Dataset Information

Mistaken identifiers: gene name errors can be introduced inadvertently when using Excel in bioinformatics.

ABSTRACT:

Background

When processing microarray data sets, we recently noticed that some gene names were being changed inadvertently to non-gene names.

Results

A little detective work traced the problem to default date format conversions and floating-point format conversions in the very useful Excel program package. The date conversions affect at least 30 gene names; the floating-point conversions affect at least 2,000 if Riken identifiers are included. These conversions are irreversible; the original gene names cannot be recovered.

Conclusions

Users of Excel for analyses involving gene names should be aware of this problem, which can cause genes, including medically important ones, to be lost from view and which has contaminated even carefully curated public databases. We provide work-arounds and scripts for circumventing the problem.

SUBMITTER: Zeeberg BR

PROVIDER: S-EPMC459209 | biostudies-literature | 2004 Jun

REPOSITORIES: biostudies-literature

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Publications

Mistaken identifiers: gene name errors can be introduced inadvertently when using Excel in bioinformatics.

Zeeberg Barry R BR Riss Joseph J Kane David W DW Bussey Kimberly J KJ Uchio Edward E Linehan W Marston WM Barrett J Carl JC Weinstein John N JN

BMC bioinformatics 20040623

<h4>Background</h4>When processing microarray data sets, we recently noticed that some gene names were being changed inadvertently to non-gene names.<h4>Results</h4>A little detective work traced the problem to default date format conversions and floating-point format conversions in the very useful Excel program package. The date conversions affect at least 30 gene names; the floating-point conversions affect at least 2,000 if Riken identifiers are included. These conversions are irreversible; t ...[more]

PMID: 15214961

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Project description:BackgroundAccuracy of the data extracted from two-dimensional confocal images is limited due to experimental errors that arise in course of confocal scanning. The common way to reduce the noise in images is sequential scanning of the same specimen several times with the subsequent averaging of multiple frames. Attempts to increase the dynamical range of an image by setting too high values of microscope PMT parameters may cause clipping of single frames and introduce errors into the data extracted from the averaged images. For the estimation and correction of this kind of errors a method based on censoring technique (Myasnikova et al., 2009) is used. However, the method requires the availability of all the confocal scans along with the averaged image, which is normally not provided by the standard scanning procedure.ResultsTo predict error size in the data extracted from the averaged image we developed a regression system. The system is trained on the learning sample composed of images obtained from three different microscopes at different combinations of PMT parameters, and for each image all the scans are saved. The system demonstrates high prediction accuracy and was applied for correction of errors in the data on segmentation gene expression in Drosophila blastoderm stored in the FlyEx database (http://urchin.spbcas.ru/flyex/, http://flyex.uchicago.edu/flyex/). The prediction method is realized as a software tool CorrectPattern freely available at http://urchin.spbcas.ru/asp/2011/emm/.ConclusionsWe created a regression system and software to predict the magnitude of errors in the data obtained from a confocal image based on information about microscope parameters used for the image acquisition. An important advantage of the developed prediction system is the possibility to accurately correct the errors in data obtained from strongly clipped images, thereby allowing to obtain images of the higher dynamical range and thus to extract more detailed quantitative information from them.

Dataset Information

Mistaken identifiers: gene name errors can be introduced inadvertently when using Excel in bioinformatics.

Background

Results

Conclusions

Publications

Mistaken identifiers: gene name errors can be introduced inadvertently when using Excel in bioinformatics.

Similar Datasets

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