How to determine whether a gene is present or absent?
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9.9 years ago
lovetl2002 ▴ 40

Suppose I have a level-3 expression matrix from TCGA (normalized), how to filter out absent genes before further processing like gene coexpression analysis? Currently what I do is:

  1. Set a lower threshold, like 5% quantile of all the expression level.
  2. Test whether a gene have enough portion of samples that pass this threshold. Like if 20% of samples have expression level of this gene larger than the threshold, then it can be considered as present.

I think my current method works to some extent. But is it robust enough?

microarray TCGA RNA-Seq • 4.6k views
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9.9 years ago

Keep in mind that some proteins are more efficient at their jobs than others. So a low transcription rate doesn't necessarily mean low or absent protein activity. You've also probably noticed that all or most of the lower quartile genes have a readcount of zero. There are two possible reasons for this:

  1. The gene is not transcribed at all, which is fine, and is exactly what you're trying to remove.
  2. The RNA-seq performed is insufficiently deep to capture the transcript expression. We can't recover these without sequencing more RNA.

Since TCGA RNA-seq is enriched for RNA with poly-A tails (more likely to be protein coding mRNA), I would go as far as to say that a single high quality uniquely mapped paired-end read across a transcript is sufficient evidence of transcription. But I'm a hopeless idealist, so a stricter cutoff from TCGA's RNA-seq working group is to study only genes with at least 3 reads in at least 70% of samples. Click here and here for related notes.

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Hi Cyriac,

When you say 3 reads at the end, do you mean 'paired-end read' as you defined in the beginning ? Wouldn't it be 3 fragments if its so ?

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Yes. Some TCGA RNA-seq was done with single end reads. Hence the generalization.
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Thanks. What if I use microarray data?

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I only have rough experience with gene expression arrays, so I can't recommend any cutoffs. But hybridization bias and the noisiness of probe intensities, make it hard to reach the kind of determinism we get from RNA-seq - of whether a fragment of a specific mRNA was transcribed or not.

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Hi

Your topic is related to my project I am working with TCGA colorectal gene expression

Could you help me about Create a Tissue Model for Convert the Affymetrix data to a format that can be used by the "createTissueSpecific()" Cobra Toolbox function we use biocLite("affy") but my data is unc_agilentg4502a_07 and it is ADF format how can convert it to present, absent AP.txt and EID.txt is value of gene expression. Which cutoff is best for it?

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Your question is not related to this thread. Please open a new one... and use tags to notify appropriate watchers.

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