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ShixiangWang / sigminer

🌲 An easy-to-use and scalable toolkit for genomic alteration signature (a.k.a. mutational signature) analysis and visualization in R https://shixiangwang.github.io/sigminer/reference/index.html
https://shixiangwang.github.io/sigminer/
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https://www.biorxiv.org/content/10.1101/2023.02.09.527740v1.full #424

Open ShixiangWang opened 1 year ago

ShixiangWang commented 1 year ago

https://github.com/jennprk/diffsig

songzhirui0o0 commented 1 year ago

Hi Dr. Wang, I have two questions for you:

  1. I saw that your software supports ASCAT, FACETS and Sequenza(https://shixiangwang.github.io/sigminer-book/analysis-supps.html?q=ASCAT#read-data), I would like to ask the first question: Have you done any consistency comparison of feature decomposition of the same dataset by these software? If the features decomposed by the three software are inconsistent, where do I start to find the reason and how do I determine which of the three is more reliable?
  2. After decomposing the features, how do I perform copy number feature decomposition for a single sample based on the known copy number features? Or, do you think it is necessary to perform copy number feature decomposition for a single sample? These are the questions I am facing, and I would like to ask you to give me some guidance.Thank you!
ShixiangWang commented 1 year ago

@songzhirui0o0

  1. Some comparisons are provided in manuscripts https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1009557 and https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbad053/7048898?login=false. In general, I recommend ASCAT, Sequenza, and FACETS in order.
  2. You can do a single sample analysis. If you have no experience analyzing mutational signatures, I recommend you read through the documentation book https://shixiangwang.github.io/sigminer-book/basic-workflow.html. In general, the workflow to analyze a sample is given: