Package 'handyFunctions'

check the validation and return index of cols given from input in rawDataFrame

Description

check the validation and return index of cols given from input in rawDataFrame

Usage

checkCols(rawDataFrame, cols)

Arguments

rawDataFrame	raw data.frame
cols	specific cols given from input

Value

return validation (only FALSE if invaild cols input) or index of cols

Examples

library(handyFunctions)
data(people)
checkCols(people, c("..name", "..sex"))
# OR
checkCols(people, c(1, 2))

---

Return suggested dtype of vector input

Description

Return suggested dtype of vector input

Usage

checkDtype(vector)

Arguments

vector

vector/list input

Value

Return suggested dtypes of vector

Examples

library(handyFunctions)
vector <- c(1, 2, 3, "", NA, "  ", "four", "NA", 5)
checkDtype(vector)

---

Grade records of virtual persons in high school

Description

A dataset containing the personal grade information (chinese, math, english, physics, biology, chemistry) of virtual persons.

Usage

grade

Format

A data frame with 6 rows and 7 variables:

name

name, chinese or foreigner, in carats

chinese

grade of the chinese, in numbers

math

grade of the math, in numbers

english

grade of the english, in numbers

physics

grade of the physics, in numbers

biology

grade of the biology, in numbers

chemistry

grade of the chemistry, in numbers

...

Source

"simulated dataset"

---

Return the index of source vector matched with query vector

Description

Return the index of source vector matched with query vector

Usage

matchIndex(SourceInfo, queryInfo, queryType = TRUE)

Arguments

SourceInfo	the source vector
queryInfo	the query vector
queryType	logical If set it to accurate match (default: TRUE)

Value

the index of source vector matched with query vector

Examples

library(handyFunctions)
data(grade)
matchIndex(grade[, "name"], c("Ming Li", "Bang Wei"))

---

merge two data.frame based on xcol and ycol

Description

merge two data.frame based on xcol and ycol

Usage

mergeCustom(x, y, xcol, ycol)

Arguments

x	the first data.frame
y	the second data.frame
xcol	colnames which you want to merged in first data.frame
ycol	colnames which you want to merged in second data.frame

Value

return the new data.frame merged

Examples

library(handyFunctions)
data(people)
data(grade)
mergeCustom(people, grade, "..name", "name")

---

Return reformatted data.frame with standard col names

Description

Return reformatted data.frame with standard col names

Usage

modifyColNames(rawDataFrame, cols = TRUE, rawSep = "..", sep = "_")

Arguments

rawDataFrame	Raw data.frame input
cols	Specific col names or indexes what you want to reformat (default: TRUE, use all cols)
rawSep	Raw odd separation symbol in col names of raw data.frame. Note: it supports regEx (regular expression), so "." means all possible symbols. If you want to use the "." dot notation, please use "[.]".
sep	Separation symbol in col names of modified data.frame

Value

A modified data.frame with col names separated by your given delimitator

Examples

library(handyFunctions)
data(people)
modified_people <- modifyColNames(people,rawSep = "[.][.]")

---

Return suggested appropriate dtypes for each column in rawDataFrame

Description

Return suggested appropriate dtypes for each column in rawDataFrame

Usage

modifyColTypes(rawDataFrame, cols = TRUE, dtype = FALSE, custom = FALSE)

Arguments

rawDataFrame	Raw data.frame
cols	Specify cols which you want to change its dtypes when custom is FALSE (default: TRUE, for all cols)
dtype	Specify indexed matched dtypes whcih you want to update when custom is FALSE (default: FALSE, for automatically update)
custom	Option whether set to auto/custom , you can specify your custom dtypes for cols given when setting to TRUE (default: FALSE, for auto)

Value

Return a new data.frame with appropriate dtypes suggested for each cols

Examples

library(handyFunctions)
data(people)
modifyColTypes(people)

---

Return reformatted data.frame with standard row names

Description

Return reformatted data.frame with standard row names

Usage

modifyRowNames(rawDataFrame, rows = TRUE, rawSep = "..", sep = "_")

Arguments

rawDataFrame	Raw data.frame input
rows	Specific row names or indexes what you want to reformat (default: TRUE, use all row)
rawSep	Raw odd separation symbol in row names of raw data.frame. Note: it supports regEx (regular expression), so "." means all possible symbols. If you want to use the "." dot notation, please use "[.]".
sep	Separation symbol in row names of modified data.frame

Value

A modified data.frame with row names separated by your given delimitator

Examples

library(handyFunctions)
data(people)
modifyRowNames(people)

---

Basic information of virtual persons

Description

A dataset containing the personal basic information (name, sex, age, and death_age) of virtual persons.

Usage

people

Format

A data frame with 6 rows and 4 variables:

..name

name, chinese or foreigner, in carats

..sex

sex of the person, in carats

..age

living age in final record, in numbers

..death..age

final age when a person is dead, in numbers

...

Source

"simulated dataset"

---

return index of x data.frame with the given vector/list or ycol in data.frame (if set the accurate match or not)

Description

return index of x data.frame with the given vector/list or ycol in data.frame (if set the accurate match or not)

Usage

queryingInfo(SourceData, sourceCol, queryCol, queryInfo, queryType = TRUE)

Arguments

SourceData	the source data.frame which you want to query
sourceCol	the col names or index of query field in source data.frame
queryCol	the col names or index of return field in source data.frame
queryInfo	vector/list the query info
queryType	logical if set it to accurate match (default: TRUE)

Value

a vector in query field matched with query info in source data

Examples

library(handyFunctions)
data(grade)
queryingInfo(grade, "name", "chinese", c("Ming Li", "Bang Wei"))

---

Function of showing SNP density at chromosome level

Description

Function of showing SNP density at chromosome level

Usage

ShowSNPDensityPlot(
  densityData,
  binSize,
  densityColorBar = c("grey", "darkgreen", "yellow", "red"),
  chromSet = c(1:22),
  withchr = FALSE
)

Arguments

densityData	the raw density data generated from vcftools
binSize	the bin size set while generating density data
densityColorBar	vector Specific the color bar for plotting density plot (generally four colors)
chromSet	vector Filtered chrom set which you want to plot (it must be matched with the CHROM column in densityData)
withchr	logical If the chromsome labels of density plot is prefixed with "chr". Note: it cannot work when the filtered chrom set contain other uncommon chrom symbols (e.g. NC0*, etc)

Value

A ggplot2 object for SNP density plot

Examples

library(handyFunctions)
data(SNV_1MB_density_data)
ShowSNPDensityPlot(SNV_1MB_density_data, binSize = 1e6, chromSet = c(38:1))

---

The SNPV number within 1Mb bins at chromosome levels generated from transcriptome dataset of two dog populations (including wild wolf and domesticated dogs).

Description

A dataset containing the SNV number within 1Mb bins called from transcriptome dataset of wild wolf and domesticated dogs.

Usage

SNV_1MB_density_data

Format

A data frame with 2544 rows and 4 variables:

CHROM

chrom id, reference genome of CanFam3.1, in numbers/carats

BIN_START

the start genomic coordinate for one bin at relevant chromosome, in numbers

SNP_COUNT

the end genomic coordinate for one bin at relevant chromosome, in numbers

VARIANTS.KB

SNV(variants) number within one bin per KB, in numbers

...

Source

"real dataset"

---

Return specific-indexed vector according to given delimitator/separator by splitting one col in data.frame

Description

Return specific-indexed vector according to given delimitator/separator by splitting one col in data.frame

Usage

splitCol(data, col = FALSE, sep, index, fixed = TRUE)

Arguments

data	vector or data.frame input
col	the col names or indexes if data.frame input
sep	separation deliminator
index	the index of symbol which you want
fixed	logical. If TRUE match split exactly, otherwise use regular expressions, detailed info can be seen in strsplit.

Value

specific-indexed vector or factor

Examples

library(handyFunctions)
data(people)
splitCol(people, col = 1, sep = " ", index = 2)

---

Reformat dataframe with the all modifiers simultaneously (colNames, rowNames and dtypes)

Description

Reformat dataframe with the all modifiers simultaneously (colNames, rowNames and dtypes)

Usage

unifyDataframe(
  rawDataFrame,
  rawRowSep = "..",
  rowSep = "_",
  rawColSep = "..",
  colSep = "_",
  changeDtype = TRUE
)

Arguments

rawDataFrame	raw data.frame
rawRowSep	raw separation deliminator of row names in raw data.frame
rowSep	the new separation deliminator of row names
rawColSep	raw separation deliminator of col names in raw data.frame
colSep	the new separation deliminator of col names
changeDtype	if change the dtypes of cols

Value

A modified data.frame with applied to above all modifiers

Examples

library(handyFunctions)
data(people)
unifyDataframe(people,rawColSep = "[.][.]")

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