1.2 Million Identical Warnings is a bit Verbose

[bklein345]

• [x] Search whether this issue (or a similar issue) has been solved before using the search tab above. Link the previous issue if appropriate below.

• [x] Paste your deepTools version (deeptools --version) and your python version (python --version) below. deeptools 3.3.2 Python 3.6.0

• [x] Paste the full deepTools command that produces the issue below (ignore if you simply spotted the issue in the code/documentation). computeGCBias
  --bamfile $bam
  --effectiveGenomeSize $genome_size
  --genome $fasta_2bit
  --GCbiasFrequenciesFile $output
  --blackListFileName $blacklist_bed
  --verbose
  --biasPlot $plot_out
  --regionSize $region_size

• [x] Paste the output printed on screen from the command that produces the issue below (ignore if you simply spotted the issue in the code/documentation). WARNING: too many NNNs present in 1:0-176 WARNING: too many NNNs present in 1:62-238 WARNING: too many NNNs present in 1:124-300 WARNING: too many NNNs present in 1:186-362 WARNING: too many NNNs present in 1:248-424 WARNING: too many NNNs present in 1:310-486 WARNING: too many NNNs present in 1:372-548 .... Repeated ~1.2million times.

[dpryan79]

computeGCBias is fairly deprecated, are you sure you need to run it at all with modern data?

[bklein345]

I was under the impression that I would need to account for GC bias in order to achieve accurate measurements of ploidy. The manuscript by Benjamini proposed a reasonable means to do so, and I assumed that was implemented in this tool here. I'm curious what you mean when you ask if this is necessary with modern data. Does modern data not suffer from GC bias? Furthermore, if the tool is deprecated, do you have suggestions for alternatives?

[dpryan79]

The tool is deprecated only because modern data rarely suffers from any major GC bias. Otherwise it should work fine.

Sent from my iPhone

On 20. Feb 2020, at 16:40, bklein345 [email protected] wrote:

 I was under the impression that I would need to account for GC bias in order to achieve accurate measurements of ploidy. The manuscript by Benjamini proposed a reasonable means to do so, and I assumed that was implemented in this tool here. I'm curious what you mean when you ask if this is necessary with modern data. Does modern data not suffer from GC bias? Furthermore, if the tool is deprecated, do you have suggestions for alternatives?

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