Comments (3)
Hi M.,
10x is not the best for making smudgeplots, the coverage variation is a bit higher compared to other types of libraries (surprisingly even PacBio HiFi is better for kmer spectra analyses). So I think your analysis will be a bit more sensitive to the L parameter you chose. What did you use? And can you show us also a genomescope plot? That helps a lot to decide about a meaningful L.
I am a bit puzzled of the 1n coverage estimate, I am not 100% how smudgeplot ended up on that number... (the labels are not well overlaping with the smudges). But I also supect your L was too low and the bottom part of the smudgeplot is simply error kmers paired with the unique genomic kmers and then the upper smudge is the real diploid one (which would also estimate the 1n coverage a bit closer to the expected 30x, assuming that the 60x is what people call genome coverage, not per-haplotype coverage).
from smudgeplot.
Hi Kamil,
Thank you for looking into this! Here is the genomscope plot made using 31-mers (high K chosen due to genome repetitiveness). I was not sure whether to also apply a higher K for smudgeplot and just followed the guide. I hope it helps with your interpretation.
L was set to 15 and U to 2700 based on the output from the smudgeplot.py cutoff. I can raise L on the next smudgepairs run (takes a day and a half).
Thanks again,
Mason
from smudgeplot.
Hi Mason,
that is a giant genome. That must be a huge dataset you are dealing with.
So, the first thing first. Your sequencing is not the cleanest (which is understandable for giant mollusc genomes) - the error peak and genome peak are overlapping. The problem is that you don't have a clean cut between errors and real genomic kmers, which is what we want L to be.
Good news is that the genomescope looks alright (both het and homo zygous peaks are kind of visible and the model relativelly well explains the data). Also, you have very little evidence of polyploidy (assuming your 1n coverage fit is right), because those usually have some of the higher coverage peaks relatively high as well. So the only thing I would suggest to you is to redo the smudgeplot PLOT with a coverage prior from the genomescope model. You can run it as:
smudgeplot.py plot 21kmc_L15_U2700_coverages.tsv -n 18 -o "Land_snail" -t "O. idahoensis"
I am suspecting you will get the peaks annotated right this time (as AB and AABB). I suspect the proportion of AB vs AABB kmers will be a bit different and quite possibly favouring AABB. That practically means that the 2n peak kmers have very often a very similar kmers within the same 2n peak. It is a puzzling signature for genomes with high heterozygosity, but perhaps we should not be bothered by this that much given how much troubles we had separating 1n and error peaks. Perhaps just keep in mind for downstream analyses that you might have quite a lot of paralogy in your genome (and keep even deeper in your mind that there polyploidy was not conclusively rejected in this analysis).
from smudgeplot.
Related Issues (20)
- long run time HOT 5
- Smudgeplot interpretation HOT 3
- Question about using corrected long reads for smudgeplot HOT 3
- Haploid x Smudgeplot HOT 1
- Lower coverage cutoff higher than upper coverage cutoff HOT 1
- sharing strange smudgeplot for imporve smudgeplot HOT 1
- Smudgeplot for allotetraploidy HOT 5
- Interpretation of smudgy smudgeplot for diatom genome HOT 2
- Could I use to these AAB kmer to make evaluation the assembled phased genome? HOT 3
- failed to obtain the final plot HOT 3
- Smudgeplot estimated incorrect ploidy level HOT 6
- Outputting smudgeplot in pdf format HOT 1
- What is "1n = 25" on the smudgeplot plots? HOT 2
- Changing color of letter(AB, AAB etc) HOT 2
- Conda install dependancy: `cairo.so` HOT 10
- ask for help: Smudgeplot erro HOT 4
- Trouble with interpretation HOT 10
- Genomescope and smudgeplot for genome with several whole-genome duplications HOT 4
- Trouble with interpretation HOT 9
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from smudgeplot.