Open Access

Gene name errors are widespread in the scientific literature

Genome Biology201617:177

https://doi.org/10.1186/s13059-016-1044-7

Published: 23 August 2016

Abstract

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.

Keywords

Microsoft 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 [1]. 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 [2]. The regex search used was similar to that described previously by Zeeberg and colleagues [1], 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) [3] 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.

Supplementary files in Excel format from 18 journals published from 2005 to 2015 were programmatically screened for the presence of gene name errors. In total, we screened 35,175 supplementary Excel files, finding 7467 gene lists attached to 3597 published papers. We downloaded and opened each file with putative gene name errors. Ten false-positive cases were identified. We confirmed gene name errors in 987 supplementary files from 704 published articles (Table 1; for individual listings, see Table S1 in Additional file 1). Of the selected journals, the proportion of published articles with Excel files containing gene lists that are affected by gene name errors is 19.6 %. Of the journals selected, Molecular Biology and Evolution, Bioinformatics, DNA Research and Genome Biology and Evolution exhibited the lowest proportion (<10 %) of affected papers (Fig. 1a). Journals that had the highest proportion of papers with affected supplementary files were Nucleic Acids Research, Genome Biology, Nature Genetics, Genome Research, Genes and Development and Nature (>20 %). There was a positive correlation between 2015 journal impact factor (JIF) and the proportion of supplementary gene lists affected (Spearman rho = 0.52, two-sided p value = 0.03), which might be due to larger and more numerous datasets accompanying high-JIF papers. Of note, BMC Bioinformatics, the forum where the Excel gene name issue was originally reported [1], continues to suffer, with gene name errors present in 13.8 % of papers with Excel gene lists. Indeed, the number of papers with gene name errors continues to be a problem (Fig. 1b). Linear-regression estimates show gene name errors in supplementary files have increased at an annual rate of 15 % over the past five years, outpacing the increase in published papers (3.8 % per year). We screened 4321 Excel files deposited to NCBI GEO [3], identifying 574 files with gene lists and finding that 228 (39.7 %) of these contain gene name errors. These are listed in Table S1 in Additional file 1.
Table 1

Results of the systematic screen of supplementary Excel files for gene name conversion errors

Journala

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

PLoS One

7783

2202

994

220

170

4240

BMC Genomics

11464

1650

801

218

158

4932

Genome Res

2607

580

251

114

68

3180

Nucleic Acids Res

2117

540

315

88

67

1661

Genome Biol

2678

664

257

97

63

1878

Genes Dev

932

395

190

75

55

1593

Hum Mol Genet

980

372

168

48

27

1724

Nature

482

150

74

27

23

1375

BMC Bioinformatics

1790

235

152

26

21

534

RNA

569

127

77

20

15

1341

Nat Genet

264

70

37

12

9

178

Bioinformatics

731

112

67

11

6

339

PLoS Comput Biol

177

79

32

6

6

46

PLoS Biol

143

54

29

7

5

206

Mol Biol Evol

995

112

79

7

4

56

Science

172

36

19

7

3

451

Genome Biol Evol

490

32

25

2

2

121

DNA Res

801

57

30

2

2

6

Total

35175

7467

3597

987

704

23861

aThe 18 journals investigated are ordered by the number of papers affected by gene name conversion errors

Fig. 1

Prevalence of gene name errors in supplementary Excel files. a Percentage of published papers with supplementary gene lists in Excel files affected by gene name errors. b Increase in gene name errors by year

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 [1]—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.

Abbreviations

GEO: 

Gene Expression Omnibus

JIF: 

journal impact factor

Declarations

Acknowledgements

We thank A. Kaspi and H. Rafehi for discussions on this paper, and R. Lazarus for informatics support.

Funding

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/).

Authors’ contributions

MZ, YE and AEO designed and conducted analyses and co-wrote the manuscript. All authors read and approved the final manuscript.

Competing interests

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.

Authors’ Affiliations

(1)
Baker IDI Heart & Diabetes Institute, The Alfred Medical Research and Education Precinct
(2)
Faculty of Engineering, Monash University
(3)
Central Clinical School, Faculty of Medicine, Monash University

References

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Copyright

© The Author(s). 2016

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