| mkGrids {ccems} | R Documentation |
This function takes g from mkg and maps it into a
dataframe of grid model definitions. It also augments and returns the input list g.
mkGrids (g,maxnPs=NULL,pRows=FALSE,contig=TRUE, atLeastOne=TRUE, IC=1)
g |
The output of mkg. |
maxnPs |
The maximum number of parameters of models in the model space. If NULL all models are found. |
pRows |
Set to TRUE if additional rows are to be added to the output dataframe to include models with p freely estimated. |
contig |
Set to TRUE to allow Kd equalities of threads only in contiguous runs. Tentatively, this should always be TRUE. |
atLeastOne |
Leave TRUE if only models with at least one complex of maximal size are to be considered. Set FALSE if there is no
prior knowledge supportive of the assertion that the largest oligomer must be in the model. |
IC |
The initial condition of all K parameters optimized. The default is IC=1. |
In a run of equal threads, the first head node of the run is the leader (optimized parameter) and the remaining nodes in the run are followers
(i.e. constrained to track the leader in parameter estimate optimizations); a default in ems is that only leader estimates are reported in html
in the results subdirectory.
In contrast to its counterpart mkSpurs, a means of traversing
the grid model space systematically with increasing numbers of parameters remains to be found and implemented.
As a result, mkGrids does not have state inputs and outputs and the whole space is found in one batch. When this drawback
limits research due to too much memory usage,
attempts will be made to identify an approach that, similar to what has been implemented for spurs, specifies
chunks of grid models, fits them, and then specifies the next chunk based on knowledge of where the previous chunk stopped. Note that setting
maxnPs to smaller values will not help with this foreseen problem as the full model space dataframe is first generated
and then, only later, truncated by maxnPs.
A list with components
chunk |
The entire K equality model space requested by the arguments. In this dataframe each row specifies a model. |
Keqs |
A list of K equality constraints indexed by model names where each element is a vector of character strings whose names are followers and values are leaders. |
g |
The input list g augmented to include the following components: |
|
A dataframe of the thread within site and oligo structure. |
|
A nested list of the thread structure with threads at the top of the list and their contents and memberships below. |
|
A list of threads within sites, i.e. the list indices are sites. |
|
A list of non-head nodes within sites. |
|
A vector of the single characters used to label Kd equivalent threads. This is with respect to the entire grid space. |
This work was supported by the National Cancer Institute (K25CA104791).
Tom Radivoyevitch (txr24@case.edu)
Radivoyevitch, T. (2008) Equilibrium model selection: dTTP induced R1 dimerization. BMC Systems Biology 2, 15.
library(ccems)
topology <- list(
heads=c("R1t0","R2t0"),
sites=list(
s=list( # s-site thread #
m=c("R1t1"), # monomer 1
d=c("R2t1","R2t2") # dimer 2
)
)
)
g <- mkg(topology,TCC=TRUE)
gridL <- mkGrids(g)
print(gridL$chunk)
topology <- list(
heads=c("R1X0","R2X2","R4X4","R6X6"), # s-sites are already filled only in (j>1)-mer head nodes
sites=list(
a=list( # a-site thread #
m=c("R1X1"), # monomer 1
d=c("R2X3","R2X4"), # dimer 2
t=c("R4X5","R4X6","R4X7","R4X8"), # tetramer 3
h=c("R6X7","R6X8","R6X9","R6X10", "R6X11", "R6X12") # hexamer 4
),
h=list( ## tails of a-site threads are heads of h-site threads # h-site
m=c("R1X2"), # monomer 5
d=c("R2X5", "R2X6"), # dimer 6
t=c("R4X9", "R4X10","R4X11", "R4X12"), # tetramer 7
h=c("R6X13", "R6X14", "R6X15","R6X16", "R6X17", "R6X18") # hexamer 8
)
)
)
g <- mkg(topology,TCC=TRUE)
gridL <- mkGrids(g,maxnPs=2)
print(gridL$chunk)
gridL <- mkGrids(g,maxnPs=4)
# the next line should be uncommented and run separately from those above since its output is large.
# print(gridL$chunk)