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trancriptVis 的左膀右臂: bedVis 和 trackVis

作者：很楠不爱3 | 2024-02-17 00:14:04

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igv collapse

我也曾经憧憬过

0d04ec103c6d60e24c2fcc1573ab1a0e.gif

introduction

here I introduced bedVis and trackVis functions to visualize peak files and bigwig files which work better with trancriptVis. You can use these functions to make a complex track plot with more ajustable parameters to control you graph produced.

Note:

all the test files can be downloaded from:

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE211475

1installation

  1. # install.packages("devtools")
  2. devtools::install_github("junjunlab/transPlotR")

bedVis

bedVis function can be used to visualize peaks data (bed format).

2examples

bed files:

  1. file <- list.files(pattern = '.bed')
  2. file
  3. # [1] "H524-NeuroD1_peaks.bed"  "H524-Promoter_peaks.bed" "H82-NeuroD1_peaks.bed"
  4. # [4] "H82-Promoter_peaks.bed"

choose the region and chromesome to be plotted:

  1. # plot
  2. bedVis(bdFile = file,
  3.        chr = "chr19",
  4.        region.min = 39875973,
  5.        region.max = 39919857)
c3c30d0695b542a5eec0e87db59d20bb.png

collapse the tracks:

  1. # collapse tracks
  2. bedVis(bdFile = file,
  3.        chr = "chr19",
  4.        region.min = 39875973,
  5.        region.max = 39919857,
  6.        collapse = TRUE)
6859177f60e77b6f60562865daa60d8a.png

change color:

  1. # change colors
  2. bedVis(bdFile = file,
  3.        chr = "chr19",
  4.        region.min = 39875973,
  5.        region.max = 39919857,
  6.        fill = ggsci::pal_d3()(4))
5561b78044e117432fc49841a6fbdd45.png

remove legend:

  1. # change to grey50 and turn off legend
  2. bedVis(bdFile = file,
  3.        chr = "chr19",
  4.        region.min = 39875973,
  5.        region.max = 39919857,
  6.        fill = rep('grey50',4),
  7.        show.legend = FALSE)
8659ea49f1b3381ef1365c23611391da.png

add peak name:

  1. # add label
  2. bd <-
  3. bedVis(bdFile = file,
  4.        chr = "chr19",
  5.        region.min = 39875973,
  6.        region.max = 39919857,
  7.        add.label = TRUE,label.column = 'name')
  8. bd
6950fff1e8c0834d1d0b5a19a334e078.png

3cases

you can combine with trancriptVis function:

  1. # combine
  2. gtf <- import('hg19.ncbiRefSeq.gtf',format = "gtf") %>%
  3.   data.frame()
  4.  
  5. p <-
  6.   trancriptVis(gtfFile = gtf,
  7.                Chr = "chr19",
  8.                posStart = 39875973,
  9.                posEnd = 39919857,
  10.                textLabel = "gene_name")
  11.  
  12. # combine
  13. p %>% insert_bottom(bd)
5f753ab70465179055d60857f312db74.png

here we can show the results in IGV:

652b3164fcda344a764ec865a5547daf.png

loadBigWig

loadBigWig function will load bigwig files and transform them into data.frame format.

4examples

  1. # test
  2. file <- list.files(pattern = '.bw')
  3. # [1] "H524-Input.bw"    "H524-NeuroD1.bw"  "H524-Promoter.bw" "H82-Input.bw"     "H82-NeuroD1.bw"
  4. # [6] "H82-Promoter.bw"
  5.  
  6. # read file
  7. mybw <- loadBigWig(file)
  8.  
  9. # check
  10. head(mybw,3)
  11. #   seqnames start   end width strand score   fileName
  12. # 1    chr19 74845 74945   101      *     1 H524-Input
  13. # 2    chr19 75000 75100   101      *     1 H524-Input
  14. # 3    chr19 80776 80876   101      *     1 H524-Input

trackVis

trackVis function can be used to visualize bigwig files in an elegant way. The trackVis will extend 3000bps upstream and downstream by defalut. You can set the extend.up/extend.dn to ajust a suitable value.

5examples

plot a region:

  1. # load data
  2. load('bWData.Rda')
  3. mybw <- bWData
  4.  
  5. # plot with specific region
  6. trackVis(bWData = mybw,
  7.          chr = "chr19",
  8.          region.min = 36226490,
  9.          region.max = 36269673)
80667b6ade9987f653a9864cd5a4e0a4.png

plot a specific gene:

  1. # load gtf
  2. gtf <- import('hg19.ncbiRefSeq.gtf',format = "gtf") %>%
  3.   data.frame()
  4.  
  5. # plot with specific gene
  6. trackVis(bWData = mybw,
  7.          gtf.file = gtf,
  8.          gene.name = "RAD23A")
579faf59392772865597d92de79186ac.png

here we show the same results in IGV:

b70c169be36796ae78c2db474388ee4d.png

show the color legend:

  1. # show legend
  2. trackVis(bWData = mybw,
  3.          chr = "chr19",
  4.          region.min = 36226490,
  5.          region.max = 36269673,
  6.          show.legend = TRUE)
244f5507946d115a08db6ffe8d7a8671.png

remove Y axis information:

  1. # remove axis info
  2. trackVis(bWData = mybw,
  3.          gtf.file = gtf,
  4.          gene.name = "RAD23A",
  5.          xAxis.info = FALSE,
  6.          yAxis.info = FALSE)
812cfb3239be0af3619dd28722c772a2.png

change a theme:

  1. # change theme
  2. trackVis(bWData = mybw,
  3.          gtf.file = gtf,
  4.          gene.name = "RAD23A",
  5.          yAxis.info = FALSE,
  6.          theme = "bw")
092940fdea4174ab1e35cf0097271031.png

change scales and layout:

  1. # free scales and draw two columns
  2. trackVis(bWData = mybw,
  3.          chr = "chr19",
  4.          region.min = 36226490,
  5.          region.max = 36269673,
  6.          scales = "free",
  7.          ncol = 2,
  8.          label.angle = 90)
a5c97e74b13a54b15617afb9052c3d1d.png

change track colors:

  1. # change color
  2. c1 <- trackVis(bWData = mybw,
  3.                gtf.file = gtf,
  4.                gene.name = "RAD23A",
  5.                color = ggsci::pal_npg()(6))
  6.  
  7. c2 <- trackVis(bWData = mybw,
  8.                gtf.file = gtf,
  9.                gene.name = "RAD23A",
  10.                color = rep('grey20',6))
  11.  
  12. c3 <- trackVis(bWData = mybw,
  13.                gtf.file = gtf,
  14.                gene.name = "RAD23A",
  15.                color = jjAnno::useMyCol(platte = "stallion",n = 6))
  16.  
  17. # combine
  18. cowplot::plot_grid(plotlist = list(c1,c2,c3),
  19.                    align = 'hv',ncol = 3)
fa62ea95708568db59909b3447d54c13.png

6highlight regions

sometimes we want to highlight some regions like peak site or modification site et. trackVis can also achive this. You just need to supply a list object include start and end coordinates.

mark three regions:

  1. # mark some regions
  2. trackVis(bWData = mybw,
  3.          chr = "chr19",
  4.          region.min = 36226490,
  5.          region.max = 36269673,
  6.          mark.region = list(c(36230500,36235000,36247500,36265000),
  7.                             c(36232800,36241000,36250000,36267000)))
a236bffe6bf604024c9a4f3b0a686d8a.png

ajust the color alpha:

  1. # change alpha
  2. trackVis(bWData = mybw,
  3.          chr = "chr19",
  4.          region.min = 36226490,
  5.          region.max = 36269673,
  6.          mark.region = list(c(36230500,36235000,36247500,36265000),
  7.                             c(36232800,36241000,36250000,36267000)),
  8.          mark.alpha = 0.2)
d75062c91e2d578914dc994f77424eb6.png

changing the marked regions color also is acceptable:

  1. # change color
  2. trackVis(bWData = mybw,
  3.          chr = "chr19",
  4.          region.min = 36226490,
  5.          region.max = 36269673,
  6.          mark.region = list(c(36230500,36235000,36247500,36265000),
  7.                             c(36232800,36241000,36250000,36267000)),
  8.          mark.alpha = 0.2,
  9.          mark.col = ggsci::pal_aaas()(4))
11f231a846b1cba534b40d460b9225c5.png

change a theme:

  1. # change theme
  2. trackVis(bWData = mybw,
  3.          chr = "chr19",
  4.          region.min = 36226490,
  5.          region.max = 36269673,
  6.          mark.region = list(c(36230500,36235000,36247500,36265000),
  7.                             c(36232800,36241000,36250000,36267000)),
  8.          mark.alpha = 0.2,
  9.          theme = "bw",yAxis.info = FALSE)
10f6eaade7e441e2a47b1f51a68d5a94.png

giving a gene name to plot with marked regions:

  1. # define gene name with mark region
  2. trackVis(bWData = mybw,
  3.          gtf.file = gtf,
  4.          gene.name = "RAD23A",
  5.          mark.region = list(c(13056500,13064000),
  6.                             c(13058400,13065000)),
  7.          mark.alpha = 0.2,
  8.          label.face = 'plain')
ef18403fbf95e1db69278ab30a3bdddd.png

7new style y axis

here I provide a new style Y axis which often ocurrs in papers, you can try this style.

add a new style Y axis:

  1. # add new y range
  2. trackVis(bWData = mybw,
  3.          chr = "chr19",
  4.          region.min = 36226490,
  5.          region.max = 36269673,
  6.          mark.region = list(c(36230500,36235000,36247500,36265000),
  7.                             c(36232800,36241000,36250000,36267000)),
  8.          mark.alpha = 0.2,
  9.          theme = "bw",yAxis.info = FALSE,
  10.          new.yaxis = TRUE)
301a50c5813246cc35262655e75a0245.png

you can ajust the pos.ration arg to palace the label:

  1. # ajust position
  2. trackVis(bWData = mybw,
  3.          chr = "chr19",
  4.          region.min = 36226490,
  5.          region.max = 36269673,
  6.          mark.region = list(c(36230500,36235000,36247500,36265000),
  7.                             c(36232800,36241000,36250000,36267000)),
  8.          mark.alpha = 0.2,
  9.          theme = "bw",yAxis.info = FALSE,
  10.          new.yaxis = TRUE,
  11.          pos.ratio = c(0.95,0.8))
26dcf12f4c91c7c53b0e49bfd439b2d6.png

8order

you can also change the plot orders through sample.order arg.

change the orders:

  1. # ajust order
  2. order <- c("H524-Input","H82-Input","H524-NeuroD1","H524-Promoter","H82-NeuroD1","H82-Promoter")
  3.  
  4. trackVis(bWData = mybw,
  5.          gtf.file = gtf,
  6.          gene.name = "RAD23A",
  7.          mark.region = list(c(13056500,13064000),
  8.                             c(13058400,13065000)),
  9.          mark.alpha = 0.2,
  10.          label.face = 'plain',
  11.          sample.order = order)
29538e8a38f6ab1f809adc6ef3047d52.png

9cases

let's see some cases working with other functions.

  1. ptrack <- trackVis(bWData = mybw,
  2.                    chr = "chr19",
  3.                    region.min = 36226490,
  4.                    region.max = 36269673)
  5.  
  6. trans <-
  7. trancriptVis(gtfFile = gtf,
  8.              Chr = "chr19",
  9.              posStart = 36226490 - 3000,
  10.              posEnd = 36269673 + 3000,
  11.              addNormalArrow = FALSE,
  12.              newStyleArrow = T,
  13.              absSpecArrowLen = T,
  14.              speArrowRelLen = 0.2,
  15.              textLabel = "gene_name",
  16.              textLabelSize = 3,
  17.              relTextDist = 0.5,
  18.              exonWidth = 0.9)
  19.  
  20. # combine
  21. ptrack %>% insert_bottom(trans,height = 0.75)
ce8655d05ce22bb67d342560b5573ab2.png

IGV:

cc4b7f8d76cf09b9535e9d1e5c80eb57.png

collapse the gene structures:

  1. trans <-
  2. trancriptVis(gtfFile = gtf,
  3.              Chr = "chr19",
  4.              posStart = 36226490 - 3000,
  5.              posEnd = 36269673 + 3000,
  6.              absSpecArrowLen = T,
  7.              speArrowRelLen = 0.2,
  8.              textLabel = "gene_name",
  9.              textLabelSize = 4,
  10.              relTextDist = 0.2,
  11.              exonWidth = 0.5,
  12.              collapse = T)
  13.  
  14. # combine
  15. ptrack %>% insert_bottom(trans,height = 0.1)
cac7bbd319333f2d03301de0dd55cbb1.png

supply with gene name:

  1. RAD23A <-
  2.   trackVis(bWData = mybw,
  3.            gtf.file = gtf,
  4.            gene.name = "RAD23A",
  5.            extend.up = 500,
  6.            extend.dn = 1000,
  7.            xAxis.info = F)
  8.  
  9. p <-
  10.   trancriptVis(gtfFile = gtf,
  11.                gene = "RAD23A",
  12.                relTextDist = -0.5,
  13.                exonWidth = 0.5,
  14.                exonColorBy = 'transcript_id',
  15.                textLabelSize = 4,
  16.                addNormalArrow = FALSE,
  17.                newStyleArrow = TRUE) +
  18.   xlab('')
  19.  
  20. # combine
  21. RAD23A %>% insert_bottom(p,height = 0.3)
1c6d405ba62902e2b486972c0d178efc.png

IGV shows:

8c1360602140b0ef68ee0a4a39864dd3.png

change transcript colors:

  1. # change transcript color
  2. p <-
  3.   trancriptVis(gtfFile = gtf,
  4.                gene = "RAD23A",
  5.                relTextDist = -0.5,
  6.                exonWidth = 0.5,
  7.                exonFill = 'black',
  8.                arrowCol = 'black',
  9.                textLabelSize = 3,
  10.                addNormalArrow = FALSE,
  11.                newStyleArrow = TRUE,
  12.                xAxis.info = FALSE,
  13.                textLabel = 'gene_name') +
  14.   xlab('')
  15.  
  16. # combine
  17. RAD23A %>% insert_bottom(p,height = 0.3)
4eaaa1553a06b26eb84e78dc49c594b1.png

let's combine track, gene and peak:

  1. # track + gene + peak
  2. RAD23A <-
  3.   trackVis(bWData = mybw,
  4.            gtf.file = gtf,
  5.            gene.name = "RAD23A",
  6.            extend.up = 500,
  7.            extend.dn = 1000,
  8.            xAxis.info = F,
  9.            theme = "bw",
  10.            yAxis.info = F,new.yaxis = T,
  11.            pos.ratio = c(0.06,0.8),
  12.            color = jjAnno::useMyCol(platte = "stallion",n = 6))
  13.  
  14. # peak
  15. bd <- bedVis(bdFile = file,
  16.              chr = "chr19",
  17.              track.width = 0.3,
  18.              show.legend = T)
  19.  
  20. # combine
  21. RAD23A %>% insert_bottom(p,height = 0.3) %>%
  22.   insert_bottom(bd,height = 0.15)
36686fefd65bb6ebe42115249b0301d5.png

end

if you have any advice or douts please leave words on:

  • https://github.com/junjunlab/transPlotR/issues.

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往期精品(点击图片直达文字对应教程)

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机器学习

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