cglasso (version 1.1.2)

MKMEP: Megakaryocyte-Erythroid Progenitors

Description

In a study about the formation of blood cells, Psaila and others (2016) have recently identified three distinct subpopulations of cells, which are all derived from hematopoietic stem cells through cell differentiation. One of these sub-populations, denoted by MK-MEP, is a previously unknown, rare population of cells that are bipotent but primarily generate megakaryocytic progeny.

‘MKMEP’ in an object of class ‘datacggm’ containing a subset of the data available from Psaila and others (2016).

Multiplex RT-qPCR is used to profile 63 genes and 48 single human MK-MEP cells. RT-qPCR data are typically right-censored with a limit of detection fixed by the manufacturer to 40. Raw data have been mean normalized using the method proposed in Pipelers and others (2017). See Section 5 in Augugliaro and others (2018) for more details.

Usage

data("MKMEP")

References

Augugliaro, L., Abbruzzo, A. and Vinciotti, V. (2018). \(\ell_1\)-Penalized gaussian graphical model. Biostatistics (to appear).

Pipelers, P., Clement, L., Vynck, M., Hellemans, J., Vandesompele, J. and Thas, O. (2017). A unified censored normal regression model for qPCR differential gene expression analysis. PLoS One 12, e0182832.

Psaila, B., Barkas, N., Iskander, D., Roy, A., Anderson, S., Ashley, N., Caputo, V. S., Lichtenberg, J., Loaiza, S., Bodine, D. M. and others. (2016). Single-cell profiling of human megakaryocyte-erythroid progenitors identifies distinct megakaryocyte and erythroid differentiation pathways. Genome Biology 17, 83--102.

See Also

cglasso, to_graph, and the method functions summary, coef, plot, aic, bic and ebic.

Examples

# NOT RUN {
data("MKMEP")
out_cglasso <- cglasso(MKMEP, pendiag = TRUE, nrho = 200L, rho.min.ratio = 0.35)
out_ebic <- ebic(out_cglasso)
plot(out_ebic, type = "l")

out_graph <- to_graph(out_cglasso, nrho = which.min(out_ebic$value_gof))
V(out_graph)$color <- "white"
V(out_graph)$frame.color <- NA
V(out_graph)$label.color <- "black"
E(out_graph)$color <- "gray75"

plot(out_graph, layout = layout_with_lgl(out_graph))
mtext(text = "Megakaryocytic MEP population", cex = 1.5, line = 1)
# }