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C3: An R package for cross-species compendium-based cell-type identification

Md Humayun Kabir, Djordje Djordjevic, Michael D. O’Connor, Joshua W. K. Ho
doi: https://doi.org/10.1101/267880
Md Humayun Kabir
1School of Medicine, Western Sydney University, Campbelltown, NSW, Australia
2Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
3Department of Computer Science and Engineering, University of Rajshahi, Bangladesh
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Djordje Djordjevic
2Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
4St. Vincent’s Clinical School, University of New South Wales, Sydney, NSW, Australia
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Michael D. O’Connor
1School of Medicine, Western Sydney University, Campbelltown, NSW, Australia
5Medical Sciences Research Group, Western Sydney University, Campbelltown, NSW, Australia
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Joshua W. K. Ho
2Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
4St. Vincent’s Clinical School, University of New South Wales, Sydney, NSW, Australia
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  • For correspondence: j.ho@victorchang.edu.au
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Abstract

Cell type identification from an unknown sample can often be done by comparing its gene expression profile against a gene expression database containing profiles of a large number of cell-types. This type of compendium-based cell-type identification strategy is particularly successful for human and mouse samples because a large volume of data exists for these organisms. However, such rich data repositories often do not exist for most non-model organisms. This makes transcriptome-based sample classification in these species challenging. We propose to overcome this challenge by performing a cross-species compendium comparison. The key is to utilise a recently published cross-species gene set analysis (XGSA) framework to correct for biases that may arise due to potentially complex homologous gene mapping between two species. The framework is implemented as an open source R package called C3. We have evaluated the performance of C3 using a variety of public data in NCBI Gene Expression Omnibus. We also compared the functionality and performance of C3 against some similar gene expression profile matching tools. Our evaluation shows that C3 is a simple and effective method for cell type identification. C3 is available at https://github.com/VCCRI/C3.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 19, 2018.
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C3: An R package for cross-species compendium-based cell-type identification
Md Humayun Kabir, Djordje Djordjevic, Michael D. O’Connor, Joshua W. K. Ho
bioRxiv 267880; doi: https://doi.org/10.1101/267880
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C3: An R package for cross-species compendium-based cell-type identification
Md Humayun Kabir, Djordje Djordjevic, Michael D. O’Connor, Joshua W. K. Ho
bioRxiv 267880; doi: https://doi.org/10.1101/267880

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