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  • teatime
    Junior Member
    • Dec 2011
    • 1

    Using profile HMMs (HMMER) to annotate genomes

    Dear community,

    I didn't find a direct answer to my question. I am planning to annotate a huge bunge of genomes and metagenomes with profile HMMs like Pfam (also some custom models).

    Because of the large size of the data set, I won't be able to optimize individual alignments of the HMMs and I am looking for a good set of parameters for hmmsearch (inclusion parameters) and postprocessing thresholds for e-values and coverage values, i.e. length of the match with respect to the length of the domain model. Could you please cite or tell me infos about finding values that are a good compromise!? And how would it be when processing some metagenomes?

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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.
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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.

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