible I would also get small RNAs . however it is not a priority. to obtain expression profiles of messenger is enough. thanks for your reply . Another question is , if I get libraries with 6 good coverage . finally I will request an external service.Comment
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Te recomiendo el servicio de otogenetics, fue el que solicité en mi trabajo de expresion diferencial de leprosis en citricos. Ten en cienta wue si llegases a solicitar el servicio de small RNAs, estos son aparte de secuenciacion de mRNAs. Saludos!Comment
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Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.07-01-2026, 11:43 AM
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I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...
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