What does UNICS do?
This web app helps you
decide whether it is best to use pool- or individual-sequencing
and compute the standard error of allele frequency estimates of future pool-sequencing experiments based on user-defined parameters (number of individuals pooled, allele frequencies, amount of unequal individual contributions to the DNA pool, mean and overdispersion in sequencing depth). Note that we assume that sequencing budget is fixed so that the precision of allele frequency estimates is the only parameter determining the choice between individual- vs pool-sequencing.
How to use UNICS?
Default parameters (e.g. average individual sequencing depth, number of individually barcoded samples, etc.) can be changed using the "show options" button below. The four top graphs
compare the performance of pool- vs individual-based sequencing
. Individual-sequencing is preferable ("Ind-seq preferable") whenever the curve is above one (i.e. when the standard errors of allele frequencies estimated using pool-sequencing are higher than the standard errors of allele frequencies estimated using individual sequencing). The four bottom graphs represent the
standard error of allele frequency estimates when using pool-sequencing
How to export UNICS graphs?
UNICS graphs are interactive, so you can mouseover the curve to get
coordinates, zoom in and out and even export a png graph by clicking on the "png" icon on the top left corner of the graph.
What are the four UNICS parameters?
These parameters are the frequency of the allele, the amount of unequal individual contributions to the DNA pool, the overdispersion in sequencing depth and the average sequencing depth. To know more about each parameter, you can click on the question mark on the left hand side of the each graph below.
Unequal individual DNA
Overdispersion in sequencing
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