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Excel Causing Errors in Scientific Research Papers

Topic: Latest Science News
by Noel Diem | Aug 24 2016, 5:45pm CDT

Three different scientists, Mark Ziemann, Yotem Eren, and Assam El-Osta have said that Microsoft Excel has problems converting gene name. They have released a scientific article entitled “Gene name errors are widespread in the scientific literature." In the article's abstract section (which is basically a summary of the paper), they explain:

“The spreadsheet software Microsoft Excel, when used with default settings, is known to convert gene names to dates and floating-point numbers. A programmatic scan of leading genomics journals reveals that approximately one-fifth of papers with supplementary Excel gene lists contain erroneous gene name conversions.”

Of course, that might not be that surprising. Excel has problems because of the "gene symbols" that the scientists use as examples:

“For example, gene symbols such as SEPT2 (Septin 2) and MARCH1 [Membrane-Associated Ring Finger (C3HC4) 1, E3 Ubiquitin Protein Ligase] are converted by default to ‘2-Sep’ and ‘1-Mar’, respectively. Furthermore, RIKEN identifiers were described to be automatically converted to floating point numbers (i.e. from accession ‘2310009E13’ to ‘2.31E+13’). Since that report, we have uncovered further instances where gene symbols were converted to dates in supplementary data of recently published papers (e.g. ‘SEPT2’ converted to ‘2006/09/02’). This suggests that gene name errors continue to be a problem in supplementary files accompanying articles. Inadvertent gene symbol conversion is problematic because these supplementary files are an important resource in the genomics community that are frequently reused. Our aim here is to raise awareness of the problem.”

For the most part, the scientists really didn't have to write a paper about the problems that Microsoft Excel causes. An easier fix would be "to raise awareness of the problem" via Excel Uservoice or to actually reach out to Microsoft. Still, it is somewhat alarming to think that 20% of all scientific papers will have errors due to Excel. What would have truly been a marvel, however, would have been if the scientists had found a way to solve the problem.

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