Fwd: dnenrich

[Ingo Ruczinski]

Just noticed the dedicated the googlegroup email, sorry, please see below.

Begin forwarded message:

From: Ingo Ruczinski <iruc...@jhu.edu>

Subject: dnenrich

Date: May 19, 2017 at 2:22:42 PM EDT

To: fro...@broadinstitute.org, shaun....@mssm.edu

Dear Menachem, Dear Shaun,

We are interested in finding out whether de novo SNVs are enriched in genes previously implicated in birth defects, and I came across your dnenrich approach (Fromer et al 2014). I had a quick question regarding the following statement from the software page 

"To model exome-wide dispersion of de novo variation under a null hypothesis that accounts for gene size, tri-nucleotide context and functional effect of a mutation, and per-trio effective gene coverage, random permutations are used to place mutations in the "exome", while the number of mutations, their base context, and functional impact are held fixed to that of the observed data.”

For ‘functional effect’, did you just consider LoF versus not in the permutation, or was there a more refined distinction? I am also not sure what precisely you mean by 'tri-nucleotide context’ here. I couldn’t find the answer in the paper / supplements or the software page. I noticed the supplements stated a paper in preparation, has that appeared anywhere? Searches on pubmed and biorxiv were negative.

Thanks a lot!

Cheers, Ingo

...

[  Ingo Ruczinski  |  http://biostat.jhsph.edu/~iruczins/  ]

[Daniel Howrigan]

Hi Ingo,

Here's my quick take on 'functional effect' and 'tri-nucleotide context'.

functional effect is the primary consequence of the nucleotide change, be it a 

1) synonymous change (amino acid is preserved)

2) missense change (amino acid is altered) 

3) LoF/PTV/LGD (a stop codon is created/lost, a start codon is lost, a frameshift alters the subsequent amino acid pattern, or an essential splice site is altered).

Whether any of these changes are damaging or deleterious to the downstream biological product may require additional information (hence the many missense severity algorithms out there), such as evidence of conservation, measured downstream biological consequences, or correlation to severe phenotypic outcomes.

tri-nucleotide context:

These are the two bases around the mutated sequence, e.g.

reference context: CGG

alternate context: CAG

the C and G around the G to A mutation are the 'context', and the chemical structure binding the nucleotides together affects the rate at which mutations can happen. CpG transitions/transversions are the trinucleotide context with the highest rate of mutation. While this fairly simple model doesn't perfectly predict the mutation rate, it does a pretty good job.

hope this helps,

best,

Dan

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Daniel Howrigan, Ph.D.
Analytic and Translational Genetics Unit
Massachusetts General Hospital