Columns:

Format

A 112 x 11 numeric array

Details

e11 e13 e15 e18 e21 p0 p7 p14 a class1 class2

  • e11, an ebryonic timepoint from the original data with the number corresponding to the day

  • e13, an ebryonic timepoint from the original data with the number corresponding to the day

  • e15, an ebryonic timepoint from the original data with the number corresponding to the day

  • e18, an ebryonic timepoint from the original data with the number corresponding to the day

  • e21, an ebryonic timepoint from the original data with the number corresponding to the day

  • p0, a postnatal timpoint from the original data with the number corresponding to the day

  • p7, a postnatal timpoint from the original data with the number corresponding to the day

  • p14, a postnatal timpoint from the original data with the number corresponding to the day

  • a, a postnatal timpoint from the original data. It is equivalent to p90.

  • class1, is the high-level class: its range is 1:4

  • class2, breaks down the high-level classes, so its range is 1:14

Rows: Each case is a gene (or gene family?) And each cell is the gene expression level for that gene at time t, averaging a few measured values and normalizing using the maximum expression value for that gene.

Reference (available on the web at pnas.org): Large-scale temporal gene expression mapping of central nervous system development by X. Wen, S. Fuhrman, G. S. Michaels, D. B. Carr, S. Smith, J. L. Barker, R. Somogyi in the Proceedings of the National Academy of Science, Vol 95, pp. 334-339, January 1998

References

https://www.pnas.org

Examples


head(ratcns)
#>    e11  e13  e15  e18  e21   p0   p7  p14    a class1 class2
#> 1 1.00 0.20 0.31 0.24 0.40 0.27 0.19 0.05 0.00      1      1
#> 2 1.00 0.77 0.21 0.37 0.40 0.44 0.68 0.69 0.47      1      1
#> 3 0.49 0.63 1.00 0.54 0.29 0.22 0.10 0.10 0.08      1      1
#> 4 0.02 0.27 0.82 0.87 0.88 0.79 0.76 0.84 1.00      1      1
#> 5 0.36 0.62 0.70 0.81 0.97 0.96 0.78 0.78 1.00      1      1
#> 6 0.06 0.17 0.53 0.96 1.00 0.90 0.51 0.42 0.40      1      1
animate_xy(ratcns[, 1:8], col = ratcns[, 10])
#> Converting input data to the required matrix format.
#> Using half_range 1.7