| Title: | Turner Miscellaneous |
| Version: | 1.0.1 |
| Maintainer: | Stephen Turner <vustephen@gmail.com> |
| Description: | Miscellaneous utility functions for data manipulation, data tidying, and working with gene expression data. |
| URL: | https://github.com/stephenturner/Tmisc, https://stephenturner.github.io/Tmisc/ |
| Depends: | R (≥ 3.1.2) |
| Imports: | dplyr, tibble, utils, rstudioapi, methods, magrittr, stats |
| License: | GPL-3 |
| LazyData: | true |
| RoxygenNote: | 7.2.3 |
| Suggests: | ggplot2, reshape2 |
| NeedsCompilation: | no |
| Packaged: | 2023-08-22 21:05:41 UTC; turner |
| Author: | Stephen Turner 
[aut, cre] |
| Repository: | CRAN |
| Date/Publication: | 2023-08-23 00:10:12 UTC |
Tmisc: Turner Miscellaneous
Description
Miscellaneous utility functions for data manipulation, data tidying, and working with gene expression data.
Author(s)
Maintainer: Stephen Turner vustephen@gmail.com (ORCID)
See Also
Useful links:
Pipe operator
Description
See magrittr::%>% for details.
Usage
lhs %>% rhs
x like y
Description
Returns a logical vector of elements of x matching the regex y.
Usage
x %like% pattern
Arguments
x |
a vector (numeric, character, factor) |
pattern |
a vector (numeric, character, factor), matching the mode of x |
Value
A logical vector with length equal to x of things in x that are like y.
See Also
Examples
(Name <- c("Mary","George","Martha"))
Name %in% c("Mary")
Name %like% "^Mar"
Name %nin% c("George")
Name %nlike% "^Mar"
x not in y
Description
Returns a logical vector of elements of x that are not in y.
Usage
x %nin% table
Arguments
x |
a vector (numeric, character, factor) |
table |
a vector (numeric, character, factor), matching the mode of x |
Value
A logical vector with length equal to x of things in x that aren't in y.
See Also
Examples
1:10 %nin% seq(from=2, to=10, by=2)
c("a", "b", "c") %nin% c("a", "b")
letters[letters %nin% unlist(strsplit("pack my box with five dozen liquor jugs", ""))]
x not like y
Description
Returns a logical vector of elements of x not matching the regex y.
Usage
x %nlike% pattern
Arguments
x |
a vector (numeric, character, factor) |
pattern |
a vector (numeric, character, factor), matching the mode of x |
Value
A logical vector with length equal to x of things in x that aren't like y.
See Also
Examples
(Name <- c("Mary","George","Martha"))
Name %in% c("Mary")
Name %like% "^Mar"
Name %nin% c("George")
Name %nlike% "^Mar"
Mode.
Description
Returns the mode of a vector. First in a tie wins (see examples).
Usage
Mode(x, na.rm = FALSE)
Arguments
x |
A vector. |
na.rm |
Remove missing values before calculating the mode (FALSE by default). NAs are counted just like any other element. That is, an NA in the vector won't necessarily result in a return NA. See the first example. |
Value
A combined p-value.
Examples
Mode(c(1,2,2,3,3,3, NA))
Mode(c(1,2,2,3,3,3, NA), na.rm=TRUE)
Mode(c(1,2,2,3,3,3, NA, NA, NA, NA))
Mode(c(1,2,2,3,3,3, NA, NA, NA, NA), na.rm=TRUE)
Mode(c("A", "Z", "Z", "B", "B"))
A palette of 17 diverging colors
Description
17 diverging colors created by combining the Set1 and Dark2 palettes from RColorBrewer.
Usage
Tcols
Format
Vector of 17 diverging colors.
Source
R Color brewer: c(brewer.pal(9, "Set1"), brewer.pal(8, "Dark2")).
Examples
## Not run:
barplot(rep(1, 17), col=Tcols, axes=F, names=c(rep("Set1", 9), rep("Dark2", 8)), horiz=TRUE, las=2)
## End(Not run)
Histograms with overlays
Description
Plot a histogram with either a normal distribution or density curve overlay.
Usage
Thist(x, overlay = "normal", col = "gray80", ...)
Arguments
x |
A numeric vector. |
overlay |
Either "normal" (default) or "density" indicating whether a normal distribution or density curve should be plotted on top of the histogram. |
col |
Color of the histogram bars. |
... |
Other arguments to be passed to |
Examples
set.seed(42)
x <- rnorm(1000, mean=5, sd=2)
Thist(x)
Thist(x, overlay="density")
Thist(x^2)
Thist(x^2, overlay="density", breaks=50, col="lightblue2")
Better scatterplot matrices.
Description
A matrix of scatter plots with rugged histograms, correlations, and significance stars. Much of the functionality borrowed from PerformanceAnalytics::chart.Correlation().
Usage
Tpairs(x, histogram = TRUE, gap = 0, ...)
Arguments
x |
A numeric matrix or data.frame. |
histogram |
Overlay a histogram on the diagonals? |
gap |
distance between subplots, in margin lines. |
... |
arguments to be passed to or from other methods. |
Examples
Tpairs(iris[-5])
Tpairs(iris[-5], pch=21, bg=Tcols[factor(iris$Species)])
Tpairs(iris[-5], pch=21, bg=gghues(3)[factor(iris$Species)], gap=1)
Insert text at current position.
Description
Call these function as an addin to insert desired text at the cursor position. After installing Tmisc, hit the Addins menu, and optionally add a keyboard shortcut, e.g., Command+Shift+I, Alt+-, etc.
Are all equal?
Description
Are all the elements of a numeric vector (approximately) equal?
Usage
are_all_equal(x, na.rm = FALSE)
Arguments
x |
A numeric vector. |
na.rm |
Remove missing values (FALSE by default; NAs in x will return NA). |
Value
Logical, whether all elements of a numeric vector are equal.
Examples
are_all_equal(c(5,5,5))
are_all_equal(c(5,5,5,6))
are_all_equal(c(5,5,5,NA,6))
are_all_equal(c(5,5,5,NA,6), na.rm=TRUE)
5==5.000000001
identical(5, 5.000000001)
are_all_equal(c(5L, 5, 5.000000001))
Print the top left corner of a data frame
Description
Prints the first n rows and columns of a data frame or matrix.
Usage
corner(x, n = 5)
Arguments
x |
A data.frame. |
n |
The number of rows/columns to print. |
Value
The corner of the data frame
Examples
corner(mtcars)
corner(iris, n=4)
Fragments per kilobase per million
Description
Takes a count matrix and a vector of gene lengths and returns an optionally log2-transformed FPKM matrix. Modified from edgeR.
Usage
counts2fpkm(x, length, log = FALSE, prior.count = 0.25)
Arguments
x |
a matrix of counts |
length |
a vector of length |
log |
logical, if |
prior.count |
average count to be added to each observation to avoid
taking log of zero. Used only if |
Value
A matrix of FPKM values.
Examples
## Not run:
library(readr)
library(dplyr)
countdata <- read_csv("http://files.figshare.com/2439061/GSE37704_featurecounts.csv")
counts <- countdata %>% select(countdata, starts_with("SRR")) %>% as.matrix
counts2fpkm(counts, countdata$length)
## End(Not run)
Create tables in dokuwiki format
Description
Prints the supplied data frame or matrix using Dokuwiki's table syntax, optionally copying the data to the clipboard (Mac OS X only).
Usage
dokuwiki(x, headersep = "^", sep = "|", clip = TRUE, ...)
Arguments
x |
A data.frame. |
headersep |
The separator used between entries in the header row. |
sep |
The separator used between entries in all other rows. |
clip |
Whether or not to write the returned table to the clipboard (currently only supported on Mac OS X). |
... |
Further arguments passed to |
Examples
dokuwiki(head(iris), clip=FALSE)
dokuwiki(head(mtcars), clip=FALSE, row.names=TRUE)
Truncate a data frame with ellipses.
Description
Prints the specified number of rows of a data frame, followed by a row of ellipses. Useful for piping to knitr::kable() for printing a truncated table in a markdown document.
Usage
ellipses(df, n = 5L)
Arguments
df |
A data.frame. |
n |
The number of rows to show before an ellipses row. |
Value
A data frame truncated by a row of ellipses.
Examples
## Not run:
ellipses(mtcars, 5)
## End(Not run)
Fisher's method to combine p-values.
Description
Uses Fisher's method to combine p-values from different tests.
Usage
fisherp(x)
Arguments
x |
A vector of p-values between 0 and 1. |
Value
A combined p-value.
Examples
fisherp(c(.042, .02, .001, 0.01, .89))
Plot missing data
Description
Plots missing data as holes on a black canvas.
Usage
gg_na(df)
Arguments
df |
A data.frame. |
Examples
# What a mess.
# Feature 10 is missing a lot. Observations 25 and 35 are completely missing.
# Most of features 40-45 are missing, except for the first few observations.
set.seed(2016-07-12)
x <- matrix(1, nrow=50, ncol=50)
x[sample(prod(dim(x)), 100)] <- NA
x <- data.frame(x)
x$X10[sample(length(x$X10), 25)] <- NA
x[c(25, 35), ] <- NA
x[1:40, 40:45] <- NA
gg_na(x)
Emulate ggplot2 default hues
Description
This will emulate ggplot2's hues, which are equally spaced hues around the color wheel, starting from 15.
Usage
gghues(n, start = 15)
Arguments
n |
The Numeric; number of hues to generate. |
start |
Numeric; the place on the color wheel to start. ggplot2 default is 15. |
Value
A vector of hues
Examples
n <- 10
gghues(3)
barplot(rep(1,n), col=gghues(n), names=gghues(n))
barplot(rep(1,n), col=gghues(n, start=15+180), names=gghues(n, start=15+180))
Two-letter genotype from VCF GT
Description
Get a two-letter genotype from a VCF GT field. Current implementation is quick and dirty, and only accepts 0/0, 0/1, or 1/1. Any other input to gt will return a missing value.
Usage
gt2refalt(gt, ref, alt)
Arguments
gt |
The genotype field (must be 0/0, 0/1, or 1/1). |
ref |
The reference allele. |
alt |
The alternate allele. |
Value
Returnvalue
Examples
gt2refalt(gt="0/0", ref="R", alt="A")
gt2refalt(gt="0/1", ref="R", alt="A")
gt2refalt(gt="1/1", ref="R", alt="A")
gt2refalt(gt="0/2", ref="R", alt="A")
gt2refalt(gt="./.", ref="R", alt="A")
Jensen-Shannon divergence
Description
Calculates a distance matrix from a matrix of probability distributions using Jensen-Shannon divergence. Adapted from https://enterotype.embl.de/enterotypes.html#dm.
Usage
jsd(M, pseudocount = 1e-06, normalizeCounts = FALSE)
Arguments
M |
a probability distribution matrix, e.g., normalized transcript compatibility counts. |
pseudocount |
a small number to avoid division by zero errors. |
normalizeCounts |
logical, whether to attempt to normalize by dividing by the column sums. Set to |
Value
A Jensen-Shannon divergence-based distance matrix.
Examples
set.seed(42)
M <- matrix(rpois(100, lambda=100), ncol=5)
colnames(M) <- paste0("sample", 1:5)
rownames(M) <- paste0("gene", 1:20)
Mnorm <- apply(M, 2, function(x) x/sum(x))
Mjsd <- jsd(Mnorm)
# equivalently
Mjsd <- jsd(M, normalizeCounts=TRUE)
Mjsd
plot(hclust(Mjsd))
Linear model p-value
Description
Extract F-test p-value from a linear model object. Can also use broom::glance(fit).
Usage
lmp(modelobject)
Arguments
modelobject |
A model object of class |
Value
The p-value on the f-test of a linear model object testing the null hypothesis that R^2==0.
Examples
# simulate some (e.g. SNP genotype) data
set.seed(42)
n=20
d=data.frame(x1=rbinom(n,2,.5), x2=rbinom(n,2,.5))
d=transform(d, y=x1+x2+rnorm(n))
#fit the linear model
fit=lm(y ~ x1 + x2, data=d)
#shows that the F-test is 0.006641
summary(fit)
#can't access that p-value using this
names(summary(fit))
# this doesn't work either
names(fit)
lmp(fit)
Lowest nonzero values
Description
Sometimes want to plot p-values (e.g., volcano plot or MA-plot), but if a statistical test returns a zero p-value, this causes problems with visualization on the log scale. This function returns a vector where the zero values are equal to the smallest nonzero value in the vector.
Usage
lowestnonzero(x)
Arguments
x |
A vector of p-values between 0 and 1. |
Value
A vector of p-values where zero values are exchanged for the lowest non-zero p-value in the original vector.
Examples
lowestnonzero(c(.042, .02, 0, .001, 0, .89))
Improved list of objects
Description
Improved list of objects. Sorts by size by default. Adapted from https://stackoverflow.com/q/1358003/654296.
Usage
lsa(
pos = 1,
pattern,
order.by = "Size",
decreasing = TRUE,
head = TRUE,
n = 10
)
Arguments
pos |
numeric. Position in the stack. |
pattern |
Regex to filter the objects by. |
order.by |
character. Either 'Type', 'Size', 'PrettySize', 'Rows', or 'Columns'. This will dictate how the output is ordered. |
decreasing |
logical. Should the output be displayed in decreasing order? |
head |
logical. Use head on the output? |
n |
numeric. Number of objects to display is head is TRUE. |
Value
A data.frame with type, size in bytes, human-readable size, rows, and columns of every object in the environment.
Author(s)
Dirk Eddelbuettel, Tony Breyal
Examples
## Not run:
a <- rnorm(100000)
b <- matrix(1, 1000, 100)
lsa()
## End(Not run)
Matrix to pairwise data frame
Description
Turns a distance matrix into a data frame of pairwise distances.
Usage
mat2df(M)
Arguments
M |
a square pairwise matrix (e.g., of distances). |
Value
Data frame with pairwise distances.
Examples
set.seed(42)
M <- matrix(rnorm(25), nrow=5)
M
mat2df(M)
M <- matrix(rnorm(25), nrow=5, dimnames=list(letters[1:5], letters[1:5]))
M
mat2df(M)
Get names and class of all columns in a data frame
Description
Get names and class of all columns in a data frame in a friendly format.
Usage
nn(df)
Arguments
df |
A data.frame. |
Value
A data.frame with index and class.
Author(s)
Stephen Turner
Examples
nn(iris)
Open the current working directory on mac
Description
Opens the current working directory on mac.
Usage
o()
Examples
## Not run:
o()
## End(Not run)
Peek at the top of a text file
Description
This returns a character vector which shows the top n lines of a file.
Usage
peek(x, n = 5)
Arguments
x |
a filename |
n |
the number of lines to return |
Examples
## Not run:
filename <- tempfile()
x<-matrix(round(rnorm(10^4),2),1000,10)
colnames(x)=letters[1:10]
write.csv(x,file=filename,row.names=FALSE)
peek(filename)
## End(Not run)
Anscombe's Quartet data (tidy)
Description
Tidy version of built-in Anscombe's Quartet data. Four datasets that have nearly identical linear regression properties, yet appear very different when graphed.
Usage
quartet
Format
Data frame with columns.
Read from the clipboard
Description
Read tabular data from the clipboard.
Usage
read.cb(header = TRUE, ...)
Arguments
header |
A logical value indicating whether the file contains the names of the variables as its first line. Overrides the default |
... |
Further arguments to be passed to |
Value
A data.frame
Examples
## Not run:
# To read CSV data with a header from the clipboard:
read.cb(header=TRUE, sep=',')
## End(Not run)
Rename objects while saving.
Description
Allows you to rename objects as you save them. See https://stackoverflow.com/a/21248218/654296.
Allows you to rename objects as you save them. See https://stackoverflow.com/a/21248218/654296.
Usage
saveit(..., file = stop("'file' must be specified"))
saveit(..., file = stop("'file' must be specified"))
Arguments
... |
Objects to save. |
file |
Filename/path where data will be saved. |
Examples
## Not run:
foo <- 1
saveit(bar=foo, file="foobar.Rdata")
## End(Not run)
## Not run:
foo <- 1
saveit(bar=foo, file="foobar.Rdata")
## End(Not run)
Write sessionInfo to the clipboard
Description
Writes output of sessionInfo() to the clipboard. Only works on Mac.
Usage
sicb()
Examples
## Not run:
# Write sessionInfo() to the clipboard on mac.
sicb()
## End(Not run)
Sort characters in a string
Description
Alphabetically sorts characters in a string. Vectorized over x.
Usage
strSort(x)
Arguments
x |
A string to sort. |
Value
A sorted string.
Examples
strSort("cba")
strSort("zyxcCbB105.a")
strSort(c("cba", "zyx"))
strSort(c("cba", NA))