PureCN Plotting Error: Troubleshooting & Solutions

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PureCN Plotting Error: Troubleshooting & Solutions

Hey there, fellow bioinformaticians! 👋 Have you ever run into a roadblock while using PureCN, especially when it comes to plotting your data? Specifically, have you seen the dreaded error Error in plot.window(...) : need finite 'ylim' values? Yeah, it's a bummer, I know. But don't worry, we're going to dive deep into this issue, figure out what's causing it, and explore some potential solutions to get you back on track. In this article, we'll cover the problem, how to reproduce it, and even suggest some workarounds. Let's get started!

Understanding the PureCN Plotting Crash

So, what's the deal with this plot.window error? It usually pops up when PureCN is trying to generate plots, particularly when it's dealing with the B-allele frequency (BAF) plot (plotTypeBAF). The error message itself – "need finite 'ylim' values" – suggests that the plotting function is encountering some issues with the y-axis limits. This often happens when the data being plotted contains invalid values, such as NaN (Not a Number) or Inf (Infinity), which can mess up the plotting scale. It's like trying to draw a graph with points that are infinitely high or undefined; the software just doesn't know what to do!

This is a pretty common issue, especially when you're working with data that has gone through multiple processing steps, like you mentioned with your segmented exomes from CNVkit and mutations called by Mutect2. Data transformation, normalization, or even just the way the data is structured can sometimes lead to these NaN values. The good news is that while the plots might not render correctly, PureCN often still generates the important output files, like the _loh.csv file, which contains crucial information about loss of heterozygosity (LOH). But, the error prevents the program from completing normally, which is a problem if you have automated scripts running the analysis.

Diving into the Error Messages

Let's break down the error messages a little further to understand what's happening under the hood:

  • Error in plot.window(...) : need finite 'ylim' values: This is the core error. It means the plot.window function, which sets up the plotting area, is getting invalid values for the y-axis limits. This can happen if your log ratios are not properly formatted.
  • Calls: plotAbs ... .plotTypeBAF -> plot -> plot.default -> localWindow -> plot.window: This line traces the function calls, showing that the error occurs during the plotTypeBAF step, specifically within the plot function and eventually in plot.window.
  • Warning message: In plot.default(xLogRatio, logRatio$log.ratio, ylab = "Copy Number log-ratio", : NaNs produced: This warning message is crucial. It tells you that the plotting function encountered NaN values while trying to plot the log ratios, indicating a problem with your input data.
  • Execution halted: This is the final nail in the coffin. The program stops running because of the error.

Reproducing the Error: The Code Breakdown

You've provided the exact code you're using to run PureCN, which is super helpful for troubleshooting. Let's take a look at it:

Rscript /opt/PureCN/PureCN.R \
  --out . --seed 1234 \
  --alpha 0.005 --fun-segmentation Hclust \
  --genome hg38 --mapping-bias-file /mapping_bias_Exome_hg38.rds \
  --max-copy-number 8 --max-non-clonal 0.75 \
  --max-ploidy 4 --max-purity 0.99 --min-ploidy 1.4 \
  --min-purity 0.95 --model betabin --model-homozygous \
  --post-optimize --sampleid sampleA \
  --seg-file sampleA.call.seg --cores 8 \
  --tumor sampleA.cnr \
  --vcf sampleA.vcf.gz

This command looks pretty standard for running PureCN. You're specifying the output directory (--out .), setting a random seed (--seed 1234), providing segmentation and VCF files, and defining various parameters related to copy number calling, purity, and ploidy. However, the command itself is unlikely to be the direct cause of the plot.window error. The error is more likely due to issues within your input files or how those files were processed before being fed into PureCN. The most common culprit is usually the .cnr file or the seg file, which contain the log ratios and segment information, respectively.

Key Input Files

Let's pinpoint the important files that PureCN uses:

  • sampleA.cnr: This file is the most likely source of the problem. It contains the copy number log ratios for your tumor sample. Invalid values in this file (like NaN or Inf) will directly cause the plotting error.
  • sampleA.call.seg: This is the segmentation file. Although less likely to cause the specific error, any inconsistencies or errors in this file could also contribute to plotting issues.
  • sampleA.vcf.gz: Your VCF file, containing mutation data. While not directly involved in the plotting, errors in this file might indirectly affect the analysis or the creation of other files.

Troubleshooting Steps & Solutions

Alright, let's get down to the nitty-gritty and figure out how to fix this PureCN plotting issue. Here's a step-by-step guide:

1. Inspect Your Input Files

The .cnr file is your primary suspect. Open sampleA.cnr (or whatever your tumor file is called) in a text editor or use a tool like head or less in your terminal to examine the first few lines. Look for any NaN, Inf, or very large or small values in the log.ratio column. Any of these can trigger the plotting error.

  • Action: If you find NaN or Inf values, you'll need to figure out where they came from. The issue often comes from the previous steps, such as CNVkit. Check your CNVkit processing steps.

2. Check the CNVkit Output

Since you are using CNVkit to segment your exomes, the quality of these files is crucial. The .cnr file is derived from the CNVkit output, so the CNVkit processing steps are very important for debugging. Ensure that all the steps in your CNVkit workflow completed without errors. Review the CNVkit documentation and best practices to ensure you're using the recommended parameters and the most up-to-date version. Make sure to check the coverage depth and GC content bias normalization, and that the segmentation is performed correctly. If you're missing any steps, or if any step encounters errors, this can produce problematic log.ratio values. Consider re-running CNVkit with more stringent quality control steps to filter out problematic regions or samples.

3. Data Cleaning & Preprocessing

If you find invalid values in your .cnr file, you might need to clean the data before feeding it into PureCN. There are several ways to do this:

  • Option 1: Filter out problematic regions: You could filter out regions with NaN or Inf values using a script in R, Python, or even a simple awk command in the terminal. You would remove the rows from the .cnr file where the log ratio is invalid.
  • Option 2: Imputation: Consider replacing the invalid values with a sensible value, such as the mean or median of the surrounding regions. This is a bit more complex but might be necessary if you have a lot of missing data.

4. Adjust PureCN Parameters (If Appropriate)

Although it's less likely to directly fix the plotting error, you could try adjusting the PureCN parameters, specifically those related to copy number segmentation or modeling. For example, you could experiment with different segmentation methods (e.g., --fun-segmentation CBS instead of Hclust), or adjust the --alpha parameter. However, this is more of a workaround if you're unable to fix the root cause.

5. Consider a tryCatch Block (The Quick Fix)

If the plots aren't critical for your analysis and you just need PureCN to run to completion, you can implement a tryCatch block in your R script to gracefully handle the error. This will prevent your wrapper scripts from failing.

tryCatch({
  # Your PureCN code here
  PureCN::run_purecn(
    ..., # Your PureCN parameters
  )
}, error = function(e) {
  cat("An error occurred during PureCN processing:\n")
  print(e)
  # You can also add code to save the partial results or log the error
  # For example: write.csv(loh_results, file = "sampleA_partial_loh.csv")
  quit(status = 1) # Exit with an error code
})

This tryCatch block will catch any errors that occur during the execution of your PureCN code. It will print the error message and allow your script to continue running. Make sure you replace the ... with your actual PureCN parameters.

6. Software and Package Versions

Make sure that your R version and the PureCN package are up-to-date. Ensure you have the latest versions of any other relevant packages, like CNVkit if you are using it. Sometimes, package updates can resolve known bugs or compatibility issues.

Expected Behavior vs. Workarounds

Your expectations are spot on: you want PureCN to complete successfully, even if the plots don't render perfectly. While the ideal solution is to fix the underlying data issues and get the plots working, using a tryCatch block provides a practical workaround. It allows you to continue your analysis without the script failing.

Conclusion: Getting Your PureCN Workflow Back on Track

Alright, folks, we've covered a lot of ground! We've discussed the PureCN plotting error, how to reproduce it, and, most importantly, how to troubleshoot and fix it. Remember, the key is to examine your input files, especially the .cnr file, and identify and correct any invalid values. While a tryCatch block can be a lifesaver for ensuring your scripts run smoothly, addressing the root cause will give you more reliable and accurate results. By following these steps, you'll be well on your way to conquering this plotting hurdle and getting the most out of your PureCN analysis. Happy analyzing, and good luck!

If you have any further questions or if something isn't clear, don't hesitate to ask. Happy coding and happy analyzing, folks!