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  • Libby Evans
    Junior Member
    • Apr 2018
    • 1

    Balance sequencing runs ATAC

    I am having trouble balancing my sequencing runs for ATAC-seq. I am doing extensive kapa on the samples but often finding one out of a pool of 6 will be far too high (on one occasion taking 40% of the total reads). These samples often look quite low by kapa. Has anyone experienced this?

    If you do size correction how do you do this? (On the tapestation or bioanalyser?) Also do you typically do a size selection after the indexing clean up? I haven't included that yet but could. Any advice very welcome! Thanks.

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    Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
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  • GATTACAT
    Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
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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.
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