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Error: BiocParallel errors #14
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Hi @MichaelPeibo, |
Hi @asenabouth ,
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Hi @MichaelPeibo - I've found the cause of your error, and it may have downstream effects. Turns out the scranNormalise function has converted some of the values into the expression matrix into infinite values - this is definitely not ideal. I will look into this; in the meantime, I recommend you use the other normalisation method |
scranNormalise has been fixed, and RegressConfoundingFactors function now works on your dataset @MichaelPeibo . Thank you for raising this issue. Please let me know if you have any other issues. |
@asenabouth
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That's a strange result. Your dataset is large enough to have enough variance (unless the regression removed this). We don't usually regress confounding factors on our dataset (the option is there for those that do wish to do this step). Do you get the same result on the dataset if you don't use the confounding factor regression? You can also use the 'remove_outlier' option with RunCORE to see what you get. This step will remove these outliers however, and is more time consuming as it repeats the dynamic tree cut until all remaining cells can be assigned a cluster. |
I had a look at your data to see if I can shed any more light on the issue - if you generate a PCA plot with PlotPCA you will see some the majority of the points in one location and some distinct data points separated away from this location. These would be the outliers in your dataset. I also ran RunCORE with remove_outlier set to TRUE, which discarded (but kept a record of) these cells which generated a result of three clusters. The number of outlier cells was less than 20, which is the minimum cluster size set by dynamicTreeCut. The way RunCORE works is it performs clustering at different resolutions and then selects the most stable resolution for you. Once you run the RunCORE function, you can view the results of all the resolutions by using the GetRandMatrix function and PlotStabilityDendro function, so you can decide if that was the best resolution for you. We also introduced an option in the latest update to set the size of these sliding windows by using the "windows" argument (just input a sequence of numbers ranging from 0 to 1). It will still try 40 different resolutions however. Hope that helps. Our group is working on a more detailed clustering package for single cell data, but we don't have an ETA for that yet. |
Hi @asenabouth Another point confused me is what you mentioned in your tutorial and your paper(congrats!), you think there are some apoptosis pathway related genes enrich in cluster2, how do you define it ? Is there any way to determine it automatically? Thanks! |
Hi @MichaelPeibo - thanks for your questions! It gives us a good idea of how our users are using our package. I'm moving your comments to different threads, just so it will be easier to track and if any other users have similar questions, they can refer to your threads. |
Hi, Ascend team
after normalization by scranNormalise, I want to regress out the cell cycle factor by RegressConfoundingFactors, however, when I run this function , I got this error,
I did installed and configured the BiocParallel as you told, any suggestion on this? Thanks!
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