问Pheatmap注释行

EN

sigs <- na.omit(res)
sigs

log2 fold change (MLE): condition groupb vs groupa 
Wald test p-value: condition groupb vs groupa 

DataFrame with 16003 rows and 6 columns
                     baseMean log2FoldChange     lfcSE       stat     pvalue      padj
                    <numeric>      <numeric> <numeric>  <numeric>  <numeric> <numeric>
ENSSSCG00000048769   82.31674    -0.35837484 0.1217091 -2.9445195 0.00323457 0.0358965
ENSSSCG00000037372   40.49912     0.19133392 0.1472912  1.2990176 0.19393788 0.3612217
ENSSSCG00000027257 1572.05160     0.00319404 0.0743954  0.0429334 0.96575464 0.9791215
ENSSSCG00000029697  494.25472    -0.07424653 0.0665490 -1.1156672 0.26456461 0.4385568
ENSSSCG00000049216    2.54242    -0.42346331 0.5024718 -0.8427604 0.39936246 0.5728141

sigs.df <- as.data.frame(sigs)

Description:df [16,003 × 6]
 
 
baseMean
<dbl>
log2FoldChange
<dbl>
lfcSE
<dbl>
stat
<dbl>
pvalue
<dbl>
ENSSSCG00000048769  8.231674e+01    -0.3583748397   0.12170911  -2.9445194769   3.234566e-03    
ENSSSCG00000037372  4.049912e+01    0.1913339198    0.14729124  1.2990176317    1.939379e-01    
ENSSSCG00000027257  1.572052e+03    0.0031940448    0.07439538  0.0429333738    9.657546e-01    
ENSSSCG00000029697  4.942547e+02    -0.0742465345   0.06654900  -1.1156672146   2.645646e-01    

sigs.df <- sigs.df[(abs(sigs.df$log2FoldChange)>1) & (sigs.df$padj < 0.05),]
sigs.df
Description:df [426 × 6]
baseMean
<dbl>
log2FoldChange
<dbl>
lfcSE
<dbl>
stat
<dbl>
pvalue
<dbl>
padj
<dbl>
18.859565   1.247705    0.4096202   3.046004    2.319046e-03    3.030462e-02
8.702231    -6.199963   1.5519239   -3.995017   6.468949e-05    4.932854e-03
9.466600    -1.535926   0.4899316   -3.134980   1.718657e-03    2.570514e-02
1099.496033 1.547162    0.3705798   4.174976    2.980168e-05    3.222408e-03

mat <- counts(dds, normalized = T)[rownames(sigs.df),]
mat

t(apply(mat,1, scale))

dds$condition <- factor(dds$condition, levels = c("Control","Blast"))

mat.z <- t(apply(mat,1, scale))
colnames(mat.z) = rownames(coldata)

mat.z

library(RColorBrewer)
bluegreen <- c("blue", "green") 
pal <- colorRampPalette(bluegreen)(100)

par(cex.main=.8)
heatmap(mat.z,cluster_rows = T, cluster_columns = T, column_labels = colnames(mat.z), name = "z-score", col = pal, legend = TRUE, 
main = "Heatmap of DEGS Normalized Counts in Pig Samples") 
The Output Heattmat is below.
Qu1: It seems to be only displaying a seclection of the genes (Rows labelled on right). How can I get it to display all the genes in detail?
[For thoose wondering, I havent mapped the Ensembl ID’s as there is an issue with Biomart & obtaining the scrofus gene ID’s !]
Qu2: I would like to annotate this with the conditions that each samples (bottom of heatmap) were exposed to. The Sample conditions & runs (Run oone and run 2) are held in the file ‘coldata’ but I am unable to get the heatmap to label/ annotate in this way.
I have seen people call a data frame to do this i./e”
df <- as.data.frame(file$sampleconditions)
then call this with pheatmap (annotation_row = df)..
However I cant seem to get this to work - should I be labelling my sample ID’s with the condition in the same file?
Thanks. Apologies for haphazardness (edited) 
:thread:
1



Rob Staruch
  5:10 PM
Rplot_Normalised_Counts_Pig_LF2C>1abs, PPadj<0005.png 
Rplot_Normalised_Counts_Pig_LF2C>1abs, PPadj<0005.png


:thread:
1

5:10
As an example of the above:
I want to add the annotation row labelling to a pheatmap.
It appears from the tutorial here: https://towardsdatascience.com/pheatmap-draws-pretty-heatmaps-483dab9a3cc
That I can call a data frame in order to do this.
Here is my data frame:

               Sample Condition
1    Sample_Run1HR62_S1_Run1    groupa
2    Sample_Run2HR62_S1_Run2    groupa
3    Sample_Run1HR70_S2_Run1    groupa
4    Sample_Run2HR70_S2_Run2    groupa
5    Sample_Run1HR78_S3_Run1    groupa
6    Sample_Run2HR78_S3_Run2    groupa
7    Sample_Run1HR81_S4_Run1    groupa
8    Sample_Run2HR81_S4_Run2    groupa
9    Sample_Run1HR87_S5_Run1    groupa
10   Sample_Run2HR87_S5_Run2    groupa
11   Sample_Run1HR99_S6_Run1    groupa
12   Sample_Run2HR99_S6_Run2    groupa
13  Sample_Run1HR107_S7_Run1    groupa
14  Sample_Run2HR107_S7_Run2    groupa
15  Sample_Run1HR114_S8_Run1    groupa
16  Sample_Run2HR114_S8_Run2    groupa
17 Sample_Run1HR142_S17_Run1    groupa
18 Sample_Run2HR142_S17_Run2    groupa
19 Sample_Run1HR146_S18_Run1    groupa
20 Sample_Run2HR146_S18_Run2    groupa
21   Sample_Run1HR61_S9_Run1    groupb
22   Sample_Run2HR61_S9_Run2    groupb
23  Sample_Run1HR71_S11_Run1    groupb
24  Sample_Run2HR71_S11_Run2    groupb
25  Sample_Run1HR74_S41_Run1    groupb
26  Sample_Run2HR74_S41_Run2    groupb
27  Sample_Run1HR80_S12_Run1    groupb
28  Sample_Run2HR80_S12_Run2    groupb
29  Sample_Run1HR86_S13_Run1    groupb
30  Sample_Run2HR86_S13_Run2    groupb
31 Sample_Run1HR115_S14_Run1    groupb
32 Sample_Run2HR115_S14_Run2    groupb
33 Sample_Run1HR121_S15_Run1    groupb
34 Sample_Run2HR121_S15_Run2    groupb
35 Sample_Run1HR127_S16_Run1    groupb
36 Sample_Run2HR127_S16_Run2    groupb
37  Sample_Run2HR66_S10_Run2    groupb
38  Sample_Run1HR66_S10_Run1    groupb
Here is the r script I am using to generate the Pheatmap:
# Create sample-sample heatmap
sampleDists <- dist(t(assay(rld))) #calculates Euclidean distance. Rld to ensure we have a roughly equal contribution from all genes
sampleDistMatrix <- as.matrix( sampleDists )
rownames(sampleDistMatrix) <- paste( targets$Sample, sep = " - " )
colnames(sampleDistMatrix) <- NULL
colors <- colorRampPalette( rev(brewer.pal(9, "Blues")) )(255)
pheatmap(sampleDistMatrix, clustering_distance_rows = sampleDists, clustering_distance_cols = sampleDists,col = colors, main = "Heatmap of Sample to Sample Distances in Pig Samples" )
Here is the same code when I add the ‘annotation_row’ command:
# Create sample-sample heatmap
sampleDists <- dist(t(assay(rld))) #calculates Euclidean distance. Rld to ensure we have a roughly equal contribution from all genes
sampleDistMatrix <- as.matrix( sampleDists )
rownames(sampleDistMatrix) <- paste( targets$Sample, sep = " - " )
colnames(sampleDistMatrix) <- NULL
colors <- colorRampPalette( rev(brewer.pal(9, "Blues")) )(255)
pheatmap(sampleDistMatrix, clustering_distance_rows = sampleDists, clustering_distance_cols = sampleDists,col = colors,annotation_row = targets, main = "Heatmap of Sample to Sample Distances in Pig Samples" )
Here is the error generated from this:
Error in check.length("fill") : 
  'gpar' element 'fill' must not be length 0
Any help would be greatly appreciated