Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets
Mass cytometry (CyTOF) is a technology that has revolutionised single-cell biology. By detecting over 40 proteins on millions of single cells, CyTOF allows the characterisation of cell subpopulations in unprecedented detail. However, most CyTOF studies require the integration of data from multiple C...
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2020-09-01
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| Online Access: | https://elifesciences.org/articles/59630 |
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doaj-d0dba3d62f0f482da6cbe72b34dd4ac22021-05-05T21:29:07ZengeLife Sciences Publications LtdeLife2050-084X2020-09-01910.7554/eLife.59630Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasetsMarie Trussart0https://orcid.org/0000-0002-7258-7272Charis E Teh1https://orcid.org/0000-0002-9745-2876Tania Tan2Lawrence Leong3Daniel HD Gray4https://orcid.org/0000-0002-8457-8242Terence P Speed5https://orcid.org/0000-0002-5403-7998Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Australia; School of Mathematics and Statistics, The University of Melbourne, Melbourne, AustraliaThe Walter and Eliza Hall Institute of Medical Research, Parkville, Australia; Department of Medical Biology, The University of Melbourne, Parkville, AustraliaThe Walter and Eliza Hall Institute of Medical Research, Parkville, Australia; Department of Medical Biology, The University of Melbourne, Parkville, AustraliaBioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Australia; School of Mathematics and Statistics, The University of Melbourne, Melbourne, AustraliaThe Walter and Eliza Hall Institute of Medical Research, Parkville, Australia; Department of Medical Biology, The University of Melbourne, Parkville, AustraliaBioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Australia; School of Mathematics and Statistics, The University of Melbourne, Melbourne, AustraliaMass cytometry (CyTOF) is a technology that has revolutionised single-cell biology. By detecting over 40 proteins on millions of single cells, CyTOF allows the characterisation of cell subpopulations in unprecedented detail. However, most CyTOF studies require the integration of data from multiple CyTOF batches usually acquired on different days and possibly at different sites. To date, the integration of CyTOF datasets remains a challenge due to technical differences arising in multiple batches. To overcome this limitation, we developed an approach called CytofRUV for analysing multiple CyTOF batches, which includes an R-Shiny application with diagnostic plots. CytofRUV can correct for batch effects and integrate data from large numbers of patients and conditions across batches, to confidently compare cellular changes and correlate these with clinically relevant outcomes.https://elifesciences.org/articles/59630peripheral blood mononuclear cellchronic lymphocytic leukaemia patientsproteins |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Marie Trussart Charis E Teh Tania Tan Lawrence Leong Daniel HD Gray Terence P Speed |
| spellingShingle |
Marie Trussart Charis E Teh Tania Tan Lawrence Leong Daniel HD Gray Terence P Speed Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets eLife peripheral blood mononuclear cell chronic lymphocytic leukaemia patients proteins |
| author_facet |
Marie Trussart Charis E Teh Tania Tan Lawrence Leong Daniel HD Gray Terence P Speed |
| author_sort |
Marie Trussart |
| title |
Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets |
| title_short |
Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets |
| title_full |
Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets |
| title_fullStr |
Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets |
| title_full_unstemmed |
Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets |
| title_sort |
removing unwanted variation with cytofruv to integrate multiple cytof datasets |
| publisher |
eLife Sciences Publications Ltd |
| series |
eLife |
| issn |
2050-084X |
| publishDate |
2020-09-01 |
| description |
Mass cytometry (CyTOF) is a technology that has revolutionised single-cell biology. By detecting over 40 proteins on millions of single cells, CyTOF allows the characterisation of cell subpopulations in unprecedented detail. However, most CyTOF studies require the integration of data from multiple CyTOF batches usually acquired on different days and possibly at different sites. To date, the integration of CyTOF datasets remains a challenge due to technical differences arising in multiple batches. To overcome this limitation, we developed an approach called CytofRUV for analysing multiple CyTOF batches, which includes an R-Shiny application with diagnostic plots. CytofRUV can correct for batch effects and integrate data from large numbers of patients and conditions across batches, to confidently compare cellular changes and correlate these with clinically relevant outcomes. |
| topic |
peripheral blood mononuclear cell chronic lymphocytic leukaemia patients proteins |
| url |
https://elifesciences.org/articles/59630 |
| work_keys_str_mv |
AT marietrussart removingunwantedvariationwithcytofruvtointegratemultiplecytofdatasets AT chariseteh removingunwantedvariationwithcytofruvtointegratemultiplecytofdatasets AT taniatan removingunwantedvariationwithcytofruvtointegratemultiplecytofdatasets AT lawrenceleong removingunwantedvariationwithcytofruvtointegratemultiplecytofdatasets AT danielhdgray removingunwantedvariationwithcytofruvtointegratemultiplecytofdatasets AT terencepspeed removingunwantedvariationwithcytofruvtointegratemultiplecytofdatasets |
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