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## Create mappability file for reference genome ## | |
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## Thomas Girke | |
## Date: May 16, 2018 | |
## PeakSeq docs: | |
## https://github.com/gersteinlab/PeakSeq | |
## http://gensoft.pasteur.fr/docs/PeakSeq/1.1/PeakSeq.readme | |
## Note: mappability step should be skipped in newer version of PeakSeq |
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################################################ | |
## Streaming through large tabular files in R ## | |
################################################ | |
## Author: Thomas Girke | |
## Last update: 21-Dec-2018 | |
## Utility: the function 'processFileInLineChunks' streams through a file in | |
## batches of lines and applies to each imported line batch a function assigned | |
## to the 'myFct' argument. The number of lines processed in each iteration can | |
## be defined under the 'n_rows' argument. As importer functions, both 'fread' |
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## Shiny App Example with Reactive URL Input ## | |
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## Author: Yuzhu Duan & Thomas Girke | |
## Last update: 06-Jul-17 | |
## Usage: save this file under name app.R to your shiny app directory, e.g. reactiveUrl | |
## Run in parent directory the following from within R: | |
## > library(shiny) | |
## > runApp(reactiveUrl) |
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## PWM matching in sequences ## | |
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## Date: May 22, 2020 | |
## Starter code for ChIP-Seq1 project | |
library(MotifDb) | |
as.list(query(MotifDb, 'athaliana')) | |
as.list(query(MotifDb, 'hsapiens')) |
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## Arranging plots with patchwork. For details see this manual page: https://ggplot2-book.org/arranging-plots.html | |
## Load libraries and create some sample data | |
library(ggplot2); library(reshape2); library(patchwork) | |
iris_mean <- aggregate(iris[,1:4], by=list(Species=iris$Species), FUN=mean) | |
df_mean <- melt(iris_mean, id.vars=c("Species"), variable.name = "Samples", value.name="Values") | |
## Create lots of plots | |
p1 <- ggplot(cbind(iris, Samples="Sepal.Length"), aes(Species, Sepal.Length)) + geom_boxplot(aes(fill = Species)) + ylim(4, 8) + theme(axis.title.x=element_blank(), axis.title.y=element_blank(), legend.position = "none") + facet_grid(rows = ~Samples) + ggtitle("(A)") + theme(plot.title = element_text(hjust=-0.3)) | |
p2 <- ggplot(df_mean[df_mean$Samples=="Sepal.Width",], aes(Species, Values)) + geom_bar(position="dodge", aes(fill = Species), stat="identity") + yli |
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