Gene name errors are widespread in the scientific literature
© The Author(s). 2016
Published: 23 August 2016
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.
KeywordsMicrosoft Excel Gene symbol Supplementary data
The problem of Excel software (Microsoft Corp., Redmond, WA, USA) inadvertently converting gene symbols to dates and floating-point numbers was originally described in 2004 . 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.
We downloaded and screened supplementary files from 18 journals published between 2005 and 2015 using a suite of shell scripts. Excel files (.xls and.xlsx suffixes) were converted to tabular separated files (tsv) with ssconvert (v1.12.9). Each sheet within the Excel file was converted to a separate tsv file. Each column of data in the tsv file was screened for the presence of gene symbols. If the first 20 rows of a column contained five or more gene symbols, then it was suspected to be a list of gene symbols, and then a regular expression (regex) search of the entire column was applied to identify gene symbol errors. Official gene symbols from Ensembl version 82, accessed November 2015, were obtained for Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Danio rerio, Escherichia coli, Gallus gallus, Homo sapiens, Mus musculus, Oryza sativa and Saccharomyces cerevisiae . The regex search used was similar to that described previously by Zeeberg and colleagues , with the added screen for dates in other formats (e.g. DD/MM/YY and MM-DD-YY). To expedite analysis of supplementary files from multi-disciplinary journals, we limited the articles screened to those that have the keyword ‘genome’ in the title or abstract (Science, Nature and PLoS One). Excel files (.xls and.xlsx) deposited in NCBI Gene Expression Omnibus (GEO)  were also screened in the same way (files released 2005–2015). All URLs screened, results and scripts used in this study are currently available at SourceForge (https://sourceforge.net/projects/genenameerrorsscreen/). Scripts were run on Ubuntu v14.04 LTS with GNU bash, version 4.3.11. These findings were verified manually by downloading and checking Excel files from every paper and GEO file suspected to include gene name errors.
Results of the systematic screen of supplementary Excel files for gene name conversion errors
Number of Excel files screened
Number of gene lists found
Number of papers with gene lists
Number of supplementary files affected
Number of papers affected
Number of gene names converted
Nucleic Acids Res
Hum Mol Genet
PLoS Comput Biol
Mol Biol Evol
Genome Biol Evol
Automatic conversion of gene symbols to dates and floating-point numbers is a problematic feature of Excel software. The description of this problem and workarounds were first highlighted over a decade ago —nevertheless, we find that these errors continue to pervade supplementary files in the scientific literature. To date, there is no way to permanently deactivate automatic conversion to dates in MS Excel and other spreadsheet software such as LibreOffice Calc or Apache OpenOffice Calc. We note, however, that the spreadsheet program Google Sheets did not convert any gene names to dates or numbers when typed or pasted; notably, when these sheets were later reopened with Excel, LibreOffice Calc or OpenOffice Calc, gene symbols such as SEPT1 and MARCH1 were protected from date conversion.
For reviewers and editorial staff, the kind of errors we describe can be spotted by copying the column of gene names and pasting it into a new sheet, and then sorting the column. Any gene symbols converted to dates will appear as numbers at the top of the column. Journals might wish to adapt our supplied scripts to screen for gene name errors in supplementary files or have researchers do this before submission. In the 987 supplementary files containing gene name errors identified here, 166 files did not contain any other identifying information such as accession numbers or genomic coordinates that could be used to infer the original gene names. We recommend that these 166 files be corrected (listed in Table S1 in Additional file 1). We also recorded several cases where gene name errors were located in the first few lines of a file—this suggests to us that these files were not properly reviewed before publication.
Finally, as our scripts focused on screening vertical lists of genes, we might have missed instances of gene symbol errors in horizontal gene lists. There are undoubtedly many more instances of gene name errors in journals outside of the 18 we screened here. In this study, we were not able to programmatically access pay-walled supplementary files. We recommend publishers allow open access to supplementary materials, as exemplified by Science, Nature and Nature Genetics. In conclusion, we show that inadvertent gene name conversion errors persist in the scientific literature, but these should be easy to avoid if researchers, reviewers, editorial staff and database curators remain vigilant.
Gene Expression Omnibus
journal impact factor
We thank A. Kaspi and H. Rafehi for discussions on this paper, and R. Lazarus for informatics support.
AEO is supported by the National Health and Medical Research Council (NHMRC GNT0526681, GNT1048377); Juvenile Diabetes Research Foundation (JDRF 5-2008-298, 27-2012-451); Diabetes Australia Research Trust (DART); Victorian Government’s Operational Infrastructure Support program (in part).
Availability of data and materials
Bash scripts, URLs and output data supporting the conclusions of this article are available in the SourceForge repository (https://sourceforge.net/projects/genenameerrorsscreen/).
MZ, YE and AEO designed and conducted analyses and co-wrote the manuscript. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Ethics approval and consent to participate
No ethical approval was required.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Zeeberg BR, Riss J, Kane DW, Bussey KJ, Uchio E, Linehan WM, et al. Mistaken identifiers: gene name errors can be introduced inadvertently when using Excel in bioinformatics. BMC Bioinformatics. 2004;5:80.View ArticlePubMedPubMed CentralGoogle Scholar
- Smedley D, Haider S, Durinck S, Pandini L, Provero P, Allen J, et al. The BioMart community portal: an innovative alternative to large, centralized data repositories. Nucleic Acids Res. 2015;1:W589–98.View ArticleGoogle Scholar
- Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, et al. NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res. 2013;41:D991–5.View ArticlePubMedGoogle Scholar