Brisbane plot

Brisbane plot: GWAS signal density plot

GWASLab can create the Brisbane plot (GWAS signal density plot). Brisbane plot is a scatter plot that shows the signal density (number of variants within the 500 Kb flanking region of the reference variant) for each variant, which is very useful for presenting the independent signals obtained from large-scale GWAS of complex traits. The signals are usually determined by other statistical methods such as conditional analysis.

.plot_mqq(mode="b")

mysumstats.plot_mqq(mode="b")

Note

To create Brisbane plot using this function, you just need to load the sumstats of independent signals. If you load the entire dataset, the plot will simply reflect the marker density for your sumstats. To investigate independent signals, please use other tools such as GCTA-COJO. GWASLab only calculates the density of all variants in the gl.Sumstats Object.

Options

Option	DataType	Description	Default
`mode`	`b`	specify Brisbane plot mode	-
`bwindowsizekb`	`int`	windowsize in kb (flanking region length on one side)	`100`

Example

Brisbane plot

See Brisbane plot

Calculate signal density

mysumstats.get_density(windowsizekb=100)

Or you can use .get_density() to just calculate the density.

Option	DataType	Description	Default
`windowsizekb`	`int`	window size for calculation of signal density. `DENSITY`	`100`

Calculate signal density

mysumstats.get_density(windowsizekb=100)

mysumstats.data
    SNPID   CHR POS P   STATUS  DENSITY
0   rs2710888   1   959842  2.190000e-57    9999999 1
1   rs3934834   1   1005806 2.440000e-29    9999999 1
2   rs182532    1   1287040 1.250000e-18    9999999 1
3   rs17160669  1   1305561 1.480000e-28    9999999 1
4   rs9660106   1   1797947 1.860000e-12    9999999 0
... ... ... ... ... ... ...
12106   rs9628283   22  50540766    5.130000e-15    9999999 1
12107   rs28642259  22  50785718    1.140000e-13    9999999 1
12108   rs11555194  22  50876662    2.000000e-15    9999999 2
12109   rs762669    22  50943423    3.000000e-30    9999999 1
12110   rs9628185   22  51109992    5.430000e-12    9999999 0

Reference

Citation for Brisbane plot

Yengo, L., Vedantam, S., Marouli, E., Sidorenko, J., Bartell, E., Sakaue, S., ... & Lee, J. Y. (2022). A saturated map of common genetic variants associated with human height. Nature, 1-16.