Can you explain me in deapth what is cycle? What is the difference beetween 100 o 200 cycle?
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Hello Davideapplevv I'll try to explain this in a simplified version.
A cycle is when a base is added during the sequencing process. Each base is fluorescently labeled so you can determine the sequence of the DNA you are interested in. So a 100-cycle run would produce DNA sequences (reads) that are 100 bases long. A 200-cycle run would produce DNA sequences that are 200 bases long or they could produce two separate reads that are each 100 bases long, which is referred to as a pair-ended run.
If that doesn't make sense then think of it like this. Imagine you have a 10-cycle sequencing kit. If you ran your samples on the sequencer, your data (reads) would look something like this - AGGCATTTAC - meaning only 10 bases because the kit was for 10 cycles.
Watch this video. And to understand the cycles, start at 2:14 where it begins to explain the part about sequencing. It will show you what each cycle looks like.Explore the Illumina workflow, including sequencing by synthesis (SBS) technology, in 3-dimensional detail. Go from sample preparation, to cluster generation...
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No worries Davideapplevv. You're correct, with a 200-cycle kit you couldn't do a 1x150bp run. You could do a 200 single read or a 2x100 pair-ended run. But what instrument are you planning on running this on? Also, Illumina kits have a few more cycles than they advertise. Meaning a 100-cycle kit might actually have 130 cycles, but you use those for index reads and maybe extending your other reads by a few bases. Check this bulletin for exact details.
https://support.illumina.com/bulleti...in-my-kit.html
And the number of samples depends on several factors. Theoretically you could add hundreds of samples into a single run, but they would get less reads. The number of samples you run would depend on the number of reads you want, the depth and coverage of your region of interest, and a several more considerations. Illumina has a calculator somewhere on their site to help you determine the amount of data you need.
Other things to think about are the complexity of your samples (library diversity), the output of your machine, and the results of previous runs. You don't want to overload the sequencer and you don't want the run to fail because you loaded one sample that didn't have diversity.
Hopefully that helps.
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