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bioRxiv · 10.1101/237214

Robust expression variability testing reveals heterogeneous T cell responses

Eling, N.·Richard, A. C.·Richardson, S.·Marioni, J. C.·Vallejos, C. A.
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Abstract

Cell-to-cell transcriptional variability in otherwise homogeneous cell populations plays a crucial role in tissue function and development. Single-cell RNA sequencing can characterise this variability in a transcriptome-wide manner. However, technical variation and the confounding between variability and mean expression estimates hinders meaningful comparison of expression variability between cell populations. To address this problem, we introduce a novel analysis approach that extends the BASiCS statistical framework to derive a residual measure of variability that is not confounded by mean expression. Moreover, we introduce a new and robust procedure for quantifying technical noise in experiments where technical spike-in molecules are not available. We illustrate how our method provides biological insight into the dynamics of cell-to-cell expression variability, highlighting a synchronisation of the translational machinery in immune cells upon activation. Additionally, our approach identifies new patterns of variability across CD4+ T cell differentiation.

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Eling, N., Richard, A. C., Richardson, S., Marioni, J. C., Vallejos, C. A.. 2017-12-21. Robust expression variability testing reveals heterogeneous T cell responses. https://doi.org/10.1101/237214

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