Bulk_RNA_seq
Shenfeng Qiu
2023-04-07
SQ NOTE:
All block can run
library(DESeq2)
library(ggplot2)
library(ComplexHeatmap)
library("org.Hs.eg.db")ls## HS_STAR_dir
## Homo_sapiens.GRCh38.109.gtf
## Homo_sapiens.GRCh38.dna_sm.primary_assembly.fa
## Sanbomics_RNAseq_video6.ipynb
## bams
## count.out
## count.out.summary
## count_table.csv
## deseq_results.csv
## deseq_workspace.RData
## diff_expr.Rmd
## diff_expr.html
## ensemble_key_mapper.csv
## fastq
## heatmap_v1.pdf
## heatmap_v1.png
## mapped
## ref
## rnaseq.Rproj
## simple_heatmap.png
## sratoolkit.3.0.2-ubuntu64
## sratoolkit.3.0.2-ubuntu64.tarCounts <- read.delim("count_table.csv", header = TRUE, row.names = 1, sep = ",")head(Counts)## Ctr_s1 Ctr_s2 Ctr_s7 Ctr_s13 RS_s6 RS_s9 RS_s12 RS_s16
## ENSG00000160072 427 328 416 246 549 202 361 174
## ENSG00000279928 0 0 0 0 0 0 0 0
## ENSG00000228037 0 0 0 1 0 0 0 1
## ENSG00000142611 24 5 54 17 14 1 73 11
## ENSG00000284616 0 0 0 0 0 0 0 0
## ENSG00000157911 174 183 213 169 250 102 189 100Counts <- Counts[which(rowSums(Counts)> 50),]head(Counts)## Ctr_s1 Ctr_s2 Ctr_s7 Ctr_s13 RS_s6 RS_s9 RS_s12 RS_s16
## ENSG00000160072 427 328 416 246 549 202 361 174
## ENSG00000142611 24 5 54 17 14 1 73 11
## ENSG00000157911 174 183 213 169 250 102 189 100
## ENSG00000269896 5 7 5 13 14 8 10 9
## ENSG00000142655 364 332 346 269 302 252 224 210
## ENSG00000171621 815 1174 630 605 660 568 533 359condition <- factor(c("C", "C", "C", "C", "S", "S", "S", "S"))coldata <- data.frame(row.names = colnames(Counts),condition)coldata## condition
## Ctr_s1 C
## Ctr_s2 C
## Ctr_s7 C
## Ctr_s13 C
## RS_s6 S
## RS_s9 S
## RS_s12 S
## RS_s16 Sdds <- DESeqDataSetFromMatrix(countData = Counts, colData = coldata, design = ~condition)dds <- DESeq(dds)vsdata <- vst(dds, blind = FALSE)plotPCA(vsdata, intgroup = "condition")+ geom_text(aes(label=name),vjust=2)
# plotPCA(vsdata, intgroup = "condition")+ geom_label(aes(label = colnames(vsdata)))plotDispEsts(dds)
res <- results(dds, contrast = c("condition", "S", "C"))head(res, 100)## log2 fold change (MLE): condition S vs C
## Wald test p-value: condition S vs C
## DataFrame with 100 rows and 6 columns
## baseMean log2FoldChange lfcSE stat pvalue
## <numeric> <numeric> <numeric> <numeric> <numeric>
## ENSG00000160072 320.76144 0.0945116 0.252136 0.374844 0.707777
## ENSG00000142611 23.79190 0.2328270 1.051377 0.221450 0.824742
## ENSG00000157911 166.60233 0.0300493 0.234862 0.127945 0.898193
## ENSG00000269896 9.15331 0.7004912 0.616870 1.135558 0.256142
## ENSG00000142655 282.67848 -0.0849087 0.169742 -0.500221 0.616919
## ... ... ... ... ... ...
## ENSG00000116652 7.14089 -0.8858524 0.706148 -1.2544852 0.209666
## ENSG00000123080 212.03083 0.0281466 0.845388 0.0332943 0.973440
## ENSG00000162415 144.12892 -1.6380016 1.352365 -1.2112130 0.225814
## ENSG00000162600 103.99734 -0.0871345 0.264999 -0.3288108 0.742299
## ENSG00000116704 393.05440 -0.1857103 0.165337 -1.1232263 0.261341
## padj
## <numeric>
## ENSG00000160072 0.999972
## ENSG00000142611 0.999972
## ENSG00000157911 0.999972
## ENSG00000269896 0.999972
## ENSG00000142655 0.999972
## ... ...
## ENSG00000116652 0.999972
## ENSG00000123080 0.999972
## ENSG00000162415 0.999972
## ENSG00000162600 0.999972
## ENSG00000116704 0.999972sigs <- na.omit(res)
sigs <- sigs[sigs$padj<0.05,]
head(sigs)## log2 fold change (MLE): condition S vs C
## Wald test p-value: condition S vs C
## DataFrame with 6 rows and 6 columns
## baseMean log2FoldChange lfcSE stat pvalue
## <numeric> <numeric> <numeric> <numeric> <numeric>
## ENSG00000187513 24.8428 8.24555 2.192258 3.76121 1.69093e-04
## ENSG00000117586 107.9179 1.78389 0.316856 5.62997 1.80241e-08
## ENSG00000116833 91.4553 -6.87821 1.531651 -4.49072 7.09839e-06
## ENSG00000076356 928.9865 1.16780 0.290421 4.02106 5.79368e-05
## ENSG00000163131 287.7356 -4.51536 1.117169 -4.04178 5.30459e-05
## ENSG00000162631 183.4102 -2.26377 0.591434 -3.82759 1.29404e-04
## padj
## <numeric>
## ENSG00000187513 4.35492e-02
## ENSG00000117586 6.63691e-05
## ENSG00000116833 5.80846e-03
## ENSG00000076356 2.24566e-02
## ENSG00000163131 2.11166e-02
## ENSG00000162631 3.52962e-02write.csv(sigs, file = "deseq_results.csv")sigs.df <- as.data.frame(sigs)
sigs.df## baseMean log2FoldChange lfcSE stat pvalue
## ENSG00000187513 24.842817 8.2455463 2.1922583 3.761211 1.690927e-04
## ENSG00000117586 107.917887 1.7838924 0.3168565 5.629970 1.802407e-08
## ENSG00000116833 91.455271 -6.8782103 1.5316509 -4.490717 7.098391e-06
## ENSG00000076356 928.986546 1.1678009 0.2904212 4.021060 5.793685e-05
## ENSG00000163131 287.735602 -4.5153567 1.1171690 -4.041785 5.304587e-05
## ENSG00000162631 183.410224 -2.2637650 0.5914336 -3.827590 1.294043e-04
## ENSG00000198744 119.991977 -6.8833832 1.4042926 -4.901673 9.502392e-07
## ENSG00000162878 301.802640 -1.1358393 0.2749817 -4.130600 3.618176e-05
## ENSG00000144339 35.107660 -2.3716410 0.5550538 -4.272813 1.930225e-05
## ENSG00000054356 582.501835 -3.3550985 0.7490842 -4.478934 7.501678e-06
## ENSG00000132329 21.202591 -3.0482421 0.8091325 -3.767297 1.650248e-04
## ENSG00000230838 37.944119 3.5348079 0.7578334 4.664360 3.095790e-06
## ENSG00000249992 1244.723782 -1.3423225 0.2848203 -4.712875 2.442460e-06
## ENSG00000163814 4524.136684 -1.1329960 0.3034945 -3.733168 1.890861e-04
## ENSG00000144824 1476.120686 0.7133463 0.1877279 3.799895 1.447577e-04
## ENSG00000169908 3899.283386 -0.8328781 0.1973860 -4.219540 2.448017e-05
## ENSG00000187091 310.551761 1.1180388 0.2419186 4.621550 3.808829e-06
## ENSG00000180914 286.479525 2.0078388 0.4579873 4.384049 1.164937e-05
## ENSG00000014257 11.801649 -2.8642169 0.6759762 -4.237156 2.263688e-05
## ENSG00000132465 26.019250 -5.1460162 1.0252602 -5.019229 5.187921e-07
## ENSG00000182585 16.937912 3.8611512 0.7417983 5.205123 1.938683e-07
## ENSG00000145335 77.494623 -6.0460584 1.2741503 -4.745169 2.083324e-06
## ENSG00000168685 223.875685 -3.2385125 0.7620463 -4.249758 2.140016e-05
## ENSG00000164251 534.108683 -2.0516183 0.4613494 -4.446994 8.708023e-06
## ENSG00000087116 2559.534531 0.9927466 0.2513969 3.948922 7.850406e-05
## ENSG00000137393 33.534508 -1.8883355 0.4885849 -3.864908 1.111312e-04
## ENSG00000204516 202.811945 -1.0041799 0.2124972 -4.725616 2.294194e-06
## ENSG00000096696 2123.165152 3.2098065 0.8143076 3.941762 8.088533e-05
## ENSG00000153294 45.873201 -1.2854609 0.2789443 -4.608308 4.059599e-06
## ENSG00000236453 46.896053 -3.2448884 0.8083689 -4.014118 5.966840e-05
## ENSG00000106538 119.587441 -4.4774851 1.0820654 -4.137906 3.504894e-05
## ENSG00000155849 21.733514 -4.3170408 1.1247341 -3.838277 1.239008e-04
## ENSG00000147257 56.457614 -4.5844851 1.2200271 -3.757691 1.714883e-04
## ENSG00000147454 532.869373 0.7796797 0.1717052 4.540804 5.604006e-06
## ENSG00000134013 11729.859413 1.6790683 0.4354026 3.856358 1.150890e-04
## ENSG00000182307 574.513438 -0.7582305 0.1926540 -3.935711 8.295090e-05
## ENSG00000154529 139.785608 2.4259239 0.6228361 3.894964 9.821351e-05
## ENSG00000119138 567.942765 -0.5141100 0.1264319 -4.066298 4.776576e-05
## ENSG00000136859 613.762293 -1.5407371 0.3457842 -4.455777 8.358986e-06
## ENSG00000085117 184.930233 -2.9281334 0.7515344 -3.896207 9.771093e-05
## ENSG00000166435 126.001366 1.0854882 0.1811251 5.993030 2.059672e-09
## ENSG00000198873 967.588853 0.4597816 0.1164530 3.948216 7.873562e-05
## ENSG00000122861 967.121837 -2.2180058 0.5388474 -4.116204 3.851637e-05
## ENSG00000138207 42.798311 3.0999427 0.7611299 4.072817 4.644793e-05
## ENSG00000121350 215.319446 0.6024325 0.1363193 4.419275 9.903249e-06
## ENSG00000261105 15.376714 3.5524727 0.9231639 3.848150 1.190134e-04
## ENSG00000287996 18.668988 -5.5178831 0.9430348 -5.851198 4.880453e-09
## ENSG00000126803 35.497279 -1.3573021 0.3176217 -4.273329 1.925756e-05
## ENSG00000092068 98.691027 -1.2613041 0.3398805 -3.711022 2.064244e-04
## ENSG00000140285 1307.029130 -2.0405477 0.5094508 -4.005388 6.191587e-05
## ENSG00000140470 43.257016 4.0088132 1.0193568 3.932689 8.400090e-05
## ENSG00000108576 21.953834 3.0816911 0.6075381 5.072424 3.927796e-07
## ENSG00000273018 7.972867 -5.5396672 1.2467529 -4.443276 8.859938e-06
## ENSG00000128482 33.914751 -1.5595766 0.4040515 -3.859847 1.134583e-04
## ENSG00000204650 67.478869 -1.3810443 0.3141193 -4.396560 1.099798e-05
## ENSG00000291090 6.854849 -3.9852812 1.0695801 -3.726024 1.945238e-04
## ENSG00000178184 54.913501 -1.9964318 0.4664466 -4.280087 1.868203e-05
## ENSG00000167642 29.901220 4.1119585 1.0350463 3.972729 7.105387e-05
## ENSG00000100376 243.485165 -1.3551115 0.2482108 -5.459519 4.774266e-08
## ENSG00000241945 16.624100 3.8380065 0.6469946 5.932054 2.991685e-09
## ENSG00000160221 11.858286 3.8295830 0.7411537 5.167056 2.378095e-07
## padj
## ENSG00000187513 4.354916e-02
## ENSG00000117586 6.636915e-05
## ENSG00000116833 5.808456e-03
## ENSG00000076356 2.245663e-02
## ENSG00000163131 2.111656e-02
## ENSG00000162631 3.529622e-02
## ENSG00000198744 1.399607e-03
## ENSG00000162878 1.614912e-02
## ENSG00000144339 1.015367e-02
## ENSG00000054356 5.815379e-03
## ENSG00000132329 4.340448e-02
## ENSG00000230838 3.256993e-03
## ENSG00000249992 2.767308e-03
## ENSG00000163814 4.720423e-02
## ENSG00000144824 3.876611e-02
## ENSG00000169908 1.163124e-02
## ENSG00000187091 3.737114e-03
## ENSG00000180914 6.863341e-03
## ENSG00000014257 1.111395e-02
## ENSG00000132465 8.490321e-04
## ENSG00000182585 4.759144e-04
## ENSG00000145335 2.767308e-03
## ENSG00000168685 1.086907e-02
## ENSG00000164251 5.931728e-03
## ENSG00000087116 2.689672e-02
## ENSG00000137393 3.323816e-02
## ENSG00000204516 2.767308e-03
## ENSG00000096696 2.689672e-02
## ENSG00000153294 3.737114e-03
## ENSG00000236453 2.253477e-02
## ENSG00000106538 1.613237e-02
## ENSG00000155849 3.443273e-02
## ENSG00000147257 4.354916e-02
## ENSG00000147454 4.855377e-03
## ENSG00000134013 3.323816e-02
## ENSG00000182307 2.689672e-02
## ENSG00000154529 3.013722e-02
## ENSG00000119138 1.954283e-02
## ENSG00000136859 5.931728e-03
## ENSG00000085117 3.013722e-02
## ENSG00000166435 2.203226e-05
## ENSG00000198873 2.689672e-02
## ENSG00000122861 1.668552e-02
## ENSG00000138207 1.954283e-02
## ENSG00000121350 6.341955e-03
## ENSG00000261105 3.371055e-02
## ENSG00000287996 2.396140e-05
## ENSG00000126803 1.015367e-02
## ENSG00000092068 4.984303e-02
## ENSG00000140285 2.279897e-02
## ENSG00000140470 2.689672e-02
## ENSG00000108576 7.231564e-04
## ENSG00000273018 5.931728e-03
## ENSG00000128482 3.323816e-02
## ENSG00000204650 6.749549e-03
## ENSG00000291090 4.775235e-02
## ENSG00000178184 1.015367e-02
## ENSG00000167642 2.552567e-02
## ENSG00000100376 1.406403e-04
## ENSG00000241945 2.203226e-05
## ENSG00000160221 5.003851e-04# set a filter is optional
# sigs.df <- sigs.df[(sigs.df$baseMean > 50) & (abs(sigs.df$log2FoldChange) > 1.2),]sigs.df$symbol <- mapIds(org.Hs.eg.db, keys = rownames(sigs.df), keytype = "ENSEMBL", column = "SYMBOL") sigs.df## baseMean log2FoldChange lfcSE stat pvalue
## ENSG00000187513 24.842817 8.2455463 2.1922583 3.761211 1.690927e-04
## ENSG00000117586 107.917887 1.7838924 0.3168565 5.629970 1.802407e-08
## ENSG00000116833 91.455271 -6.8782103 1.5316509 -4.490717 7.098391e-06
## ENSG00000076356 928.986546 1.1678009 0.2904212 4.021060 5.793685e-05
## ENSG00000163131 287.735602 -4.5153567 1.1171690 -4.041785 5.304587e-05
## ENSG00000162631 183.410224 -2.2637650 0.5914336 -3.827590 1.294043e-04
## ENSG00000198744 119.991977 -6.8833832 1.4042926 -4.901673 9.502392e-07
## ENSG00000162878 301.802640 -1.1358393 0.2749817 -4.130600 3.618176e-05
## ENSG00000144339 35.107660 -2.3716410 0.5550538 -4.272813 1.930225e-05
## ENSG00000054356 582.501835 -3.3550985 0.7490842 -4.478934 7.501678e-06
## ENSG00000132329 21.202591 -3.0482421 0.8091325 -3.767297 1.650248e-04
## ENSG00000230838 37.944119 3.5348079 0.7578334 4.664360 3.095790e-06
## ENSG00000249992 1244.723782 -1.3423225 0.2848203 -4.712875 2.442460e-06
## ENSG00000163814 4524.136684 -1.1329960 0.3034945 -3.733168 1.890861e-04
## ENSG00000144824 1476.120686 0.7133463 0.1877279 3.799895 1.447577e-04
## ENSG00000169908 3899.283386 -0.8328781 0.1973860 -4.219540 2.448017e-05
## ENSG00000187091 310.551761 1.1180388 0.2419186 4.621550 3.808829e-06
## ENSG00000180914 286.479525 2.0078388 0.4579873 4.384049 1.164937e-05
## ENSG00000014257 11.801649 -2.8642169 0.6759762 -4.237156 2.263688e-05
## ENSG00000132465 26.019250 -5.1460162 1.0252602 -5.019229 5.187921e-07
## ENSG00000182585 16.937912 3.8611512 0.7417983 5.205123 1.938683e-07
## ENSG00000145335 77.494623 -6.0460584 1.2741503 -4.745169 2.083324e-06
## ENSG00000168685 223.875685 -3.2385125 0.7620463 -4.249758 2.140016e-05
## ENSG00000164251 534.108683 -2.0516183 0.4613494 -4.446994 8.708023e-06
## ENSG00000087116 2559.534531 0.9927466 0.2513969 3.948922 7.850406e-05
## ENSG00000137393 33.534508 -1.8883355 0.4885849 -3.864908 1.111312e-04
## ENSG00000204516 202.811945 -1.0041799 0.2124972 -4.725616 2.294194e-06
## ENSG00000096696 2123.165152 3.2098065 0.8143076 3.941762 8.088533e-05
## ENSG00000153294 45.873201 -1.2854609 0.2789443 -4.608308 4.059599e-06
## ENSG00000236453 46.896053 -3.2448884 0.8083689 -4.014118 5.966840e-05
## ENSG00000106538 119.587441 -4.4774851 1.0820654 -4.137906 3.504894e-05
## ENSG00000155849 21.733514 -4.3170408 1.1247341 -3.838277 1.239008e-04
## ENSG00000147257 56.457614 -4.5844851 1.2200271 -3.757691 1.714883e-04
## ENSG00000147454 532.869373 0.7796797 0.1717052 4.540804 5.604006e-06
## ENSG00000134013 11729.859413 1.6790683 0.4354026 3.856358 1.150890e-04
## ENSG00000182307 574.513438 -0.7582305 0.1926540 -3.935711 8.295090e-05
## ENSG00000154529 139.785608 2.4259239 0.6228361 3.894964 9.821351e-05
## ENSG00000119138 567.942765 -0.5141100 0.1264319 -4.066298 4.776576e-05
## ENSG00000136859 613.762293 -1.5407371 0.3457842 -4.455777 8.358986e-06
## ENSG00000085117 184.930233 -2.9281334 0.7515344 -3.896207 9.771093e-05
## ENSG00000166435 126.001366 1.0854882 0.1811251 5.993030 2.059672e-09
## ENSG00000198873 967.588853 0.4597816 0.1164530 3.948216 7.873562e-05
## ENSG00000122861 967.121837 -2.2180058 0.5388474 -4.116204 3.851637e-05
## ENSG00000138207 42.798311 3.0999427 0.7611299 4.072817 4.644793e-05
## ENSG00000121350 215.319446 0.6024325 0.1363193 4.419275 9.903249e-06
## ENSG00000261105 15.376714 3.5524727 0.9231639 3.848150 1.190134e-04
## ENSG00000287996 18.668988 -5.5178831 0.9430348 -5.851198 4.880453e-09
## ENSG00000126803 35.497279 -1.3573021 0.3176217 -4.273329 1.925756e-05
## ENSG00000092068 98.691027 -1.2613041 0.3398805 -3.711022 2.064244e-04
## ENSG00000140285 1307.029130 -2.0405477 0.5094508 -4.005388 6.191587e-05
## ENSG00000140470 43.257016 4.0088132 1.0193568 3.932689 8.400090e-05
## ENSG00000108576 21.953834 3.0816911 0.6075381 5.072424 3.927796e-07
## ENSG00000273018 7.972867 -5.5396672 1.2467529 -4.443276 8.859938e-06
## ENSG00000128482 33.914751 -1.5595766 0.4040515 -3.859847 1.134583e-04
## ENSG00000204650 67.478869 -1.3810443 0.3141193 -4.396560 1.099798e-05
## ENSG00000291090 6.854849 -3.9852812 1.0695801 -3.726024 1.945238e-04
## ENSG00000178184 54.913501 -1.9964318 0.4664466 -4.280087 1.868203e-05
## ENSG00000167642 29.901220 4.1119585 1.0350463 3.972729 7.105387e-05
## ENSG00000100376 243.485165 -1.3551115 0.2482108 -5.459519 4.774266e-08
## ENSG00000241945 16.624100 3.8380065 0.6469946 5.932054 2.991685e-09
## ENSG00000160221 11.858286 3.8295830 0.7411537 5.167056 2.378095e-07
## padj symbol
## ENSG00000187513 4.354916e-02 GJA4
## ENSG00000117586 6.636915e-05 TNFSF4
## ENSG00000116833 5.808456e-03 NR5A2
## ENSG00000076356 2.245663e-02 PLXNA2
## ENSG00000163131 2.111656e-02 CTSS
## ENSG00000162631 3.529622e-02 NTNG1
## ENSG00000198744 1.399607e-03 MTCO3P12
## ENSG00000162878 1.614912e-02 PKDCC
## ENSG00000144339 1.015367e-02 TMEFF2
## ENSG00000054356 5.815379e-03 PTPRN
## ENSG00000132329 4.340448e-02 RAMP1
## ENSG00000230838 3.256993e-03 LINC01614
## ENSG00000249992 2.767308e-03 TMEM158
## ENSG00000163814 4.720423e-02 CDCP1
## ENSG00000144824 3.876611e-02 PHLDB2
## ENSG00000169908 1.163124e-02 TM4SF1
## ENSG00000187091 3.737114e-03 PLCD1
## ENSG00000180914 6.863341e-03 OXTR
## ENSG00000014257 1.111395e-02 ACP3
## ENSG00000132465 8.490321e-04 JCHAIN
## ENSG00000182585 4.759144e-04 EPGN
## ENSG00000145335 2.767308e-03 SNCA
## ENSG00000168685 1.086907e-02 IL7R
## ENSG00000164251 5.931728e-03 F2RL1
## ENSG00000087116 2.689672e-02 ADAMTS2
## ENSG00000137393 3.323816e-02 RNF144B
## ENSG00000204516 2.767308e-03 MICB
## ENSG00000096696 2.689672e-02 DSP
## ENSG00000153294 3.737114e-03 ADGRF4
## ENSG00000236453 2.253477e-02 <NA>
## ENSG00000106538 1.613237e-02 RARRES2
## ENSG00000155849 3.443273e-02 ELMO1
## ENSG00000147257 4.354916e-02 GPC3
## ENSG00000147454 4.855377e-03 SLC25A37
## ENSG00000134013 3.323816e-02 LOXL2
## ENSG00000182307 2.689672e-02 C8orf33
## ENSG00000154529 3.013722e-02 CNTNAP3B
## ENSG00000119138 1.954283e-02 KLF9
## ENSG00000136859 5.931728e-03 ANGPTL2
## ENSG00000085117 3.013722e-02 CD82
## ENSG00000166435 2.203226e-05 XRRA1
## ENSG00000198873 2.689672e-02 GRK5
## ENSG00000122861 1.668552e-02 PLAU
## ENSG00000138207 1.954283e-02 RBP4
## ENSG00000121350 6.341955e-03 PYROXD1
## ENSG00000261105 3.371055e-02 LMO7-AS1
## ENSG00000287996 2.396140e-05 <NA>
## ENSG00000126803 1.015367e-02 HSPA2
## ENSG00000092068 4.984303e-02 SLC7A8
## ENSG00000140285 2.279897e-02 FGF7
## ENSG00000140470 2.689672e-02 ADAMTS17
## ENSG00000108576 7.231564e-04 SLC6A4
## ENSG00000273018 5.931728e-03 FAM106A
## ENSG00000128482 3.323816e-02 RNF112
## ENSG00000204650 6.749549e-03 LINC02210
## ENSG00000291090 4.775235e-02 <NA>
## ENSG00000178184 1.015367e-02 PARD6G
## ENSG00000167642 2.552567e-02 SPINT2
## ENSG00000100376 1.406403e-04 FAM118A
## ENSG00000241945 2.203226e-05 PWP2
## ENSG00000160221 5.003851e-04 GATD3mat <- counts(dds, normalized = T)[rownames(sigs.df),]mat.z <- t(apply(mat, 1, scale))
colnames(mat.z) <- rownames(coldata)
mat.z## Ctr_s1 Ctr_s2 Ctr_s7 Ctr_s13 RS_s6
## ENSG00000187513 -0.53390969 -0.53390969 -0.53390969 -0.53390969 1.97294286
## ENSG00000117586 -0.93991508 -0.61602859 -1.01384340 -0.80454210 -0.05109491
## ENSG00000116833 2.36333821 0.38919437 -0.45124583 -0.45837166 -0.46489894
## ENSG00000076356 -0.32972220 -0.93532312 -0.72459294 -1.17132466 1.22592980
## ENSG00000163131 0.58611704 2.29590457 -0.48201437 -0.49517994 -0.46931566
## ENSG00000162631 1.75275345 -0.34935008 1.12805234 0.40949604 -0.97805604
## ENSG00000198744 1.14519483 2.00779525 -0.51495335 -0.51960557 -0.52365352
## ENSG00000162878 0.14096034 1.20452216 1.43228507 0.49779997 -1.03618650
## ENSG00000144339 1.24264050 1.80328716 -0.37234003 0.17096428 -0.68052573
## ENSG00000054356 0.19785195 2.39673854 -0.43436327 -0.16505469 -0.45011870
## ENSG00000132329 -0.33864954 -0.13546766 0.47052149 2.30421527 -0.59019318
## ENSG00000230838 -0.74166204 -0.67095896 -0.60269355 -0.69498860 0.57260423
## ENSG00000249992 1.11376072 0.47027382 -0.23420351 1.73529297 -0.84693447
## ENSG00000163814 0.79134182 1.46517167 -0.11847441 1.01754669 -1.20626766
## ENSG00000144824 -0.40713988 -0.70840591 -0.96857577 -1.05602308 0.76567492
## ENSG00000169908 1.43371644 0.64756937 0.38895329 0.90978613 -0.17797172
## ENSG00000187091 -0.93831242 -1.06934077 -0.70926495 -0.54021732 1.27203695
## ENSG00000180914 -0.58920496 -0.68409801 -0.74471724 -0.61412055 0.27363306
## ENSG00000014257 1.15598892 1.59929029 0.43851743 0.16724335 -0.71134235
## ENSG00000132465 1.45334702 -0.22990702 -0.38663275 1.73903963 -0.66278780
## ENSG00000182585 -0.85194984 -0.66726873 -0.93377131 -0.98437895 1.11614969
## ENSG00000145335 0.70527739 2.24684661 -0.46540957 -0.47580085 -0.50130744
## ENSG00000168685 0.09551537 2.41963187 -0.41965263 -0.16948451 -0.51270136
## ENSG00000164251 1.34865193 -0.06240734 0.66858637 1.33044977 -0.45854198
## ENSG00000087116 -1.13002496 -1.50874839 -0.35333968 -0.46906323 0.86915682
## ENSG00000137393 0.47985999 1.08372183 0.93303660 1.00149305 -1.08004435
## ENSG00000204516 1.34801928 1.25523837 0.82747025 -0.07371315 -0.73809646
## ENSG00000096696 -0.53251342 -0.48176487 -0.43793748 -0.41088822 0.21343057
## ENSG00000153294 1.06361116 1.10499403 0.29164536 1.11063829 -0.63310557
## ENSG00000236453 0.50570056 2.26627870 -0.09631936 -0.21611802 -0.55792454
## ENSG00000106538 -0.40913187 2.46035476 -0.09849627 -0.32101684 -0.38468953
## ENSG00000155849 0.35644813 2.35889797 -0.32807386 -0.27576359 -0.56444333
## ENSG00000147257 -0.60942160 -0.34907534 1.66893358 1.55881582 -0.59076903
## ENSG00000147454 -0.79416469 -1.39611264 -0.50979399 -0.76803669 1.08043146
## ENSG00000134013 -0.64247076 -0.75779689 -0.73631455 -0.42355638 -0.48336395
## ENSG00000182307 0.62478308 0.79178891 0.23891919 1.63504944 -1.25141446
## ENSG00000154529 -0.36319534 -0.76664214 -0.72091774 -0.80866731 1.79123037
## ENSG00000119138 0.21694835 1.30754752 1.20947187 0.71493564 -0.44712167
## ENSG00000136859 1.52017355 -0.08796441 0.59387660 1.20650722 -0.67753257
## ENSG00000085117 -0.56025860 2.28932996 0.02247387 0.45799610 -0.65277923
## ENSG00000166435 -0.91178564 -0.88845228 -0.73302335 -1.05988577 0.44710907
## ENSG00000198873 -0.91115240 -0.68270089 -1.02680580 -0.74118008 0.40099866
## ENSG00000122861 1.73309368 -0.42750016 0.16644674 1.31520838 -0.79008625
## ENSG00000138207 -0.62997906 -0.47097984 -0.57879728 -0.50529400 -0.05442631
## ENSG00000121350 -1.06269299 -1.09452026 -0.86391452 -0.56202311 0.47760324
## ENSG00000261105 -0.56850408 -0.62793527 -0.47842898 -0.57652140 0.47350098
## ENSG00000287996 1.30740946 0.61261539 0.45987480 1.21300890 -0.85141589
## ENSG00000126803 0.62006932 1.14314570 1.25751394 0.54493707 -0.90317272
## ENSG00000092068 0.21938888 0.79250376 -0.09916691 2.00890720 -0.94719858
## ENSG00000140285 0.95659346 1.97693295 -0.61752954 0.28163359 -0.63427062
## ENSG00000140470 -0.58520522 -0.65221855 -0.48896389 -0.68084573 2.08596481
## ENSG00000108576 -0.72228522 -0.87415297 -0.65067586 -0.77129963 0.65168549
## ENSG00000273018 1.59175949 1.09763393 -0.10815409 0.71828904 -0.85669292
## ENSG00000128482 1.67632860 0.98325299 -0.12219770 0.67835139 -0.83262277
## ENSG00000204650 0.81327506 0.28296359 1.04148121 1.31375392 -1.11591959
## ENSG00000291090 1.81103062 1.02078743 0.01478665 0.34062552 -0.80030530
## ENSG00000178184 -0.10991692 1.81023717 0.23891238 1.09599940 -0.79005448
## ENSG00000167642 -0.53495486 -0.61107317 -0.61275360 -0.55952159 1.44065822
## ENSG00000100376 0.37350881 0.05037276 1.15885227 1.68138493 -0.69842009
## ENSG00000241945 -0.87618949 -0.95982135 -0.74943537 -0.95141867 1.49321372
## ENSG00000160221 -0.96050450 -0.71143214 -0.95087806 -0.93563061 0.53770998
## RS_s9 RS_s12 RS_s16
## ENSG00000187513 1.19670395 -0.53390969 -0.5000984
## ENSG00000117586 0.85601470 1.39783702 1.1715724
## ENSG00000116833 -0.46911242 -0.46400074 -0.4449030
## ENSG00000076356 1.45910939 -0.19462442 0.6705481
## ENSG00000163131 -0.46200961 -0.49636428 -0.4771378
## ENSG00000162631 -0.94261237 -0.51330728 -0.5069761
## ENSG00000198744 -0.52245618 -0.53392502 -0.5383964
## ENSG00000162878 -1.06082912 -0.17910648 -0.9994454
## ENSG00000144339 -0.76558203 -0.63184242 -0.7666017
## ENSG00000054356 -0.54008015 -0.47694259 -0.5280311
## ENSG00000132329 -0.65022198 -0.49115831 -0.5690461
## ENSG00000230838 1.96151642 0.78183487 -0.6056524
## ENSG00000249992 -0.87241786 -0.85782807 -0.5079436
## ENSG00000163814 -0.99809123 -0.84570031 -0.1055266
## ENSG00000144824 1.79073853 -0.10543833 0.6891695
## ENSG00000169908 -0.96700377 -1.31954188 -0.9155078
## ENSG00000187091 -0.09463063 0.59741740 1.4823117
## ENSG00000180914 2.11188356 0.70972518 -0.4631010
## ENSG00000014257 -0.98156744 -0.72252913 -0.9456011
## ENSG00000132465 -0.65324593 -0.65818188 -0.6016313
## ENSG00000182585 1.56203156 0.46352084 0.2956667
## ENSG00000145335 -0.49403616 -0.49779755 -0.5177724
## ENSG00000168685 -0.42874739 -0.49764576 -0.4869156
## ENSG00000164251 -0.72891705 -0.95370004 -1.1441217
## ENSG00000087116 0.94765285 1.04173106 0.6026355
## ENSG00000137393 -0.17924787 -1.21148118 -1.0273381
## ENSG00000204516 -0.86504778 -0.66962499 -1.0842455
## ENSG00000096696 2.40651794 -0.36383341 -0.3930111
## ENSG00000153294 -0.90687974 -0.86779179 -1.1631117
## ENSG00000236453 -0.73764627 -0.48337707 -0.6805940
## ENSG00000106538 -0.41945791 -0.40507556 -0.4224868
## ENSG00000155849 -0.45876295 -0.58661491 -0.5016875
## ENSG00000147257 -0.53999073 -0.60682860 -0.5316641
## ENSG00000147454 0.21919396 1.04028009 1.1282025
## ENSG00000134013 0.53727982 0.35074511 2.1554776
## ENSG00000182307 -0.95118502 -0.23603528 -0.8519059
## ENSG00000154529 1.29559636 0.03954724 -0.4669514
## ENSG00000119138 -1.14475309 -1.06012486 -0.7969038
## ENSG00000136859 -1.19402401 -0.50440486 -0.8566315
## ENSG00000085117 -0.54014074 -0.49880001 -0.5178213
## ENSG00000166435 0.66765979 1.20949853 1.2688797
## ENSG00000198873 1.58297831 0.19690958 1.1809526
## ENSG00000122861 -0.92019113 -0.58962648 -0.4873448
## ENSG00000138207 2.36922745 -0.35328272 0.2235318
## ENSG00000121350 1.19639850 0.70100874 1.2081404
## ENSG00000261105 2.31371219 -0.27812360 -0.2576998
## ENSG00000287996 -0.87435252 -0.93357006 -0.9335701
## ENSG00000126803 -1.28590957 -0.60565277 -0.7709310
## ENSG00000092068 -0.81617592 -0.43054501 -0.7277134
## ENSG00000140285 -0.64143502 -0.78038630 -0.5415385
## ENSG00000140470 0.97800160 -0.27303227 -0.3837008
## ENSG00000108576 0.22934668 0.08523138 2.0521501
## ENSG00000273018 -0.72944962 -0.85669292 -0.8566929
## ENSG00000128482 -0.76909026 -0.52350745 -1.0905148
## ENSG00000204650 -0.27238215 -1.02546919 -1.0377028
## ENSG00000291090 -0.90926505 -0.77707808 -0.7005818
## ENSG00000178184 -0.44555841 -0.82686123 -0.9727579
## ENSG00000167642 1.77155453 -0.58559608 -0.3083134
## ENSG00000100376 -0.85501294 -0.80103224 -0.9096535
## ENSG00000241945 0.72051489 0.99323843 0.3298978
## ENSG00000160221 0.71596719 1.56104198 0.7437262h <- Heatmap(mat.z, cluster_rows = T, cluster_columns = T, column_labels = colnames(mat.z), name = "Z-score", row_labels = sigs.df[rownames(mat.z),]$symbol)
h
png('simple_heatmap.png', res = 250, width = 1000, height = 1500)
print(h)
dev.off()To make a complex heatmap
df <- as.data.frame(sigs)
df## baseMean log2FoldChange lfcSE stat pvalue
## ENSG00000187513 24.842817 8.2455463 2.1922583 3.761211 1.690927e-04
## ENSG00000117586 107.917887 1.7838924 0.3168565 5.629970 1.802407e-08
## ENSG00000116833 91.455271 -6.8782103 1.5316509 -4.490717 7.098391e-06
## ENSG00000076356 928.986546 1.1678009 0.2904212 4.021060 5.793685e-05
## ENSG00000163131 287.735602 -4.5153567 1.1171690 -4.041785 5.304587e-05
## ENSG00000162631 183.410224 -2.2637650 0.5914336 -3.827590 1.294043e-04
## ENSG00000198744 119.991977 -6.8833832 1.4042926 -4.901673 9.502392e-07
## ENSG00000162878 301.802640 -1.1358393 0.2749817 -4.130600 3.618176e-05
## ENSG00000144339 35.107660 -2.3716410 0.5550538 -4.272813 1.930225e-05
## ENSG00000054356 582.501835 -3.3550985 0.7490842 -4.478934 7.501678e-06
## ENSG00000132329 21.202591 -3.0482421 0.8091325 -3.767297 1.650248e-04
## ENSG00000230838 37.944119 3.5348079 0.7578334 4.664360 3.095790e-06
## ENSG00000249992 1244.723782 -1.3423225 0.2848203 -4.712875 2.442460e-06
## ENSG00000163814 4524.136684 -1.1329960 0.3034945 -3.733168 1.890861e-04
## ENSG00000144824 1476.120686 0.7133463 0.1877279 3.799895 1.447577e-04
## ENSG00000169908 3899.283386 -0.8328781 0.1973860 -4.219540 2.448017e-05
## ENSG00000187091 310.551761 1.1180388 0.2419186 4.621550 3.808829e-06
## ENSG00000180914 286.479525 2.0078388 0.4579873 4.384049 1.164937e-05
## ENSG00000014257 11.801649 -2.8642169 0.6759762 -4.237156 2.263688e-05
## ENSG00000132465 26.019250 -5.1460162 1.0252602 -5.019229 5.187921e-07
## ENSG00000182585 16.937912 3.8611512 0.7417983 5.205123 1.938683e-07
## ENSG00000145335 77.494623 -6.0460584 1.2741503 -4.745169 2.083324e-06
## ENSG00000168685 223.875685 -3.2385125 0.7620463 -4.249758 2.140016e-05
## ENSG00000164251 534.108683 -2.0516183 0.4613494 -4.446994 8.708023e-06
## ENSG00000087116 2559.534531 0.9927466 0.2513969 3.948922 7.850406e-05
## ENSG00000137393 33.534508 -1.8883355 0.4885849 -3.864908 1.111312e-04
## ENSG00000204516 202.811945 -1.0041799 0.2124972 -4.725616 2.294194e-06
## ENSG00000096696 2123.165152 3.2098065 0.8143076 3.941762 8.088533e-05
## ENSG00000153294 45.873201 -1.2854609 0.2789443 -4.608308 4.059599e-06
## ENSG00000236453 46.896053 -3.2448884 0.8083689 -4.014118 5.966840e-05
## ENSG00000106538 119.587441 -4.4774851 1.0820654 -4.137906 3.504894e-05
## ENSG00000155849 21.733514 -4.3170408 1.1247341 -3.838277 1.239008e-04
## ENSG00000147257 56.457614 -4.5844851 1.2200271 -3.757691 1.714883e-04
## ENSG00000147454 532.869373 0.7796797 0.1717052 4.540804 5.604006e-06
## ENSG00000134013 11729.859413 1.6790683 0.4354026 3.856358 1.150890e-04
## ENSG00000182307 574.513438 -0.7582305 0.1926540 -3.935711 8.295090e-05
## ENSG00000154529 139.785608 2.4259239 0.6228361 3.894964 9.821351e-05
## ENSG00000119138 567.942765 -0.5141100 0.1264319 -4.066298 4.776576e-05
## ENSG00000136859 613.762293 -1.5407371 0.3457842 -4.455777 8.358986e-06
## ENSG00000085117 184.930233 -2.9281334 0.7515344 -3.896207 9.771093e-05
## ENSG00000166435 126.001366 1.0854882 0.1811251 5.993030 2.059672e-09
## ENSG00000198873 967.588853 0.4597816 0.1164530 3.948216 7.873562e-05
## ENSG00000122861 967.121837 -2.2180058 0.5388474 -4.116204 3.851637e-05
## ENSG00000138207 42.798311 3.0999427 0.7611299 4.072817 4.644793e-05
## ENSG00000121350 215.319446 0.6024325 0.1363193 4.419275 9.903249e-06
## ENSG00000261105 15.376714 3.5524727 0.9231639 3.848150 1.190134e-04
## ENSG00000287996 18.668988 -5.5178831 0.9430348 -5.851198 4.880453e-09
## ENSG00000126803 35.497279 -1.3573021 0.3176217 -4.273329 1.925756e-05
## ENSG00000092068 98.691027 -1.2613041 0.3398805 -3.711022 2.064244e-04
## ENSG00000140285 1307.029130 -2.0405477 0.5094508 -4.005388 6.191587e-05
## ENSG00000140470 43.257016 4.0088132 1.0193568 3.932689 8.400090e-05
## ENSG00000108576 21.953834 3.0816911 0.6075381 5.072424 3.927796e-07
## ENSG00000273018 7.972867 -5.5396672 1.2467529 -4.443276 8.859938e-06
## ENSG00000128482 33.914751 -1.5595766 0.4040515 -3.859847 1.134583e-04
## ENSG00000204650 67.478869 -1.3810443 0.3141193 -4.396560 1.099798e-05
## ENSG00000291090 6.854849 -3.9852812 1.0695801 -3.726024 1.945238e-04
## ENSG00000178184 54.913501 -1.9964318 0.4664466 -4.280087 1.868203e-05
## ENSG00000167642 29.901220 4.1119585 1.0350463 3.972729 7.105387e-05
## ENSG00000100376 243.485165 -1.3551115 0.2482108 -5.459519 4.774266e-08
## ENSG00000241945 16.624100 3.8380065 0.6469946 5.932054 2.991685e-09
## ENSG00000160221 11.858286 3.8295830 0.7411537 5.167056 2.378095e-07
## padj
## ENSG00000187513 4.354916e-02
## ENSG00000117586 6.636915e-05
## ENSG00000116833 5.808456e-03
## ENSG00000076356 2.245663e-02
## ENSG00000163131 2.111656e-02
## ENSG00000162631 3.529622e-02
## ENSG00000198744 1.399607e-03
## ENSG00000162878 1.614912e-02
## ENSG00000144339 1.015367e-02
## ENSG00000054356 5.815379e-03
## ENSG00000132329 4.340448e-02
## ENSG00000230838 3.256993e-03
## ENSG00000249992 2.767308e-03
## ENSG00000163814 4.720423e-02
## ENSG00000144824 3.876611e-02
## ENSG00000169908 1.163124e-02
## ENSG00000187091 3.737114e-03
## ENSG00000180914 6.863341e-03
## ENSG00000014257 1.111395e-02
## ENSG00000132465 8.490321e-04
## ENSG00000182585 4.759144e-04
## ENSG00000145335 2.767308e-03
## ENSG00000168685 1.086907e-02
## ENSG00000164251 5.931728e-03
## ENSG00000087116 2.689672e-02
## ENSG00000137393 3.323816e-02
## ENSG00000204516 2.767308e-03
## ENSG00000096696 2.689672e-02
## ENSG00000153294 3.737114e-03
## ENSG00000236453 2.253477e-02
## ENSG00000106538 1.613237e-02
## ENSG00000155849 3.443273e-02
## ENSG00000147257 4.354916e-02
## ENSG00000147454 4.855377e-03
## ENSG00000134013 3.323816e-02
## ENSG00000182307 2.689672e-02
## ENSG00000154529 3.013722e-02
## ENSG00000119138 1.954283e-02
## ENSG00000136859 5.931728e-03
## ENSG00000085117 3.013722e-02
## ENSG00000166435 2.203226e-05
## ENSG00000198873 2.689672e-02
## ENSG00000122861 1.668552e-02
## ENSG00000138207 1.954283e-02
## ENSG00000121350 6.341955e-03
## ENSG00000261105 3.371055e-02
## ENSG00000287996 2.396140e-05
## ENSG00000126803 1.015367e-02
## ENSG00000092068 4.984303e-02
## ENSG00000140285 2.279897e-02
## ENSG00000140470 2.689672e-02
## ENSG00000108576 7.231564e-04
## ENSG00000273018 5.931728e-03
## ENSG00000128482 3.323816e-02
## ENSG00000204650 6.749549e-03
## ENSG00000291090 4.775235e-02
## ENSG00000178184 1.015367e-02
## ENSG00000167642 2.552567e-02
## ENSG00000100376 1.406403e-04
## ENSG00000241945 2.203226e-05
## ENSG00000160221 5.003851e-04ensembl_map <- read.csv('ensemble_key_mapper.csv', header = TRUE)
head(ensembl_map, 100)## X X0
## 1 ENSG00000183908 LRRC55
## 2 ENSG00000262081 IL9RP4
## 3 ENSG00000250483 PPM1AP1
## 4 ENSG00000284465 TAF11L7
## 5 ENSG00000136267 DGKB
## 6 ENSG00000233733 H2AZP6
## 7 ENSG00000255552 LY6G6E
## 8 ENSG00000250166 C2CD5-AS1
## 9 ENSG00000223212 RNU4-74P
## 10 ENSG00000228219 NPM1P30
## 11 ENSG00000252810 RNU6-345P
## 12 ENSG00000206172 HBA1
## 13 ENSG00000238210 ETDA
## 14 ENSG00000229325 ACAP2-IT1
## 15 ENSG00000081059 TCF7
## 16 ENSG00000206728 Y_RNA
## 17 ENSG00000233827 CCNQP1
## 18 ENSG00000278524 MIR6810
## 19 ENSG00000122033 MTIF3
## 20 ENSG00000248449 PCDHGB8P
## 21 ENSG00000171222 SCAND1
## 22 ENSG00000207123 Y_RNA
## 23 ENSG00000147408 CSGALNACT1
## 24 ENSG00000226388 ELL2P4
## 25 ENSG00000062524 LTK
## 26 ENSG00000213018 PABPN1P1
## 27 ENSG00000254312 MRPL57P7
## 28 ENSG00000215883 CYB5RL
## 29 ENSG00000207864 MIR27B
## 30 ENSG00000215005 HSPD1P7
## 31 ENSG00000225416 RPL36AP28
## 32 ENSG00000269136 BRI3BPP1
## 33 ENSG00000233860 SHROOM3-AS1
## 34 ENSG00000266187 RN7SL480P
## 35 ENSG00000132967 HMGB1P5
## 36 ENSG00000232467 TMA16P2
## 37 ENSG00000276712 MIR7111
## 38 ENSG00000111325 OGFOD2
## 39 ENSG00000102309 PIN4
## 40 ENSG00000069329 VPS35
## 41 ENSG00000171612 SLC25A33
## 42 ENSG00000224411 HSP90AA2P
## 43 ENSG00000184961 RPL7AP49
## 44 ENSG00000130054 NALF2
## 45 ENSG00000163424 TEX55
## 46 ENSG00000188629 ZNF177
## 47 ENSG00000236946 HNRNPA1P70
## 48 ENSG00000148019 CEP78
## 49 ENSG00000188460 ACTBP11
## 50 ENSG00000182372 CLN8
## 51 ENSG00000073861 TBX21
## 52 ENSG00000231332 OOEP-AS1
## 53 ENSG00000252246 RNA5SP92
## 54 ENSG00000144655 CSRNP1
## 55 ENSG00000106028 SSBP1
## 56 ENSG00000252377 RNU6-504P
## 57 ENSG00000222327 RNU6-855P
## 58 ENSG00000136628 EPRS1
## 59 ENSG00000254843 XIAPP2
## 60 ENSG00000162437 RAVER2
## 61 ENSG00000199203 Y_RNA
## 62 ENSG00000072041 SLC6A15
## 63 ENSG00000149609 C20orf144
## 64 ENSG00000248483 POU5F2
## 65 ENSG00000200677 SNORD18
## 66 ENSG00000087086 FTL
## 67 ENSG00000277613 U6
## 68 ENSG00000120688 WBP4
## 69 ENSG00000126500 FLRT1
## 70 ENSG00000240666 MME-AS1
## 71 ENSG00000134709 HOOK1
## 72 ENSG00000232951 IPO7P1
## 73 ENSG00000127993 RBM48
## 74 ENSG00000285866 LINC02852
## 75 ENSG00000121892 PDS5A
## 76 ENSG00000180867 PDIA3P1
## 77 ENSG00000139767 SRRM4
## 78 ENSG00000143369 ECM1
## 79 ENSG00000109519 GRPEL1
## 80 ENSG00000138777 PPA2
## 81 ENSG00000217566 TDGF1P4
## 82 ENSG00000163939 PBRM1
## 83 ENSG00000232203 SLC25A6P2
## 84 ENSG00000161896 IP6K3
## 85 ENSG00000239684 PTGER4P3
## 86 ENSG00000253982 CLN8-AS1
## 87 ENSG00000104218 CSPP1
## 88 ENSG00000176043 RPL36P3
## 89 ENSG00000271465 SQSTM1P1
## 90 ENSG00000261303 GOLGA6GP
## 91 ENSG00000241007 SEPTIN7P6
## 92 ENSG00000252294 RNU6-589P
## 93 ENSG00000078070 MCCC1
## 94 ENSG00000230921 HAO2-IT1
## 95 ENSG00000227336 LINC00434
## 96 ENSG00000183629 GOLGA8G
## 97 ENSG00000163564 PYHIN1
## 98 ENSG00000252514 RNU7-53P
## 99 ENSG00000186113 OR5D14
## 100 ENSG00000154813 DPH3# the 'ensemble_key_mapper.csv' file was created by the 'Sanbomics_RNAseq_video6' filekeys <- ensembl_map$X
values <- ensembl_map$X0
l <- list()
for (i in 1:length(keys)){
l[keys[i]] <- values[i]
}# l# for non-mapped labels
no_values <- setdiff(rownames(df), keys)
for (i in 1:length(no_values)){
l[no_values[i]] <- 'NA'
}df$symbol <- unlist(l[rownames(df)], use.names = FALSE)
df.top <- df[(df$padj < 0.05) & (df$baseMean > 50) & (abs(df$log2FoldChange) >1.2), ]
df.top## baseMean log2FoldChange lfcSE stat pvalue
## ENSG00000117586 107.91789 1.783892 0.3168565 5.629970 1.802407e-08
## ENSG00000116833 91.45527 -6.878210 1.5316509 -4.490717 7.098391e-06
## ENSG00000163131 287.73560 -4.515357 1.1171690 -4.041785 5.304587e-05
## ENSG00000162631 183.41022 -2.263765 0.5914336 -3.827590 1.294043e-04
## ENSG00000198744 119.99198 -6.883383 1.4042926 -4.901673 9.502392e-07
## ENSG00000054356 582.50184 -3.355099 0.7490842 -4.478934 7.501678e-06
## ENSG00000249992 1244.72378 -1.342323 0.2848203 -4.712875 2.442460e-06
## ENSG00000180914 286.47952 2.007839 0.4579873 4.384049 1.164937e-05
## ENSG00000145335 77.49462 -6.046058 1.2741503 -4.745169 2.083324e-06
## ENSG00000168685 223.87569 -3.238513 0.7620463 -4.249758 2.140016e-05
## ENSG00000164251 534.10868 -2.051618 0.4613494 -4.446994 8.708023e-06
## ENSG00000096696 2123.16515 3.209807 0.8143076 3.941762 8.088533e-05
## ENSG00000106538 119.58744 -4.477485 1.0820654 -4.137906 3.504894e-05
## ENSG00000147257 56.45761 -4.584485 1.2200271 -3.757691 1.714883e-04
## ENSG00000134013 11729.85941 1.679068 0.4354026 3.856358 1.150890e-04
## ENSG00000154529 139.78561 2.425924 0.6228361 3.894964 9.821351e-05
## ENSG00000136859 613.76229 -1.540737 0.3457842 -4.455777 8.358986e-06
## ENSG00000085117 184.93023 -2.928133 0.7515344 -3.896207 9.771093e-05
## ENSG00000122861 967.12184 -2.218006 0.5388474 -4.116204 3.851637e-05
## ENSG00000092068 98.69103 -1.261304 0.3398805 -3.711022 2.064244e-04
## ENSG00000140285 1307.02913 -2.040548 0.5094508 -4.005388 6.191587e-05
## ENSG00000204650 67.47887 -1.381044 0.3141193 -4.396560 1.099798e-05
## ENSG00000178184 54.91350 -1.996432 0.4664466 -4.280087 1.868203e-05
## ENSG00000100376 243.48517 -1.355112 0.2482108 -5.459519 4.774266e-08
## padj symbol
## ENSG00000117586 6.636915e-05 TNFSF4
## ENSG00000116833 5.808456e-03 NR5A2
## ENSG00000163131 2.111656e-02 CTSS
## ENSG00000162631 3.529622e-02 NTNG1
## ENSG00000198744 1.399607e-03 MTCO3P12
## ENSG00000054356 5.815379e-03 PTPRN
## ENSG00000249992 2.767308e-03 TMEM158
## ENSG00000180914 6.863341e-03 OXTR
## ENSG00000145335 2.767308e-03 SNCA
## ENSG00000168685 1.086907e-02 IL7R
## ENSG00000164251 5.931728e-03 F2RL1
## ENSG00000096696 2.689672e-02 DSP
## ENSG00000106538 1.613237e-02 RARRES2
## ENSG00000147257 4.354916e-02 GPC3
## ENSG00000134013 3.323816e-02 LOXL2
## ENSG00000154529 3.013722e-02 CNTNAP3B
## ENSG00000136859 5.931728e-03 ANGPTL2
## ENSG00000085117 3.013722e-02 CD82
## ENSG00000122861 1.668552e-02 PLAU
## ENSG00000092068 4.984303e-02 SLC7A8
## ENSG00000140285 2.279897e-02 FGF7
## ENSG00000204650 6.749549e-03 LINC02210
## ENSG00000178184 1.015367e-02 PARD6G
## ENSG00000100376 1.406403e-04 FAM118Adf.top <- df.top[order(df.top$log2FoldChange, decreasing = TRUE),]df.top## baseMean log2FoldChange lfcSE stat pvalue
## ENSG00000096696 2123.16515 3.209807 0.8143076 3.941762 8.088533e-05
## ENSG00000154529 139.78561 2.425924 0.6228361 3.894964 9.821351e-05
## ENSG00000180914 286.47952 2.007839 0.4579873 4.384049 1.164937e-05
## ENSG00000117586 107.91789 1.783892 0.3168565 5.629970 1.802407e-08
## ENSG00000134013 11729.85941 1.679068 0.4354026 3.856358 1.150890e-04
## ENSG00000092068 98.69103 -1.261304 0.3398805 -3.711022 2.064244e-04
## ENSG00000249992 1244.72378 -1.342323 0.2848203 -4.712875 2.442460e-06
## ENSG00000100376 243.48517 -1.355112 0.2482108 -5.459519 4.774266e-08
## ENSG00000204650 67.47887 -1.381044 0.3141193 -4.396560 1.099798e-05
## ENSG00000136859 613.76229 -1.540737 0.3457842 -4.455777 8.358986e-06
## ENSG00000178184 54.91350 -1.996432 0.4664466 -4.280087 1.868203e-05
## ENSG00000140285 1307.02913 -2.040548 0.5094508 -4.005388 6.191587e-05
## ENSG00000164251 534.10868 -2.051618 0.4613494 -4.446994 8.708023e-06
## ENSG00000122861 967.12184 -2.218006 0.5388474 -4.116204 3.851637e-05
## ENSG00000162631 183.41022 -2.263765 0.5914336 -3.827590 1.294043e-04
## ENSG00000085117 184.93023 -2.928133 0.7515344 -3.896207 9.771093e-05
## ENSG00000168685 223.87569 -3.238513 0.7620463 -4.249758 2.140016e-05
## ENSG00000054356 582.50184 -3.355099 0.7490842 -4.478934 7.501678e-06
## ENSG00000106538 119.58744 -4.477485 1.0820654 -4.137906 3.504894e-05
## ENSG00000163131 287.73560 -4.515357 1.1171690 -4.041785 5.304587e-05
## ENSG00000147257 56.45761 -4.584485 1.2200271 -3.757691 1.714883e-04
## ENSG00000145335 77.49462 -6.046058 1.2741503 -4.745169 2.083324e-06
## ENSG00000116833 91.45527 -6.878210 1.5316509 -4.490717 7.098391e-06
## ENSG00000198744 119.99198 -6.883383 1.4042926 -4.901673 9.502392e-07
## padj symbol
## ENSG00000096696 2.689672e-02 DSP
## ENSG00000154529 3.013722e-02 CNTNAP3B
## ENSG00000180914 6.863341e-03 OXTR
## ENSG00000117586 6.636915e-05 TNFSF4
## ENSG00000134013 3.323816e-02 LOXL2
## ENSG00000092068 4.984303e-02 SLC7A8
## ENSG00000249992 2.767308e-03 TMEM158
## ENSG00000100376 1.406403e-04 FAM118A
## ENSG00000204650 6.749549e-03 LINC02210
## ENSG00000136859 5.931728e-03 ANGPTL2
## ENSG00000178184 1.015367e-02 PARD6G
## ENSG00000140285 2.279897e-02 FGF7
## ENSG00000164251 5.931728e-03 F2RL1
## ENSG00000122861 1.668552e-02 PLAU
## ENSG00000162631 3.529622e-02 NTNG1
## ENSG00000085117 3.013722e-02 CD82
## ENSG00000168685 1.086907e-02 IL7R
## ENSG00000054356 5.815379e-03 PTPRN
## ENSG00000106538 1.613237e-02 RARRES2
## ENSG00000163131 2.111656e-02 CTSS
## ENSG00000147257 4.354916e-02 GPC3
## ENSG00000145335 2.767308e-03 SNCA
## ENSG00000116833 5.808456e-03 NR5A2
## ENSG00000198744 1.399607e-03 MTCO3P12rlog_out <- rlog(dds, blind=FALSE) #get nomalized count data fro dds object
mat <- assay(rlog_out)[rownames(df.top), rownames(coldata)]
colnames(mat) <- rownames(coldata)
base_mean <- rowMeans(mat)
mat.scaled <- t(apply(mat, 1, scale))
colnames(mat.scaled) <- colnames(mat)
# assay(rlog_out)[rownames(df.top), rownames(coldata)] #inspect onlynum_keep <- 24
rows_keep <- c(seq(1:num_keep), seq((nrow(mat.scaled)-num_keep), nrow(mat.scaled)))
df.top## baseMean log2FoldChange lfcSE stat pvalue
## ENSG00000096696 2123.16515 3.209807 0.8143076 3.941762 8.088533e-05
## ENSG00000154529 139.78561 2.425924 0.6228361 3.894964 9.821351e-05
## ENSG00000180914 286.47952 2.007839 0.4579873 4.384049 1.164937e-05
## ENSG00000117586 107.91789 1.783892 0.3168565 5.629970 1.802407e-08
## ENSG00000134013 11729.85941 1.679068 0.4354026 3.856358 1.150890e-04
## ENSG00000092068 98.69103 -1.261304 0.3398805 -3.711022 2.064244e-04
## ENSG00000249992 1244.72378 -1.342323 0.2848203 -4.712875 2.442460e-06
## ENSG00000100376 243.48517 -1.355112 0.2482108 -5.459519 4.774266e-08
## ENSG00000204650 67.47887 -1.381044 0.3141193 -4.396560 1.099798e-05
## ENSG00000136859 613.76229 -1.540737 0.3457842 -4.455777 8.358986e-06
## ENSG00000178184 54.91350 -1.996432 0.4664466 -4.280087 1.868203e-05
## ENSG00000140285 1307.02913 -2.040548 0.5094508 -4.005388 6.191587e-05
## ENSG00000164251 534.10868 -2.051618 0.4613494 -4.446994 8.708023e-06
## ENSG00000122861 967.12184 -2.218006 0.5388474 -4.116204 3.851637e-05
## ENSG00000162631 183.41022 -2.263765 0.5914336 -3.827590 1.294043e-04
## ENSG00000085117 184.93023 -2.928133 0.7515344 -3.896207 9.771093e-05
## ENSG00000168685 223.87569 -3.238513 0.7620463 -4.249758 2.140016e-05
## ENSG00000054356 582.50184 -3.355099 0.7490842 -4.478934 7.501678e-06
## ENSG00000106538 119.58744 -4.477485 1.0820654 -4.137906 3.504894e-05
## ENSG00000163131 287.73560 -4.515357 1.1171690 -4.041785 5.304587e-05
## ENSG00000147257 56.45761 -4.584485 1.2200271 -3.757691 1.714883e-04
## ENSG00000145335 77.49462 -6.046058 1.2741503 -4.745169 2.083324e-06
## ENSG00000116833 91.45527 -6.878210 1.5316509 -4.490717 7.098391e-06
## ENSG00000198744 119.99198 -6.883383 1.4042926 -4.901673 9.502392e-07
## padj symbol
## ENSG00000096696 2.689672e-02 DSP
## ENSG00000154529 3.013722e-02 CNTNAP3B
## ENSG00000180914 6.863341e-03 OXTR
## ENSG00000117586 6.636915e-05 TNFSF4
## ENSG00000134013 3.323816e-02 LOXL2
## ENSG00000092068 4.984303e-02 SLC7A8
## ENSG00000249992 2.767308e-03 TMEM158
## ENSG00000100376 1.406403e-04 FAM118A
## ENSG00000204650 6.749549e-03 LINC02210
## ENSG00000136859 5.931728e-03 ANGPTL2
## ENSG00000178184 1.015367e-02 PARD6G
## ENSG00000140285 2.279897e-02 FGF7
## ENSG00000164251 5.931728e-03 F2RL1
## ENSG00000122861 1.668552e-02 PLAU
## ENSG00000162631 3.529622e-02 NTNG1
## ENSG00000085117 3.013722e-02 CD82
## ENSG00000168685 1.086907e-02 IL7R
## ENSG00000054356 5.815379e-03 PTPRN
## ENSG00000106538 1.613237e-02 RARRES2
## ENSG00000163131 2.111656e-02 CTSS
## ENSG00000147257 4.354916e-02 GPC3
## ENSG00000145335 2.767308e-03 SNCA
## ENSG00000116833 5.808456e-03 NR5A2
## ENSG00000198744 1.399607e-03 MTCO3P12l2_val <- as.matrix(df.top[rows_keep,]$log2FoldChange)
colnames(l2_val) <- "logFC"
mean <- as.matrix(df.top[rows_keep,]$baseMean)
colnames(mean) <- "AveExpr"df.top## baseMean log2FoldChange lfcSE stat pvalue
## ENSG00000096696 2123.16515 3.209807 0.8143076 3.941762 8.088533e-05
## ENSG00000154529 139.78561 2.425924 0.6228361 3.894964 9.821351e-05
## ENSG00000180914 286.47952 2.007839 0.4579873 4.384049 1.164937e-05
## ENSG00000117586 107.91789 1.783892 0.3168565 5.629970 1.802407e-08
## ENSG00000134013 11729.85941 1.679068 0.4354026 3.856358 1.150890e-04
## ENSG00000092068 98.69103 -1.261304 0.3398805 -3.711022 2.064244e-04
## ENSG00000249992 1244.72378 -1.342323 0.2848203 -4.712875 2.442460e-06
## ENSG00000100376 243.48517 -1.355112 0.2482108 -5.459519 4.774266e-08
## ENSG00000204650 67.47887 -1.381044 0.3141193 -4.396560 1.099798e-05
## ENSG00000136859 613.76229 -1.540737 0.3457842 -4.455777 8.358986e-06
## ENSG00000178184 54.91350 -1.996432 0.4664466 -4.280087 1.868203e-05
## ENSG00000140285 1307.02913 -2.040548 0.5094508 -4.005388 6.191587e-05
## ENSG00000164251 534.10868 -2.051618 0.4613494 -4.446994 8.708023e-06
## ENSG00000122861 967.12184 -2.218006 0.5388474 -4.116204 3.851637e-05
## ENSG00000162631 183.41022 -2.263765 0.5914336 -3.827590 1.294043e-04
## ENSG00000085117 184.93023 -2.928133 0.7515344 -3.896207 9.771093e-05
## ENSG00000168685 223.87569 -3.238513 0.7620463 -4.249758 2.140016e-05
## ENSG00000054356 582.50184 -3.355099 0.7490842 -4.478934 7.501678e-06
## ENSG00000106538 119.58744 -4.477485 1.0820654 -4.137906 3.504894e-05
## ENSG00000163131 287.73560 -4.515357 1.1171690 -4.041785 5.304587e-05
## ENSG00000147257 56.45761 -4.584485 1.2200271 -3.757691 1.714883e-04
## ENSG00000145335 77.49462 -6.046058 1.2741503 -4.745169 2.083324e-06
## ENSG00000116833 91.45527 -6.878210 1.5316509 -4.490717 7.098391e-06
## ENSG00000198744 119.99198 -6.883383 1.4042926 -4.901673 9.502392e-07
## padj symbol
## ENSG00000096696 2.689672e-02 DSP
## ENSG00000154529 3.013722e-02 CNTNAP3B
## ENSG00000180914 6.863341e-03 OXTR
## ENSG00000117586 6.636915e-05 TNFSF4
## ENSG00000134013 3.323816e-02 LOXL2
## ENSG00000092068 4.984303e-02 SLC7A8
## ENSG00000249992 2.767308e-03 TMEM158
## ENSG00000100376 1.406403e-04 FAM118A
## ENSG00000204650 6.749549e-03 LINC02210
## ENSG00000136859 5.931728e-03 ANGPTL2
## ENSG00000178184 1.015367e-02 PARD6G
## ENSG00000140285 2.279897e-02 FGF7
## ENSG00000164251 5.931728e-03 F2RL1
## ENSG00000122861 1.668552e-02 PLAU
## ENSG00000162631 3.529622e-02 NTNG1
## ENSG00000085117 3.013722e-02 CD82
## ENSG00000168685 1.086907e-02 IL7R
## ENSG00000054356 5.815379e-03 PTPRN
## ENSG00000106538 1.613237e-02 RARRES2
## ENSG00000163131 2.111656e-02 CTSS
## ENSG00000147257 4.354916e-02 GPC3
## ENSG00000145335 2.767308e-03 SNCA
## ENSG00000116833 5.808456e-03 NR5A2
## ENSG00000198744 1.399607e-03 MTCO3P12library(ComplexHeatmap)
library(RColorBrewer)
library(circlize)# col1 <- brewer.pal(9, "YlGnBu")#map values between b/w/r for min and max l2 values
col_logFC <- colorRamp2(c(min(l2_val), 0, max(l2_val)), c("blue", "white", "red"))
# map between 0% quantile and 75% quantile of mean values
col_AveExpr <- colorRamp2(c(quantile(mean)[1], quantile(mean)[4]), c("white", "red"))ha <- HeatmapAnnotation(summary = anno_summary(gp = gpar(fill = 2), height = unit(2, "cm")))
h1 <- Heatmap(mat.scaled[rows_keep,], cluster_rows = F, column_labels = colnames(mat.scaled), name = "Z-score", cluster_columns = T)
h2 <- Heatmap(l2_val, row_labels = df.top$symbol[rows_keep], cluster_rows = F, name = "logFC", top_annotation = ha, col = col_logFC, cell_fun = function(j, i, x, y, w, h, col){
grid.text(round(l2_val[i, j],2), x, y)
})
h3 <- Heatmap(mean, row_labels = df.top$symbol[rows_keep], cluster_rows = F, name = "AveExpr", col = col_AveExpr, cell_fun = function(j, i, x, y, w, h, col){
grid.text(round(mean[i,j],2), x,y)
})
h <- h1+h2+h3
h
png("./heatmap_v1.png", res = 300, width = 3000, height = 5500)
print(h)
dev.off()## png
## 2pdf("./heatmap_v1.pdf", width = 6, height = 9, pointsize = 6 )
print(h)
dev.off()sessionInfo()## R version 4.2.0 (2022-04-22 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 19044)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=English_United States.utf8
## [2] LC_CTYPE=English_United States.utf8
## [3] LC_MONETARY=English_United States.utf8
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.utf8
##
## attached base packages:
## [1] grid stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] circlize_0.4.15 RColorBrewer_1.1-3
## [3] org.Hs.eg.db_3.15.0 AnnotationDbi_1.58.0
## [5] ComplexHeatmap_2.12.1 ggplot2_3.3.6
## [7] DESeq2_1.36.0 SummarizedExperiment_1.26.1
## [9] Biobase_2.56.0 MatrixGenerics_1.8.1
## [11] matrixStats_0.62.0 GenomicRanges_1.48.0
## [13] GenomeInfoDb_1.32.2 IRanges_2.30.0
## [15] S4Vectors_0.34.0 BiocGenerics_0.42.0
##
## loaded via a namespace (and not attached):
## [1] bitops_1.0-7 bit64_4.0.5 doParallel_1.0.17
## [4] httr_1.4.3 tools_4.2.0 bslib_0.3.1
## [7] utf8_1.2.2 R6_2.5.1 DBI_1.1.3
## [10] colorspace_2.0-3 GetoptLong_1.0.5 withr_2.5.0
## [13] tidyselect_1.1.2 bit_4.0.4 compiler_4.2.0
## [16] cli_3.3.0 Cairo_1.5-15 DelayedArray_0.22.0
## [19] labeling_0.4.2 sass_0.4.1 scales_1.2.0
## [22] genefilter_1.78.0 stringr_1.4.0 digest_0.6.29
## [25] rmarkdown_2.14 XVector_0.36.0 pkgconfig_2.0.3
## [28] htmltools_0.5.2 highr_0.9 fastmap_1.1.0
## [31] rlang_1.0.3 GlobalOptions_0.1.2 rstudioapi_0.13
## [34] RSQLite_2.2.14 farver_2.1.0 shape_1.4.6
## [37] jquerylib_0.1.4 generics_0.1.2 jsonlite_1.8.0
## [40] BiocParallel_1.30.3 dplyr_1.0.9 RCurl_1.98-1.6
## [43] magrittr_2.0.3 GenomeInfoDbData_1.2.8 Matrix_1.5-3
## [46] Rcpp_1.0.8.3 munsell_0.5.0 fansi_1.0.3
## [49] lifecycle_1.0.1 stringi_1.7.6 yaml_2.3.5
## [52] zlibbioc_1.42.0 blob_1.2.3 parallel_4.2.0
## [55] crayon_1.5.1 lattice_0.20-45 Biostrings_2.64.0
## [58] splines_4.2.0 annotate_1.74.0 KEGGREST_1.36.2
## [61] locfit_1.5-9.5 knitr_1.39 pillar_1.7.0
## [64] rjson_0.2.21 geneplotter_1.74.0 codetools_0.2-18
## [67] XML_3.99-0.10 glue_1.6.2 evaluate_0.15
## [70] png_0.1-7 vctrs_0.4.1 foreach_1.5.2
## [73] gtable_0.3.0 purrr_0.3.4 clue_0.3-62
## [76] assertthat_0.2.1 cachem_1.0.6 xfun_0.31
## [79] xtable_1.8-4 survival_3.3-1 tibble_3.1.7
## [82] iterators_1.0.14 memoise_2.0.1 cluster_2.1.3
## [85] ellipsis_0.3.2