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Goku Sun
Jun 12, 2020, 5:57:36 AM6/12/20
to brainGraph-help
Hi, Chris.
There is warning message in the R console:
I can't figure out why. Please help !
I am doing analysis of tractography networks of 3 groups, each group have about 20 subjects.
Follow your code example in user guide 7.2.3 to create matrix, and 7.3 to create graphs, 7.4 to calculate graph measures.
g.group <- g <- fnames <- vector('list', length = length(groups))for (i in seq_along(groups)) { for (j in seq_along(thresholds)) { print(paste0('Threshold ', j, '/', length(thresholds), '; group ', i, '; ', format(Sys.time(), '%H:%M:%S'))) foreach(k = seq_along(inds[[i]])) %dopar% { g.tmp <- graph_from_adjacency_matrix(A.norm.sub[[j]][, , inds[[i]][k]], mode = 'undirected', diag = F, weighted = T) g.tmp <- set_brainGraph_attr(g.tmp, atlas, modality = 'dti', weighting = 'sld', threshold = thresholds[j], subject = covars_dti[groups[i], Study.ID[k]], group = groups[i], use.parallel = FALSE, A = A.norm.sub[[j]][, , inds[[i]][k]]) saveRDS(g.tmp, file = paste0(savedir, '/', sprintf('g%i_thr%02i_subj%03i%s', i, j, k, '.rds'))) } } # Group mean weighted graphs print(paste0('Group', i, '; ', format(Sys.time(), '%H:%M:%S'))) g.group[[i]] <- lapply(seq_along(thresholds), function(x) graph_from_adjacency_matrix(A.norm.mean[[x]][[i]], mode = 'undirected', diag = F, weighted = T)) g.group[[i]] <- llply(seq_along(thresholds), function(x) brainGraph::set_brainGraph_attr(g.group[[i]][[x]], atlas, modality = 'dti', weighting = 'sld', threshold = thresholds[x], group = groups[i], A = A.norm.mean[[x]][[i]], use.parallel = FALSE), .parallel = TRUE)}
## check datafor (i in seq_along(groups)) { g[[i]] <- fnames[[i]] <- vector('list', length = length(thresholds)) for (j in seq_along(thresholds)) {
fnames[[i]][[j]] <- list.files(savedir, sprintf('g%i_thr%02i.*', i, j), full.names=T) g[[i]][[j]] <- lapply(fnames[[i]][[j]], readRDS) } x <- all.equal(sapply(g[[i]][[1]], graph_attr, 'name'), covars_dti[groups[i], Study.ID]) if (isTRUE(x)) lapply(fnames[[i]], file.remove)}saveRDS(g, file = paste0(savedir, '/', 'g.rds'))saveRDS(g.group, file = paste0(savedir, '/', 'g.group.rds'))
## Graph and Vertex measurements# GROUP-LEVEL#===============================================================================dt.V.group <- rbindlist(lapply(g.group, function(x) rbindlist(lapply(x, vertex_attr_dt))))dt.G.group <- rbindlist(Map(graph_attr_dt, g.group, as.list(groups)))# SUBJECT-LEVEL#===============================================================================dt.V <- vector('list', length = length(groups))for (i in seq_along(groups)) { dt.V[[i]] <- lapply(g[[i]], llply, vertex_attr_dt, groups[i]) dt.V[[i]] <- rbindlist(lapply(dt.V[[i]], rbindlist))}dt.V <- rbindlist(dt.V)dt.G <- rbindlist(Map(function(x, y) rbindlist(lapply(x, graph_attr_dt, y)), g, as.list(groups)))dt.V.group$sub.thresh <- dt.G.group$sub.thresh <- dt.G$sub.thresh <- dt.V$sub.thresh <- sub.threshsetorderv(dt.V, 'threshold', -1)setorderv(dt.G, 'threshold', -1)setcolorder(dt.V.group, c('modality', 'atlas', 'weighting', 'sub.thresh', 'threshold', 'Group', names(dt.V.group)[1:33]))setcolorder(dt.G.group, c('modality', 'atlas', 'weighting', 'sub.thresh','threshold', 'Group', names(dt.G.group)[c(1:4, 6:23)]))setcolorder(dt.G, c('modality', 'atlas', 'weighting', 'sub.thresh', 'threshold', 'Group', 'Study.ID', names(dt.G)[c(1:4, 6:23)]))setcolorder(dt.V, c('modality', 'atlas', 'weighting', 'sub.thresh', 'threshold', 'Group', 'Study.ID', names(dt.V)[1:33]))dt.G.group.tidy <- melt(dt.G.group, names(dt.G)[1:6])dt.G.tidy <- melt(dt.G, c(names(dt.G)[1:7], 'density'))red lines I actually commented out, because they always gave errors:
Error in colnamesInt(x, neworder, check_dups = TRUE) :
argument specifying columns specify duplicated column(s)Warning message: In melt.data.table(dt.G.group, names(dt.G)[1:6]) : 'measure.vars' [num.tri, diameter, transitivity, assortativity, ...] are not all of the same type. By order of hierarchy, the molten data value column will be of type 'character'. All measure variables not of type 'character' will be coerced too. Check DETAILS in ?melt.data.table for more on coercion.
and the yellow line gives duplicate density, maybe because I commented out the red lines?
Then, I found a lot of graph metrics always the same in one group, they are:
"Cp" "Lp" "E.global" "mod" "density" "num.tri" "diameter" "threshold""transitivity" "assortativity" "assortativity.lobe" "assortativity.lobe.hemi""asymm" "spatial.dist" "num.hubs" "E.local" "vulnerability"
while other graph metrics seems normal, different for each subject in one group:
"strength" "mod.wt"
"E.local.wt" "E.global.wt" "diameter.wt" "Lp.wt"
"num.hubs.wt" I can't figure out why. Please help !
The environment is brainGraph v2.7.3，Ubuntu 18.04, Rstudio 1.2.5033, and R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Chris Watson
Jun 12, 2020, 10:47:32 AM6/12/20
to brainGr...@googlegroups.com
It looks like the non-weighted metrics are the same across subjects. This means that each subject within a group has the same topology. I suspect it depends on the "sub.thresh" value you used (the closer to 1, the more likely it is that they will have the same edges), but I didn't see you mention it in the email. It is not necessarily a problem or issue, though.
Chris
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Goku Sun
Jun 12, 2020, 1:03:36 PM6/12/20
to brainGraph-help
Hi, Chris,
I do checked the raw fdt_matrix, they were not the same across subjects.
Sorry I did not mention these arguments.
sub.thresh = 0.5 , as your example codes in the user guide.
thresholds <- rev(seq(0.001, 0.01, 0.001))sub.thresh <- 0.5divisor <- 'waytotal'my.mats <- create_mats(matfiles$A, modality=modality, divisor=divisor, div.files=matfiles$way, threshold.by = "consensus", mat.thresh=thresholds, sub.thresh=sub.thresh, inds=inds)I plotted some matrix in A.norm.sub to compare, and looks like the topology maybe the same, if turned into binary network. Only the weights differs.
At this point, what is your advice for me to do analysis correctly?
Should I change some parameter when create_mats? Change "threshold.by" or sub.thresh, or something else?
Chris Watson
Jun 12, 2020, 3:54:16 PM6/12/20
to brainGr...@googlegroups.com
I wouldn't say there is one way or another that is "correct". It is not wrong for all subjects to have the same topology. What that means, though, is that you can only perform inference on weighted graph metrics. If you would like to learn more, you will have to read the literature
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Goku Sun
Jun 12, 2020, 11:48:25 PM6/12/20
to brainGraph-help
Thank you, Chris.
the console output was:
Now I get the point that it is not wrong to have the same topology in the same group.
Your answers helped me a lot, thank you.
Oh, by the way, I have an other question to ask. I compared the 3 group weighted graph metrics, but I could not get the glm plots.
I have 3 group subjects, GroupA, GroupB, GroupC, and the GLM design was like this:
X <- brainGraph_GLM_design(covars_use, coding = "cell.means")conmat <- matrix(c(-1,1,0, -1,0,1, 0,-1,1), nrow = 3)
conmat <- t(conmat)rownames(conmat) <- c("B-A", "C-A", "C-B")
g.glm <- do.call(Map, c(c, g))[[6]]glm.res <- brainGraph_GLM(g.list = g.glm, covars = covars_use, measure = "strength", X = X, con.mat = conmat, level = "graph")summary(glm.res)
plot(glm.res)brainGraph GLM results
---------------------------------------------------------------
Level: graph
Graph metric of interest: strength
Contrast type: T contrast
Alternative hypothesis: C != 0
Contrast matrix:
GroupA GroupB GroupC
B-A -1 1 0
C-A -1 0 1
C-B 0 -1 1
Statistics
-------------------------------
B-A
Region Estimate 95% CI low 95% CI high Std. error t value p-value p-value (FDR)
1: graph 0.11905 0.046618 0.19149 0.036224 3.2866 0.0016847 0.0016847
C-A
No signficant results!
C-B
No signficant results!
`geom_smooth()` using formula 'y ~ x'
`geom_smooth()` using formula 'y ~ x'
`geom_smooth()` using formula 'y ~ x'
TableGrob (4 x 2) "arrange": 6 grobs
z cells name grob
1 1 (2-2,1-1) arrange gtable[layout]
2 2 (2-2,2-2) arrange gtable[layout]
3 3 (3-3,1-1) arrange gtable[layout]
4 4 (3-3,2-2) arrange gtable[layout]
5 5 (1-1,1-2) arrange text[GRID.text.4511]
6 6 (4-4,1-2) arrange text[GRID.text.4512]
There were 12 warnings (use warnings() to see them)
> warnings()
1: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric, ... :
pseudoinverse used at 2.4124
2: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric, ... :
neighborhood radius 0.11965
3: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric, ... :
reciprocal condition number 3.5405e-16
4: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric, ... :
There are other near singularities as well. 0.014315
5: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric, ... :
pseudoinverse used at 2.4124
6: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric, ... :
neighborhood radius 0.11965
7: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric, ... :
reciprocal condition number 3.9505e-16
8: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric, ... :
There are other near singularities as well. 0.014315
9: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric, ... :
pseudoinverse used at 0.043446
10: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric, ... :
neighborhood radius 0.0065543
11: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric, ... :
reciprocal condition number 2.2595e-16
12: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric, ... :
There are other near singularities as well. 4.2959e-05
there was no plot showed. Maybe I used the wrong plot function or wrong polt parameters, I'm afraid.
How can I plot the GLM results? Please give me some instructions.
Thank you!
Goku Sun
Jun 12, 2020, 11:56:29 PM6/12/20
to brainGraph-help
Hi, Chris.
Some infomation you may need:
> X GroupA GroupB GroupC [1,] 1 0 0 [2,] 1 0 0 [3,] 1 0 0
...
[22,] 0 1 0
[23,] 0 1 0
[24,] 0 1 0...
[42,] 0 0 1
[50,] 0 0 1
[51,] 0 0 1
[52,] 0 0 1
and covars_use only has two columns: Study.ID and Group, for simplify purpose.Chris Watson
Jun 13, 2020, 1:06:49 AM6/13/20
to brainGr...@googlegroups.com
You may have to add "[[1]]" at the end of the call to the "plot" function.
plot(glm.res)[[1]]
Chris
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Goku Sun
Jun 13, 2020, 1:57:02 AM6/13/20
to brainGraph-help
Hi, Chris.
Sorry to bother you again...
I did as you told me, then I got no plot but these messages from R console:
> plot(glm.res)[[1]]
`geom_smooth()` using formula 'y ~ x' `geom_smooth()` using formula 'y ~ x' `geom_smooth()` using formula 'y ~ x'
[[1]]
TableGrob (12 x 9) "layout": 18 grobs
z cells name grob
1 0 ( 1-12, 1- 9) background rect[plot.background..rect.1312]
2 5 ( 6- 6, 4- 4) spacer zeroGrob[NULL]
3 7 ( 7- 7, 4- 4) axis-l absoluteGrob[GRID.absoluteGrob.1298]
4 3 ( 8- 8, 4- 4) spacer zeroGrob[NULL]
5 6 ( 6- 6, 5- 5) axis-t zeroGrob[NULL]
6 1 ( 7- 7, 5- 5) panel gTree[panel-1.gTree.1290]
7 9 ( 8- 8, 5- 5) axis-b absoluteGrob[GRID.absoluteGrob.1294]
8 4 ( 6- 6, 6- 6) spacer zeroGrob[NULL]
9 8 ( 7- 7, 6- 6) axis-r zeroGrob[NULL]
10 2 ( 8- 8, 6- 6) spacer zeroGrob[NULL]
11 10 ( 5- 5, 5- 5) xlab-t zeroGrob[NULL]
12 11 ( 9- 9, 5- 5) xlab-b titleGrob[axis.title.x.bottom..titleGrob.1301]
13 12 ( 7- 7, 3- 3) ylab-l titleGrob[axis.title.y.left..titleGrob.1304]
14 13 ( 7- 7, 7- 7) ylab-r zeroGrob[NULL]
15 14 ( 4- 4, 5- 5) subtitle zeroGrob[plot.subtitle..zeroGrob.1308]
16 15 ( 3- 3, 5- 5) title titleGrob[plot.title..titleGrob.1307]
17 16 (10-10, 5- 5) caption zeroGrob[plot.caption..zeroGrob.1310]
18 17 ( 2- 2, 2- 2) tag zeroGrob[plot.tag..zeroGrob.1309]
[[2]]
TableGrob (12 x 9) "layout": 18 grobs
z cells name grob
1 0 ( 1-12, 1- 9) background rect[plot.background..rect.1354]
2 5 ( 6- 6, 4- 4) spacer zeroGrob[NULL]
3 7 ( 7- 7, 4- 4) axis-l absoluteGrob[GRID.absoluteGrob.1340]
4 3 ( 8- 8, 4- 4) spacer zeroGrob[NULL]
5 6 ( 6- 6, 5- 5) axis-t zeroGrob[NULL]
6 1 ( 7- 7, 5- 5) panel gTree[panel-1.gTree.1332]
7 9 ( 8- 8, 5- 5) axis-b absoluteGrob[GRID.absoluteGrob.1336]
8 4 ( 6- 6, 6- 6) spacer zeroGrob[NULL]
9 8 ( 7- 7, 6- 6) axis-r zeroGrob[NULL]
10 2 ( 8- 8, 6- 6) spacer zeroGrob[NULL]
11 10 ( 5- 5, 5- 5) xlab-t zeroGrob[NULL]
12 11 ( 9- 9, 5- 5) xlab-b titleGrob[axis.title.x.bottom..titleGrob.1343]
13 12 ( 7- 7, 3- 3) ylab-l titleGrob[axis.title.y.left..titleGrob.1346]
14 13 ( 7- 7, 7- 7) ylab-r zeroGrob[NULL]
15 14 ( 4- 4, 5- 5) subtitle zeroGrob[plot.subtitle..zeroGrob.1350]
16 15 ( 3- 3, 5- 5) title titleGrob[plot.title..titleGrob.1349]
17 16 (10-10, 5- 5) caption zeroGrob[plot.caption..zeroGrob.1352]
18 17 ( 2- 2, 2- 2) tag zeroGrob[plot.tag..zeroGrob.1351]
[[3]]
TableGrob (12 x 9) "layout": 18 grobs
z cells name grob
1 0 ( 1-12, 1- 9) background rect[plot.background..rect.1398]
2 5 ( 6- 6, 4- 4) spacer zeroGrob[NULL]
3 7 ( 7- 7, 4- 4) axis-l absoluteGrob[GRID.absoluteGrob.1384]
4 3 ( 8- 8, 4- 4) spacer zeroGrob[NULL]
5 6 ( 6- 6, 5- 5) axis-t zeroGrob[NULL]
6 1 ( 7- 7, 5- 5) panel gTree[panel-1.gTree.1376]
7 9 ( 8- 8, 5- 5) axis-b absoluteGrob[GRID.absoluteGrob.1380]
8 4 ( 6- 6, 6- 6) spacer zeroGrob[NULL]
9 8 ( 7- 7, 6- 6) axis-r zeroGrob[NULL]
10 2 ( 8- 8, 6- 6) spacer zeroGrob[NULL]
11 10 ( 5- 5, 5- 5) xlab-t zeroGrob[NULL]
12 11 ( 9- 9, 5- 5) xlab-b titleGrob[axis.title.x.bottom..titleGrob.1387]
13 12 ( 7- 7, 3- 3) ylab-l titleGrob[axis.title.y.left..titleGrob.1390]
14 13 ( 7- 7, 7- 7) ylab-r zeroGrob[NULL]
15 14 ( 4- 4, 5- 5) subtitle zeroGrob[plot.subtitle..zeroGrob.1394]
16 15 ( 3- 3, 5- 5) title titleGrob[plot.title..titleGrob.1393]
17 16 (10-10, 5- 5) caption zeroGrob[plot.caption..zeroGrob.1396]
18 17 ( 2- 2, 2- 2) tag zeroGrob[plot.tag..zeroGrob.1395]
[[4]]
TableGrob (12 x 9) "layout": 18 grobs
z cells name grob
1 0 ( 1-12, 1- 9) background rect[plot.background..rect.1444]
2 5 ( 6- 6, 4- 4) spacer zeroGrob[NULL]
3 7 ( 7- 7, 4- 4) axis-l absoluteGrob[GRID.absoluteGrob.1430]
4 3 ( 8- 8, 4- 4) spacer zeroGrob[NULL]
5 6 ( 6- 6, 5- 5) axis-t zeroGrob[NULL]
6 1 ( 7- 7, 5- 5) panel gTree[panel-1.gTree.1422]
7 9 ( 8- 8, 5- 5) axis-b absoluteGrob[GRID.absoluteGrob.1426]
8 4 ( 6- 6, 6- 6) spacer zeroGrob[NULL]
9 8 ( 7- 7, 6- 6) axis-r zeroGrob[NULL]
10 2 ( 8- 8, 6- 6) spacer zeroGrob[NULL]
11 10 ( 5- 5, 5- 5) xlab-t zeroGrob[NULL]
12 11 ( 9- 9, 5- 5) xlab-b titleGrob[axis.title.x.bottom..titleGrob.1433]
13 12 ( 7- 7, 3- 3) ylab-l titleGrob[axis.title.y.left..titleGrob.1436]
14 13 ( 7- 7, 7- 7) ylab-r zeroGrob[NULL]
15 14 ( 4- 4, 5- 5) subtitle zeroGrob[plot.subtitle..zeroGrob.1440]
16 15 ( 3- 3, 5- 5) title titleGrob[plot.title..titleGrob.1439]
17 16 (10-10, 5- 5) caption zeroGrob[plot.caption..zeroGrob.1442]
18 17 ( 2- 2, 2- 2) tag zeroGrob[plot.tag..zeroGrob.1441]
[[5]]
text[GRID.text.1445]
[[6]]
text[GRID.text.1446]
Chris Watson
Jun 13, 2020, 6:28:58 PM6/13/20
to brainGr...@googlegroups.com
Try:
arrangeGrob(plot(res.glm))
arrangeGrob(plot(res.glm)[[1]])
grid.arrange(grobs=plot(res.glm))
grid.arrange(grobs=plot(res.glm)[[1]])
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Goku Sun
Jun 14, 2020, 1:52:17 AM6/14/20
to brainGraph-help
Thank you, Chris!
I tried them, and the results are:
arrangeGrob(plot(res.glm)) # Console output some info like before, but less, and no plot.
arrangeGrob(plot(res.glm)[[1]]) # Console output some info and 1 error, no plot
grid.arrange(grobs=plot(res.glm)) # Console output some info and 1 error, no plot
grid.arrange(grobs=plot(res.glm)[[1]]) # Some warnings and finally 1 page of 4 plots shows, yeah ~
You are very kind and patience, thank you!
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