text: user12245: Just wondering whether anyone can point me to a research paper which describes how the scoring values are generated by the Bruker software for species identification of bacteria in MALDI-TOF MS. For example, there are countless papers describing the Bruker output score as green (species-level confidence), yellow (genus-level), or red (neither species- nor genus-level confidence). However, none of the papers that I see are discussing how these numbers are actually calculated within the Bruker system. Even the Bruker brochure glosses over the point: "After the acquisition of the spectral data has been completed, a report is generated. The result for each sample is clearly listed under ‘Organism (best match)’ accompanied by the resulting score and an appropriate ‘traffic light’ color scheme." Can anyone point me in the direction of a paper or at least some online information such as wikipedia describing how Bruker came up with these numbers? It's not just an arbitrary number, right?
  Another generic description of the scores is in this presentation: "Higher the log (score), higher the similarity between mass spectrum of isolate & the database entry in the reference library."
  
  user12245: 
  For identification scoring, the software correlates signal
  intensities of matched signals of mass spectra. The three scores
  obtained from such a procedure are multiplied and normalized to a
  value of 1,000 and its common logarithm. Log scores over 2 are
  considered as reliable identification of a bacterial species (Table
  4), whereas log scores over 1.7 generally indicate reliable
  identification of bacterial genera. Log scores of 3 are obtained when
  spectra are matched with themselves.
  
  Sauer, S., Freiwald, A., Maier, T., Kube, M., Reinhardt, R., Kostrzewa, M., & Geider, K. (2008). Classification and identification of bacteria by mass spectrometry and
  computational analysis. PloS one, 3(7), e2843.
  Going further, from a random thread on ResearchGate:
  https://www.researchgate.net/post/Does_anyone_know_how_is_the_p-value_calculated_by_Bruker_Biotyper_during_MALDI-MS_fingerprinting_of_bacteria
  
  Number of peaks matched in your unknown sample divided by the number
  of peaks in the unknown sample, this is given a score (out of 10)
  Number of peaks matched in your unknown sample divided by the number
  of peaks in the reference sample, this is given a score (out of 10)
  Score of relative intensities of matching peaks (out of 10)
  Total score out of 1000
  Log10 score out of 3
  There is no relationship of the score with a p-value nor you can
  calculate the statistics because the bruker database is not open and
  you can not know the values for what the score was calculated to do
  the statistical analysis
  
  
original_text: 12245: <p>Just wondering whether anyone can point me to a research paper which describes how the scoring values are generated by the Bruker software for species identification of bacteria in MALDI-TOF MS. For example, there are countless papers describing the Bruker output score as green (species-level confidence), yellow (genus-level), or red (neither species- nor genus-level confidence). However, none of the papers that I see are discussing how these numbers are actually calculated within the Bruker system. Even the <a href="https://www.bruker.com/en/products-and-solutions/microbiology-and-diagnostics/microbial-identification/_jcr_content/root/contentpar/linklist.download-asset.pdf/primarylist/item0/1884563-brochure-maldi-biotyper-ruo-gp-bruker-md-12-2020.pdf" rel="nofollow noreferrer">Bruker brochure</a> glosses over the point: &quot;After the acquisition of the spectral data has been completed, a report is generated. The result for each sample is clearly listed under ‘Organism (best match)’ accompanied by the resulting score and an appropriate ‘traffic light’ color scheme.&quot; Can anyone point me in the direction of a paper or at least some online information such as wikipedia describing how Bruker came up with these numbers? It's not just an arbitrary number, right?</p>
  <p>Another generic description of the scores is in <a href="https://idmicro.files.wordpress.com/2020/06/maldi-tof-elias-16jun2020.pdf" rel="nofollow noreferrer">this presentation</a>: &quot;Higher the log (score), higher the similarity between mass spectrum of isolate &amp; the database entry in the reference library.&quot;</p>
   12245: <blockquote>
  <p>For identification scoring, the software correlates signal
  intensities of matched signals of mass spectra. The three scores
  obtained from such a procedure are multiplied and normalized to a
  value of 1,000 and its common logarithm. Log scores over 2 are
  considered as reliable identification of a bacterial species (Table
  4), whereas log scores over 1.7 generally indicate reliable
  identification of bacterial genera. Log scores of 3 are obtained when
  spectra are matched with themselves.</p>
  </blockquote>
  <p>Sauer, S., Freiwald, A., Maier, T., Kube, M., Reinhardt, R., Kostrzewa, M., &amp; Geider, K. (2008). Classification and identification of bacteria by mass spectrometry and
  computational analysis. <em>PloS one, 3</em>(7), e2843.</p>
  <p>Going further, from a random thread on ResearchGate:</p>
  <p><a href="https://www.researchgate.net/post/Does_anyone_know_how_is_the_p-value_calculated_by_Bruker_Biotyper_during_MALDI-MS_fingerprinting_of_bacteria" rel="nofollow noreferrer">https://www.researchgate.net/post/Does_anyone_know_how_is_the_p-value_calculated_by_Bruker_Biotyper_during_MALDI-MS_fingerprinting_of_bacteria</a></p>
  <blockquote>
  <p>Number of peaks matched in your unknown sample divided by the number
  of peaks in the unknown sample, this is given a score (out of 10)</p>
  <p>Number of peaks matched in your unknown sample divided by the number
  of peaks in the reference sample, this is given a score (out of 10)</p>
  <p>Score of relative intensities of matching peaks (out of 10)</p>
  <p>Total score out of 1000</p>
  <p>Log10 score out of 3</p>
  <p>There is no relationship of the score with a p-value nor you can
  calculate the statistics because the bruker database is not open and
  you can not know the values for what the score was calculated to do
  the statistical analysis</p>
  </blockquote>
  