I would like to use LogFC aftre RdgeR to colour KEGG Pathway Maps with my data.

1. Is it ok to extract $logFC, create a named list and put it into pathway()?
2. Should I use some filters like FDR < 0.05 & LogFC > or < 1.5 before using pathview()? I want to get grey colour for all NoSignal, red for Up and blue for Down regulated genes

Picture I want to get:

My EdgeR pipeline:
# filtering
keep <- filterByExpr(y, design)
y_filtered <- y[keep, , keep.lib.sizes=FALSE]

# to estimate dispersion 
y_disp_design <- estimateDisp(y_filtered, design = design, verbose=TRUE)

# Fit a quasi-likelihood negative binomial generalized log-linear model to count data
fit <- glmQLFit(y_disp_design, design, robust = TRUE)

# Conduct genewise statistical tests
LFC <- 1.5
tr.c1_2  <- glmTreat (fit, contrast = my.contrasts[, 'c1_2'], lfc = log2(LFC)) 

# Identify which genes are significantly differentially expressed
is.de.tr.c1_2 <- decideTestsDGE(tr.c1_2)

# View the  amount of Up and Down genes
summary(is.de.tr.c1_2)
Down 3191
NotSig 13930
Up 1077

# Extracts the most differentially expressed genes
TT_tr.c1_2 <- topTags(tr.c1_2, Inf)

# View TT_tr.c1_2
TT_tr.c1_2
Coefficient:  1*stage_1 -1*stage_2 
                          logFC unshrunk.logFC   logCPM       PValue          FDR
TRINITY_DN583_c0_g1   -3.254507  -3.255309e+00 6.980710 1.123231e-11 2.044055e-07
TRINITY_DN1301_c4_g1  -5.887508  -5.921260e+00 3.852718 2.272249e-11 2.067519e-07
...



# extract LogFC !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
gene_list <- TT_tr.c1_2$table$logFC 

# create named list
names(gene_list) <- my_KO_names

# view named logFC
head(gene_list)
K14156    K10860    K00072    K15701    K22257    K06240
-3.960318 -3.503302 -3.774908 -3.335891 -4.597206 -3.679689

dme <- pathview(gene.data=gene_list, 
                pathway.id="04064", 
                species = "ko",
                out.suffix = my_pair,
                limit = list(gene = 2, 
                             cpd = 1))