Average spotlength


I would like to calculate the average spotlength of reads obtained from 50 different samples after paired end 300 sequencing using Miseq platform.

Please let me know How can i calculate the average spotlength of each sample separetely using linux command line ?


Hi @M_F,
We're not exactly sure what you're referring to. Could you point us at a definition of "spot length" in this context?


Hello @gregcaporaso ,

Thanks for your reply.

I referred to this link to give you a definition of spot length
What Is A "Spot" In Sra Format.

"The spot length is the expected total length for all reads."

I need to know how to calculate reads spot length directly using linux command lines.


Thanks for the link @M_F, that explains it.

We don't have a way to calculate that directly in QIIME 2, as far as I am aware. If this is for an SRA submission, perhaps they have some recommendation on how to do this? You might also check with some more general tools for working with fastq files, like FastQC. It's also possible a clever forum user might be able to provide an example of how to do this using Linux built-in tools, which shouldn't be too difficult but I don't have time right now to derive and test a command for doing this.


Hi @gregcaporaso and @M_F,

Maybe this is utterly naive, but if the reads are untrimmed, wouldn't the average spot lenght be 300nt? And, if the reads are trimmed, wouldn't you expect it to be 300 - trim length?



@jwdebelius, I think you may be right. Despite the title of this post (my bad), I was thinking the goal was calculating a total spot length as something like the length of all reads, post-trimming, summed on a per-sample basis.

So that said, @M_F, if using QIIME 2 for read processing, there isn't a direct way to have this computed across all samples post demultiplexing (someone please correct me if I'm forgetting about something here), but the output of qiime demux summarize will provide this information across all samples in the bottom of the second tab. For example (for a single-end data set):

Thanks @jwdebelius!

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