Comments (3)
@satriaps Thanks for your interest in fastTopics. To answer your questions:
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The use of the multinomial measurement model (upon which the topic model is based) is supported by several recent publications, among them Townes et al (2019) and Sarkar & Stephens (2020). It is true some accounting of overdispersion could help in some settings. Most importantly, you should use the "raw" counts, not the log-transformed counts.
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Yes, that is a feature that I would like to implement. Thank you for the suggestion. One thing I should say though is that people do not typically wait for the optimization to "converge" to a fixed point (however convergence is measured), particularly for large or complex data sets. So my general advice is that monitoring convergence of the optimization is helpful, but, depending on the setting, a good solution may not require convergence.
Hope that helps.
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@pcarbo (2) is now addressed by c71461e so this issue can be closed.
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Thanks!
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Related Issues (20)
- Geting Help for FastTopics Error HOT 5
- function error-diff_count_clusters() & diff_count_analysis() HOT 2
- diff_count_clusters not found HOT 6
- Curious about how fast is the CD algorithm compared to SQUAREM HOT 2
- Feature request: multi-threaded DE analysis HOT 14
- de_analysis using LDA Topic Modeling HOT 6
- de_analysis save intermediate steps + return likelihood optimization requests HOT 19
- Flip columns of X in poisson2binom (branch:poisson2binom)
- Improve documentation for parallel computing options HOT 10
- A question on the paper on differentiation expression HOT 3
- fastTopics on normalized data HOT 3
- Type I error control for homogenous case HOT 2
- Add more colors to structure_plot HOT 2
- Error in verify.fit.and.count.matrix(X, fit) : Dimensions of input matrices "X" , "fit$F" and "fit$L" do not agree HOT 4
- Allow "fit" argument to structure_plot to also be an "L" matrix, similar to de_analysis. HOT 1
- Considerations for bulk RNAseq HOT 2
- Feature request: early stopping HOT 5
- What is a sensible threshold to select the most informative features per topic? HOT 2
- Segmentation fault in multithreading setup HOT 8
- Usage of fastTopics for multi condition multi timepoints datasets HOT 2
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