text: user10553: I have fasta files with multiple sequences. They are reads that mapped to the genome outside of  probe-targeted regions.
  From a quick perusal, they appear to be repetitive and have low complexity. Is there a way I can quantify their complexity and use that as an explanation as to why those regions were mapped to?
  
  user9972: "Complexity" is also known as entropy. A quick and dirty way is to use a file compression utility - zip will get good compression for a repetitive sequence.
  You can also look at the k-mer distribution for some suitable k: in a repetitive sequence it will be biased. Here is a tool that give a local plot: https://rdrr.io/github/vsbuffalo/qrqc/man/kmerEntropyPlot.html
  
  user6251: Use Picard EstimateLibraryComplexity.
  From the docs:
  
  Estimates the numbers of unique molecules in a sequencing library.
  
  java -jar picard.jar EstimateLibraryComplexity \
       I=input.bam \
       O=est_lib_complex_metrics.txt
  
  
original_text: 10553: <p>I have fasta files with multiple sequences. They are reads that mapped to the genome outside of  probe-targeted regions.
  From a quick perusal, they appear to be repetitive and have low complexity. Is there a way I can quantify their complexity and use that as an explanation as to why those regions were mapped to?</p>
   9972: <p>&quot;Complexity&quot; is also known as entropy. A quick and dirty way is to use a file compression utility - zip will get good compression for a repetitive sequence.</p>
  <p>You can also look at the k-mer distribution for some suitable k: in a repetitive sequence it will be biased. Here is a tool that give a local plot: <a href="https://rdrr.io/github/vsbuffalo/qrqc/man/kmerEntropyPlot.html" rel="nofollow noreferrer">https://rdrr.io/github/vsbuffalo/qrqc/man/kmerEntropyPlot.html</a></p>
   6251: <p>Use Picard <a href="http://broadinstitute.github.io/picard/command-line-overview.html" rel="nofollow noreferrer">EstimateLibraryComplexity</a>.</p>
  <p>From the docs:</p>
  <blockquote>
  <p>Estimates the numbers of unique molecules in a sequencing library.</p>
  </blockquote>
  <pre><code>java -jar picard.jar EstimateLibraryComplexity \
       I=input.bam \
       O=est_lib_complex_metrics.txt
  </code></pre>
  