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  • wingless
    Junior Member
    • Jan 2012
    • 8

    Comparing transcript enrichment RIP vs Input - is it meaningful?

    Hi, I have been wondering the following:

    there are lots of methods to sequence protein-bound RNAs nowadays such as RIP, CLIP whatever-IP .. as far as I can tell from papers doing it, people just sequence what's in the IP, and use similar approach to peak calling to say if a given transcript is targeted or isn't targeted by a given protein. This is fine, but gives you binary data i.e. whether a transcript may be a target of a protein or not.

    Is it wrong, in principle, to compare the read counts mapping to transcripts in IP versus read counts in input (normal RNA seq), and infer enriched transcripts in the IP based on these numbers (like IP/input ratio per gene) ? What package can be used to provide some meaningful stats?

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  • GATTACAT
    Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
    by GATTACAT
    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
  • SEQadmin2
    Nine Things a Sample Prep Scientist Thinks About Before Sequencing
    by SEQadmin2


    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...
    06-18-2026, 07:11 AM

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