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XiaoTaoWang / EagleC

A deep-learning framework for predicting a full range of structural variations from bulk and single-cell contact maps
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Help Interpreting Results for Structural Variations #39

Open qolba opened 3 months ago

qolba commented 3 months ago

Hi,

I’ve been using EagleC to analyze HiC data, and I’ve encountered some results that I’m having trouble interpreting. The output looks like this:

chrom1 pos1 chrom2 pos2 ++ +- -+ -- chr10 3150000 chr10 4800000 2.543e-18 1.478e-14 0.8158 1.85e-20 chr18 42200000 chr18 43800000 1.738e-11 6.265e-12 0.9564 1.28e-09 chr21 24500000 chr21 30650000 3.837e-08 0.8111 1.423e-08 1.402e-07

I’ve visualized the reported regions, and they seem to show some form of structural rearrangement, but I’m not sure how to distinguish between different types of events like deletion, duplication, insertion, or inversion based on these results.

Could you please explain how to interpret the ++, +-, -+, and -- columns? How do these values relate to different types of structural variants?

Thank you for your help!

N268_50kb_chr10_3150000_4800000 N268_50kb_chr18_42200000_43800000

XiaoTaoWang commented 3 months ago

Hi, the values in these columns represent the probability scores indicating the likelihood that a predicted SV belongs to a specific fusion type ("++", "+-", "-+", and "--"). Specifically, if an SV has high scores for both "++" and "--", or for both "+-" and "-+", it can be interpreted as a reciprocal translocation it the fusion occurs between two chromosomes. Similarly, an inversion is expected to have high scores for both the "++" and "--" fusion types.