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  • chobeich
    Junior Member
    • Jan 2020
    • 5

    SNP array analysis

    I there!!
    A friend has passed me the data of an Infinium Omni5-4 array. In short, they have applied two different mutagens to a cell line. I have passed a data set that contains:
    3 mother samples (MS)
    3 samples mutagene 1 (M1)
    3 samples mutagene 2 (M2)
    Its objective is to identify the mutagenic potential of each mutagene.
    After googeling, I think what I need to do is a Manhattan plot to identify the chromosomal regions that have mutated the most for each mutagene.
    What I have done at the moment is:
    1 Genotyping callin, using the Genotyping Module of Genome Studio
    2 Establish the reference set: SNP's 100% call and with the same genotype in all MS.
    3 Assign each SNP of samples M1 and M2 a 1 if the genotype has varied from the reference or a 0 if it has not. The SNPs of the M1 and M2 samples that are not in the reference set or that are not 100% called have been discarded.
    I have done all this with perl. What I now have is a text file with the following structure:
    SNP_1 SNP_2 ...
    M1.1 1 0
    M1.2 1 1
    .
    .
    M2.3 0 0

    And that's all folfs!!, I have no idea what I should do now.
    Any help will be welcome because, as you may deduced, I have no idea of ​​working with arrays or statistics.
    Thank you

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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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  • SEQadmin2
    Nine Things a Sample Prep Scientist Thinks About Before Sequencing
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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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