TangSoftwareLab / SynergyFinderR

SynergyFinder R package development
https://www.bioconductor.org/packages/release/bioc/html/synergyfinder.html
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Differences between SynergyFinderPlus ([www.synergyfinder.org](http://www.synergyfinder.org/)) and SynergyFinder2 (https://synergyfinder.fimm.fi/). #1

Open TangSoftwareLab opened 2 years ago

TangSoftwareLab commented 2 years ago

There are substantial differences between SynergyFinderPlus (www.synergyfinder.org) and SynergyFinder2 (https://synergyfinder.fimm.fi/). For assessing the degree of synergy for higher-order drug combinations, SynergyFinderPlus develops novel mathematical models for BLISS, LOEWE and ZIP, which are distinct from those developed in SynergyFinder2 (Table 1). In fact, we found that mathematical models used in SynergyFinder2 are incompatible with the assumptions of BLISS, LOEWE and ZIP. Therefore, it might be suboptimal to use SynergyFinder2 for the analysis of high-order drug combination data. Please find the detailed explanations as below, using the three-drug combination data as an example: image

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References: [1] SynergyFinderPlus website: www.synergyfinder.org; www.synergyfinderplus.org [2] SynergyFinderPlus R package: https://www.bioconductor.org/packages/release/bioc/html/synergyfinder.html [3] SynergyFinder2 website: www.synergyfinder.fimm.fi [4] SynergyFinderPlus publication: Zheng S., Wang W., Aldahdooh J., Malyutina A., Shadbahr T., Pessia A., Tang J. (2022). SynergyFinder Plus: towards a better interpretation and annotation of drug combination screening datasets. Genomics Proteomics Bioinformatics. https://doi.org/10.1016/j.gpb.2022.01.004. [5] SynergyFinder2 publication: Ianevski A, Giri, ZK, and Aittokallio T. (2020) SynergyFinder 2.0: visual analytics of multi-drug combination synergies. Nucleic Acids Res. 48(W1):W488-W493. doi: 10.1093/nar/gkaa216.
[6] Mathematical modelling of HSA, BLISS, LOEWE and ZIP: Yadav, B., Wennerberg, K., Aittokallio T., Tang J.
(2015) Searching for drug synergy in complex dose–response landscapes using an interaction potency model. Comput Struct Biotechnol J. 13:504-13. doi: 10.1016/j.csbj.2015.09.001
[7] SynergyFinder1 publication: Ianevski A., He L., Aittokallio T., Tang J. (2017) SynergyFinder: a web application for analyzing drug combination dose-response matrix data. Bioinformatics 33(15):2413-2415. He L., Kulesskiy E, Saarela J., Turunen L., Wennerberg, K., Aittokallio T., Tang J. (2018) Methods for high-throughput drug combination screening and synergy scoring. Methods Mol Biol. 1711:351-398. doi: 10.1007/978-1-4939-7493-1_17

Originally posted by @TangSoftwareLab in https://github.com/TangSoftwareLab/SynergyFinderWeb/discussions/1

IanevskiAleksandr commented 2 years ago

There is indeed a typo in the SynergyFinder 2.0 manuscript "-" sign should be "+" at the end of multi-drug combination Bliss synergy formula, but in the code it is correct. We will put the note on SynergyFinder v3 (that is accepted to NAR) that there is a typo in the SynergyFinder 2.0 manuscript in Bliss and ZIP equations, but the formula is (and was) correct on the website, so it doesn't affect any previous or future analysis.

For example, for 3 drug combination, we actually calculate Bliss as g123 = g1 · g2 · g3 in the code of SynergyFinder.Fimm.Fi website. Thus, for 3 drugs providing responses e.g. g1 = 35 %inhibition, g2 = 57 %inhibition, g3 = 44 %inhibition, we calculate Bliss effect as 100(1-(1-0.35)(1-0.57)(1-0.44)) = 84.348. This is exactly the same as 35+57+44 - (35x44)/100 - (57x44)/100 - (35x57)/100 + 35x44x57/10000 = 84.348. In addition, in our code implementation for ZIP, we first fit d-r curves for each observed row in 3d cube, and then run Bliss on those "fitted" data.

It is a pity that you are making such claims (and spending time, that you could spend on REAL research, on making such comparisons) without trying to contact us first, and without even trying to use the tool, otherwise, you would notice that calculations are correct, and we just have a typo in the manuscript.

TangSoftwareLab commented 1 year ago

More comments can be viewed at www.synergyfinder.org Posted here: On July 2022, the authors of SynergyFinder2 published ‘Correction to ‘SynergyFinder 2.0: visual analytics of multi-drug combination synergies’’ at https://doi.org/10.1093/nar/gkac552. It stated that “In the originally published version of this manuscript, there is an error in the Bliss and ZIP equations. There should be a ‘+’ sign instead of ‘-’, before the last term. However, the authors advise that the formulas are correct in the codes used for calculation on the website, so the error doesn’t affect any previous or future analysis with SynergyFinder.”

However, the statement was false. The sign before the last term should depend on the parity in the combination. If the number of drugs is odd, e.g. a 3-drug combination, then the sign should be ‘+’, as the authors corrected. However, if the number is even, e.g. a 4-drug combination, the sign should be ‘-’.

Furthermore, the erratum did not solve the issues concerning the Loewe model. If SynergyFinder3 continues to use the formula S_LOEWE=a/A+b/B to determine the Loewe synergy score, then it is still inconsistent with the definition of Loewe models. The problem of Loewe model may be inherent irrespective of the size of the combination, which may explain why the results between SynergyFinder⅔ and SynergyFinder+ are different, even for 2-drug combinations.

Reproducibility is a crucial issue in medical research, particularly in drug discovery. It is essential to provide mathematically sound models to avoid false interpretations of data. In conclusion, the mathematical models in SynergyFinder 2&3 contain severe flaws that require correction. Additionally, contrary to the authors' claims in the publications, we found that the source code for SynergyFinder 2 & 3 was not available. Without access to the source code, evaluating the reproducibility of the results becomes challenging. Given that there are over 400 citations of these two papers, it is crucial to inform the drug discovery community about the issues and urge them to reanalyze their datasets with the corrected models.