Example of a MIACCS File entry for FASTQ files

Example of a MIACCS File entry for Read-Count files

data.extract()

Usage:
data.extract(scriptpath=NULL, datapath=NULL, fastqfile=NULL, extract = FALSE, pattern = "default", maschinepattern = "default", createindex = FALSE, bowtie2file = NULL, referencefile= NULL, mapping = FALSE, reversecomplement = FALSE, threads = 1, bowtieparams = "", sensitivity = "very-sensitive-local", match = "perfect")

scriptpath
Absolute path of the folder that contains CRISPR-extract.pl and CRISPR-mapping.pl
Default NULL
Values absolute path (character)

datapath
Absolute path of the folder that contains the data files (e.g. file.FASTQ)
Default NULL
Values absolute path (character)

fastqfile
Filename of FASTQ file WITHOUT .fastq extension
Default NULL
Values filename (character)

extract
Whether CRISPR-extract.pl is used to extract the 20 nt target sequence from the NGS reads using pattern Default FALSE
Values TRUE, FALSE (boolean)

pattern
PERL regular Expression to extract 20 nt target sequence from NGS reads. Please see extract pattern in this manual for more information.
Default Regular Expression (character)

machinepattern
Machine ID of your Sequencing machine. Used to identify the read id.

createindex
Do you want caRpools to generate a bowtie2 index? Only necessary if mapping=TRUE. Default FALSE
Values TRUE, FALSE

bowtie2file
Filename of bowtie2 index file, without extension. Is the same as reference file, if createindex=TRUE.

referencefile
Filename of the library reference FASTA file, without extension. Is the same as bowtie2 file, if createindex=TRUE.

mapping
Indicates whether FASTQ files need to be mapped against referencefile/bowtie2file. FALSE by default.
Default FALSE
Values TRUE, FALSE

reversecomplement
Is the NGS sequence in reverse complement order?
Default FALSE
Values TRUE, FALSE

threads
How many threads can bowtie2 use for mapping? Only used if mapping=TRUE. Usually cores of CPU.
Default 2
Values any integer

bowtieparams
If you want to pass additional parameters to bowtie2.

sensitivity
You can adjust the sensitivity of bowtie2 using this parameter. By default, bowtie2 is used in a very-sensitive-local setting. More information about different sensitivity parameters can be found at the bowtie2 options.
Default “very-sensitive-local”
Other options: very-fast, fast, sensitive, very-fast-local, fast-local, sensitive-local

match
After bowtie2 mapping, the alignment is converted into read count files filename_extracted-design.txt and filename_extracted-genes.txt.
You can indicate how well the alignment must be in order to be used for generating the read count for each sgRNA.
By default, this is set to perfect, which only employs a mapped read if the full 20 nt from the sequencing match perfectly to the sgRNA found in your library reference. The following options can be used:

• perfect - Read is used of all 20 nt from the sequencing are matching the target sequence given in the library reference
• high - Read is used if at least 18 nt (starting from the PAM) are matching the target sequence in the reference
• seed - Read is used if at least 14 nt (starting from the PAM) are a perfect match against the target sequence in the reference

aggregatetogenes()

Usage
aggregatetogenes(data.frame, namecolumn=1, countcolumn=2, agg.function=sum, extractpattern=expression("^(.+?)_.+"), type="aggregate")

data.frame
A data-frame of sgRNA read-count data as done by load.file
Default empty
Values data-frame

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

countcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

type
CaRpools can either aggregate the data frame (type = "annotate") or annotate the gene identifiers only as an additional column (type = "annotate").
Default “aggregate”
Values “aggregate”, “annotate”

CONTROL1.g=aggregatetogenes(data.frame = CONTROL1, agg.function=sum,
            extractpattern = expression("^(.+?)(_.+)"), type="aggregate")
knitr::kable(CONTROL1.g[1:10,])

CONTROL1.g.annotate=aggregatetogenes(data.frame = CONTROL1, agg.function=sum,
            extractpattern = expression("^(.+?)(_.+)"), type="annotate")
knitr::kable(CONTROL1.g.annotate[1:10,])

get.gene.info()

Usage
get.gene.info = function(data, namecolumn=1, extractpattern=expression("^(.+?)(_.+)"), host="www.ensembl.org", database="ensembl", dataset="hsapiens_gene_ensembl", filters="ensembl_gene_id", attributes = c("hgnc_symbol"), return.val = "dataset", controls=FALSE)

data Data frame that contains read-count data. Default none Values data.frame containing read-count data (data.frame)

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

host
The host which is used to retrieve biomaRt information.
Default “www.ensembl.org”
Values See biomaRt website for further information.

database
BiomaRt database to be used. See ?listMarts() or biomaRt documentation.
Default “ENSEMBL_MART_ENSEMBL”, is using the ensembl database
Values Any biomaRt database (character)

dataset
The biomaRt data-set to be used. For homo sapiens, hsapiens_gene_ensembl is recommended. See ?listDatasets or biomaRt documentation.
Default “hsapiens_gene_ensembl”
Values Any biomaRt dataset (character)

filters
The input filter information to retrieve biomaRt annotation, usually is the type of gene identifier used in the read-count files, e.g. “ensemble_gene_id”. see ?listFilters
Default “ensembl_gene_id”
Values Any biomaRt filter (character)

attributes
The output attribute to retrieve from biomaRt, usually the annotations that need to be fetched, e.g. “hgnc_symbol”. see ?listAttributes
Default “hgnc_symbol”
Values Any biomaRt attribute (character)

return.val
The type of object that is returned. For whole data-set, e.g. conversion of gene identifiers, use “dataset”.
Default “dataset”
Values “dataset” (will give back the same data frame, but with exchanged gene identifiers), “info” (will return a data frame with all attributes fetched for genes, is used to annotate gene with additional information)

controls
Is set to TRUE if data is not a data frame, but a vector.
Default FALSE
Values TRUE, FALSE (boolean)

CONTROL1.replaced = get.gene.info(CONTROL1, namecolumn=1, host="www.ensembl.org",
      extractpattern=expression("^(.+?)(_.+)"), database="ENSEMBL_MART_ENSEMBL", dataset="hsapiens_gene_ensembl",
      filters="hgnc_symbol", attributes =c("ensembl_gene_id"), return.val = "dataset")

## Creating a generic function for 'nchar' from package 'base' in package 'S4Vectors'

knitr::kable(CONTROL1.replaced[1:10,])

CONTROL1.replaced.info = get.gene.info(CONTROL1, namecolumn=1, host="www.ensembl.org",
      extractpattern=expression("^(.+?)(_.+)"), database="ENSEMBL_MART_ENSEMBL", dataset="hsapiens_gene_ensembl",
      filters="hgnc_symbol", attributes = c("ensembl_gene_id","description"), return.val = "info")

knitr::kable(CONTROL1.replaced.info[1:10,])

stats.data()

Usage
stats.data = (dataset, namecolumn = 1, fullmatchcolumn = 2, extractpattern=expression("^(.+?)_.+"), readcount.unmapped.total = NA, controls.target = NULL, controls.nontarget = "random", type="stats")

dataset
Data frame of read-count object.
Default none
Values data frame as created by load.file()

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

readcount.unmapped.total
Number of raw NGS reads, only used if type="mapping.
Default NA
Values Number of raw reads (integer)

controls.target
If type="controls", this is the gene identifier of the positive control.
Default NULL
Value Gene Identifier (character)

controls.nontarget
If type="controls", this is the gene identifier of the non-targeting control.
Default “random”
Value Gene Identifier (character)

type
Which type of statistic will be generated.
Default “stats”
Values “stats” will generate short statistics like median and mean for the data set, “mapping” will generate an overview of how many reads are present, “dataset” is used to generate in-depth statistics for each gene of a dataset, “controls” is used for in-depth statistics of the controls.

knitr::kable(stats.data(dataset=CONTROL1, namecolumn = 1, fullmatchcolumn = 2,
  extractpattern=expression("^(.+?)_.+"), readcount.unmapped.total = 1786217, type="mapping"))

knitr::kable(stats.data(dataset=CONTROL1, namecolumn = 1, fullmatchcolumn = 2,
  extractpattern=expression("^(.+?)_.+"), readcount.unmapped.total = 1786217,
  type="stats"))

knitr::kable(stats.data(dataset=CONTROL1, namecolumn = 1, fullmatchcolumn = 2,
  extractpattern=expression("^(.+?)_.+"), readcount.unmapped.total = 1786217,
  type="dataset")[1:10,1:5])

unmapped.genes()

Usage
unmapped.genes(data, namecolumn=1, fullmatchcolumn=2, genes=NULL, extractpattern=expression("^(.+?)_.+"))

data
A data.frame as created by load.file.
Default empty
Values read-count data.frame

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

genes
If you want to know how many sgRNAs are not present for a single gene, set genes to your gene identifier of interest.
Default NULL
Values gene identifier (character)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

carpools.read.distribution()

Usage
carpools.read.distribution=(dataset,namecolumn=1, fullmatchcolumn=2,breaks="NULL", title="Title", xlab="X-Axis", ylab="Y-Axis",statistics=TRUE, col=rgb(0, 0, 0, alpha = 0.65), extractpattern=expression("^(.+?)_.+"), plotgene=NULL, type="distribution", logscale=TRUE)

dataset Data frame of read-count data as created by load.file().
Default none
Values A data frame

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

breaks
Histogram breaks see ?hist. By default, will be calculated according to the data-set length.
Default NULL Values (numeric)

title
Main title of plot
Default “Title”
Values “The title you want” (character)

xlab
Label of X-Axis
Default “X-Axis”
Values “Label of X-Axis” (character)

ylab
Label of Y-Axis
Default “Y-Axis”
Values “Label of Y-Axis” (character)

statistics
Whether basic statistics will be shown in the plot.
Default TRUE
Values TRUE, FALSE (boolean)

col
The color of the plotted data. Can be any R color or RGB object. See ?rgb() for further information.
Default rgb(0, 0, 0, alpha = 0.65)
Values Any R color name or RGB color object (character OR color object)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

plotgene
You can only plot the read count distribution of sgRNAs belonging to a certain gene, which is given to the function via plotgene.
Default NULL
Value NULL or gene identifier (character)

type
You can plot either the read count distribution either as a normal histogram, or a box-and-whisker plot.
Default “distribution”
Values “distribution” to plot a histogram, or “whisker” to plot a whisker plot (character)

logscale
Indicates whether the read-count is plotted in a logarithmic scale.
Default TRUE
Values TRUE, FALSE (boolean)

# Histogram
carpools.read.distribution(CONTROL1, fullmatchcolumn=2,breaks=200,
  title=d.CONTROL1, xlab="log2 Readcount", ylab="# sgRNAs",statistics=TRUE) 

# Whisker
carpools.read.distribution(CONTROL1, fullmatchcolumn=2,breaks=200,
  title=d.CONTROL1, xlab="log2 Readcount", ylab="# sgRNAs",statistics=TRUE,
  type="whisker") 

# Histogram
carpools.read.distribution(CONTROL1, fullmatchcolumn=2,breaks=200,
  title=d.CONTROL1, xlab="log2 Readcount", ylab="# sgRNAs",statistics=TRUE, plotgene="CASP8") 

carpools.read.depth()

Usage
carpools.read.depth(datasets, namecolumn=1, fullmatchcolumn=2, dataset.names=NULL, extractpattern=expression("^(.+?)_.+"), col=rgb(0, 0, 0, alpha = 0.65), xlab="Genes", ylab="Read Count per sgRNA", statistics=TRUE, labelgenes = NULL, controls.target = controls.target, controls.nontarget=controls.nontarget, labelcolor="orange", waterfall=FALSE)

dataset A list of data frames of read-count data as created by load.file().
Default none
Values A list of data frames

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

dataset.names
A list of names that must be according to the list of data sets given in dataset.
Default NULL
Value NULL or list of data names (list)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

col
The color of the plotted data. Can be any R color or RGB object. See ?rgb() for further information.
Default rgb(0, 0, 0, alpha = 0.65)
Values Any R color name or RGB color object (character OR color object)

xlab
Label of X-Axis
Default “X-Axis”
Values “Label of X-Axis” (character)

ylab
Label of Y-Axis
Default “Y-Axis”
Values “Label of Y-Axis” (character)

statistics
Whether basic statistics will be shown in the plot.
Default TRUE
Values TRUE, FALSE (boolean)

labelgenes
You can highlight certain genes within the plot. This expects a gene identifier or a vector of gene identifiers.
Default NULL
Values A gene identifier or vector of gene identifiers (character)

labelcolor
Color to highlight genes stated in labelgenes.
Default “orange”
Values Any R color or RGB color object.

controls.target
Highlights the positive control in red color.
Default NULL
Value Gene Identifier (character)

controls.nontarget
Highlights the non-targeting control in blue color.
Default “random”
Value Gene Identifier (character)

waterfall
You can either plot the read depth sorted by gene identifier (FALSE, default) or according to the read depth.
Default FALSE
Values TRUE, FALSE (boolean)

# Plot for a singe sample
carpools.read.depth(datasets = list(CONTROL1), namecolumn=1 ,fullmatchcolumn=2,
  dataset.names=list(d.CONTROL1), extractpattern=expression("^(.+?)_.+"),
  xlab="Genes", ylab="Read Count per sgRNA",statistics=TRUE, labelgenes = NULL,
  controls.target = "CASP8", controls.nontarget="random", waterfall=FALSE)

# Plot for a singe sample sorted to read depth
carpools.read.depth(datasets = list(CONTROL1), namecolumn=1 ,fullmatchcolumn=2,
  dataset.names=list(d.CONTROL1), extractpattern=expression("^(.+?)_.+"),
  xlab="Genes", ylab="Read Count per sgRNA",statistics=TRUE, labelgenes = NULL,
  controls.target = "CASP8", controls.nontarget="random", waterfall=TRUE)

carpools.reads.genedesigns()

Usage
carpools.reads.genedesigns(dataset, namecolumn=1, fullmatchcolumn=2, title="Read Count", xlab="% of sgRNAs present", ylab="# of Genes", agg.function=sum, extractpattern=expression("^(.+?)_.+"), col = rgb(0, 0, 0, alpha = 0.65))

dataset A data frame of read-count data as created by load.file().
Default none
Values A data frame

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

title
The title of the plot.
Default “Read Count”
Values “Any title” (character)

xlab
Label of X-Axis
Default “X-Axis”
Values “Label of X-Axis” (character)

ylab
Label of Y-Axis
Default “Y-Axis”
Values “Label of Y-Axis” (character)

agg.function
The function to aggregate sgRNA read-count. Default sum
Values any mathematical function (function)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

col
The color of the plotted data. Can be any R color or RGB object. See ?rgb() for further information.
Default rgb(0, 0, 0, alpha = 0.65)
Values Any R color name or RGB color object (character OR color object)

control1.readspergene = carpools.reads.genedesigns(CONTROL1, namecolumn=1, fullmatchcolumn=2, title=paste("% sgRNAs:", d.CONTROL1, sep=" "), xlab="% of sgRNAs present", ylab="# of Genes")

carpools.read.count.vs()

Usage
carpools.read.count.vs(dataset, namecolumn=1, fullmatchcolumn=2, title="Read Count", dataset.names = NULL, xlab="Readcount Dataset1", ylab="Readcount Dataset2", xlim=NULL, ylim=NULL, pch=16, col = rgb(0, 0, 0, alpha = 0.65), labelgenes=NULL, labelcolor="red", extractpattern=expression("^(.+?)_.+"), plotline=TRUE, normalize=TRUE, norm.function=median, offsetplot=1.2, center=FALSE, aggregated=FALSE, pairs=FALSE, type=NULL, identify=FALSE)

dataset A list of data frames of read-count data as created by load.file().
Default none
Values A list of data frames

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

title
The title of the plot.
Default “Read Count”
Values “Any title” (character)

dataset.names
A list of names that must be according to the list of data sets given in dataset.
Default NULL
Value NULL or list of data names (list)

xlab
Label of X-Axis, only if pairs=FALSE
Default “X-Axis”
Values “Label of X-Axis” (character)

ylab
Label of Y-Axis only if pairs=FALSE
Default “Y-Axis”
Values “Label of Y-Axis” (character)

xlim
You can define the x-axis range being plotted, e.g. c(0,1).
Default empty
Values empty or a vector with the lower and upper limit.

ylim
You can define the y-axis range being plotted, e.g. c(0,1).
Default empty
Values empty or a vector with the lower and upper limit.

pch
The type of point used in the plot. See ?par().
Default 16
Values Any number describing the point, e.g. 16 (numeric)

col
The color of the plotted data. Can be any R color or RGB object. See ?rgb() for further information.
Default rgb(0, 0, 0, alpha = 0.65)
Values Any R color name or RGB color object (character OR color object)

labelgenes
You can highlight certain genes within the plot. This expects a gene identifier or a vector of gene identifiers.
Default NULL
Values A gene identifier or vector of gene identifiers (character)

labelcolor
Color to highlight genes stated in labelgenes.
Default “orange”
Values Any R color or RGB color object.

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

plotline
You can draw additional lines indicating a fold change of 0, 2, 4.
Default TRUE
*Values** TRUE, FALSE (boolean)

normalize
Whether you would like to normalize read-counts first. Recommended if not done already.
Default TRUE
Values TRUE, FALSE (boolean)

norm.function
The mathematical function to normalize data if normalize=TRUE. By default, the median is used.
Default median
Values Any mathematical function of R (function)

offsetplot
Offetplot is used to stretch the x- and y-axis for nicer graphs. This will extend plotting area by offsetplot.
Default 1.2 (Plotting area is stretched to 1.2 times)
Values any number (numeric)

center
If you like you can center your data within the plot.
Default FALSE
Values TRUE, FALSE (boolean)

aggregated
If you want to highlight genes, set this to true if you provide already aggregated gene read count instead of sgRNA read counts.
Default FALSE
Values TRUE, FALSE (boolean)

pairs
In the case of plotting all four data sets at once, you can use a pairs plot for easier overview (see ?pairs()).
Default FALSE
Values TRUE, FALSE (boolean)

type
This indicates whether you would like to color all highlighted genes in either red (“enriched”) or blue (“depleted”) color according to the standards in caRpools for plotting enriched or depleted genes after analysis.
Default NULL
Values NULL, “enriched”, “depleted”

identify
You can ask R to let you identify genes by clicking on the dots in the graph. This only works if pairs=FALSE.
Default FALSE
Values TRUE, FALSE (boolean)

# Highlight the non-targeting control in two datasets
carpools.read.count.vs(dataset=list(TREAT1,CONTROL1), dataset.names = c(d.TREAT1, d.CONTROL1),
  pairs=FALSE, namecolumn=1, fullmatchcolumn=2, title="", pch=16,
  normalize=TRUE, norm.function=median, labelgenes="random", labelcolor="blue",
  center=FALSE, aggregated=FALSE)

# Highlight the non-targeting control in two datasets with CENTERING
carpools.read.count.vs(dataset=list(TREAT1,CONTROL1), dataset.names = c(d.TREAT1, d.CONTROL1),
  pairs=FALSE, namecolumn=1, fullmatchcolumn=2, title="", pch=16,
  normalize=TRUE, norm.function=median, labelgenes="random", labelcolor="blue",
  center=TRUE, aggregated=FALSE)

# Highlight the targeting control in two datasets on GENE level
carpools.read.count.vs(dataset=list(TREAT1.g,CONTROL1.g), dataset.names = c(d.TREAT1, d.CONTROL1),
  pairs=FALSE, namecolumn=1, fullmatchcolumn=2, title="", pch=16,
  normalize=TRUE, norm.function=median, labelgenes="CASP8", labelcolor="red",
  center=FALSE, aggregated=TRUE)

## Warning in cor(plot.dataset[plot.dataset[, "designs"] %in% labelgenes,
## "dataset1"], : Standardabweichung ist Null

## Warning in cor(plot.dataset[plot.dataset[, "designs"] %in% labelgenes,
## "dataset1"], : Standardabweichung ist Null

# Highlight non-targeting control in all datasets
carpools.read.count.vs(dataset=list(TREAT1, TREAT2, CONTROL1, CONTROL2),
  dataset.names = c(d.TREAT1, d.TREAT2, d.CONTROL1, d.CONTROL2), pairs=TRUE, namecolumn=1,
  fullmatchcolumn=2, title="", pch=16, normalize=TRUE, norm.function=median,
  labelgenes="random", labelcolor="blue", center=FALSE, aggregated=FALSE)

# Highlight targeting control in all datasets on Gene Level
carpools.read.count.vs(dataset=list(TREAT1.g, TREAT2.g, CONTROL1.g, CONTROL2.g),
  dataset.names = c(d.TREAT1, d.TREAT2, d.CONTROL1, d.CONTROL2), pairs=TRUE, namecolumn=1,
  fullmatchcolumn=2, title="", pch=16, normalize=TRUE, norm.function=median,
  labelgenes="CASP8", labelcolor="blue", center=FALSE, aggregated=TRUE)

carpools.raw.genes()

Usage carpools.raw.genes(untreated.list,treated.list, genes=NULL, namecolumn=1, fullmatchcolumn=2, norm.function=median, extractpattern=expression("^(.+?)_.+"), do.plot=TRUE, log=FALSE, put.names=FALSE, type="foldchange", controls.target= NULL, controls.nontarget=NULL, sort=TRUE, ...)

untreated.list A list of untreated sample data frames of read-count data as created by load.file().
Default none
Values A list of data frames of the untreated samples

treated.list A list of treated sample data frames of read-count data as created by load.file().
Default none
Values A list of data frames of the treated samples

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

norm.function
The mathematical function to normalize data if normalize=TRUE. By default, the median is used.
Default median
Values Any mathematical function of R (function)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

do.plot
Whether a plot is drawn or only tabular output is returned.
Default TRUE
Values TRUE, FALSE (boolean)

log
Plot in log-scale?
Default FALSE
Values TRUE, FALSE (boolean)

put.names
Do you want the sgRNA identifiers to be plotted?
Default FALSE
Values TRUE, FALSE

type
Provides different types. “foldchange” for log2 foldchange, “readcount” for read-count, “z-score” for Z-scores, “z-ratio” for a Z-ratio or “vioplot” for a log2 FC of sgRNA effects.
Default “foldchange”
Values “foldchange”, “readcount”, “z-score”, “z-ratio”, “vioplot”

controls.target
Highlights the positive control in red color.
Default NULL
Value Gene Identifier (character)

controls.nontarget
Highlights the non-targeting control in blue color.
Default “random”
Value Gene Identifier (character)

sort
This leads to output sorted by fold-change or z-ratio instead of names.
Default TRUE
Values TRUE, FALSE

genes
For which gene shall sgRNA effects being plotted?
Default NULL
Values Gene identifier

# Foldchange
p1 = carpools.raw.genes(untreated.list = list(CONTROL1, CONTROL2),
  treated.list = list(TREAT1, TREAT2), genes="CASP8", namecolumn=1,
  fullmatchcolumn=2, norm.function=median, extractpattern=expression("^(.+?)_.+"), 
  do.plot=TRUE, log=FALSE, put.names=TRUE, type="foldchange" )

# Z-Ratio
p2 = carpools.raw.genes(untreated.list = list(CONTROL1, CONTROL2),
  treated.list = list(TREAT1, TREAT2), genes="CASP8", namecolumn=1,
  fullmatchcolumn=2, norm.function=median, extractpattern=expression("^(.+?)_.+"), 
  do.plot=TRUE, log=FALSE, put.names=TRUE, type="z-ratio" )

# Read Count
p3 = carpools.raw.genes(untreated.list = list(CONTROL1, CONTROL2),
  treated.list = list(TREAT1, TREAT2), genes="CASP8", namecolumn=1,
  fullmatchcolumn=2, norm.function=median, extractpattern=expression("^(.+?)_.+"), 
  do.plot=TRUE, log=FALSE, put.names=TRUE, type="readcount" )

# Violine plot
p4 = carpools.raw.genes(untreated.list = list(CONTROL1, CONTROL2),
  treated.list = list(TREAT1, TREAT2), genes="CASP8", namecolumn=1,
  fullmatchcolumn=2, norm.function=median, extractpattern=expression("^(.+?)_.+"), 
  do.plot=TRUE, log=FALSE, put.names=TRUE, type="vioplot" )

stat.wilcox()

Usage
stat.wilcox(untreated.list=list(dataset1.untreated, dataset2.untreated),treated.list=list(dataset1.treated, dataset2.treated), namecolumn=1, fullmatchcolumn=2,normalize=TRUE,norm.fun=median, extractpattern=expression("^(.+?)_.+"), controls=NULL, control.picks=150, sorting=TRUE)

untreated.list A list of untreated sample data frames of read-count data as created by load.file().
Default none
Values A list of data frames of the untreated samples

treated.list A list of treated sample data frames of read-count data as created by load.file().
Default none
Values A list of data frames of the treated samples

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

normalize
Whether you would like to normalize read-counts first. Recommended if not done already.
Default TRUE
Values TRUE, FALSE (boolean)

norm.function
The mathematical function to normalize data if normalize=TRUE. By default, the median is used.
Default median
Values Any mathematical function of R (function)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

controls
Please give the gene identifier of the non-targeting control. If you do not have non-targeting controls, leave NULL.
Default NULL
Values NULL or gene identifier (character)

control.picks
If no non-targeting controls are present or set, wilcox will pick a random number of sgRNAs from the data set as the alternative population. This is only used if controls=NULL.
Default 300
Values numeric

stat.DEseq()

Usage
stat.DESeq(untreated.list,treated.list,namecolumn=1, fullmatchcolumn=2, agg.function=sum, extractpattern=expression("^(.+?)_.+"), sorting=FALSE, sgRNA.pval = 0.01, filename.deseq="data", fitType="parametric", p.adjust="holm")

untreated.list A list of untreated sample data frames of read-count data as created by load.file().
Default none
Values A list of data frames of the untreated samples

treated.list A list of treated sample data frames of read-count data as created by load.file().
Default none
Values A list of data frames of the treated samples

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

agg.function
The function to aggregate sgRNA read-count. Default sum
Values any mathematical function (function)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

sorting
Sort output by log2 fold change? Default FALSE
Values TRUE, FALSE (boolean)

sgRNA.pval
p-value threshold to count significant sgRNAs for each gene.
Default 0.001
Value (numeric)

filename.deseq
Filename of raw DESeq2 data output.
Default “data”
Values (character)

fit.Type
See ?DESeq2.
Default “parametric”
Values “parametric”, “local” “mean”

p.adjust
Method to adjust p-value for multiple testing. See ?DEseq2.
Default “holm” Values see ?DESeq2

stat.mageck()

Usage
stat.mageck(untreated.list, treated.list, namecolumn=1, fullmatchcolumn=2, norm.fun=median, extractpattern=expression("^(.+?)_.+"), mageckfolder=NULL, sort.criteria="neg", adjust.method="fdr", filename=NULL, fdr.pval=0.05)

untreated.list A list of untreated sample data frames of read-count data as created by load.file().
Default none
Values A list of data frames of the untreated samples

treated.list A list of treated sample data frames of read-count data as created by load.file().
Default none
Values A list of data frames of the treated samples

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

sort.criteria
MAGeCK argument –sort-criteria
Default “neg”
Values see MAGeCK documentation

mageckfolder
Folder for MAGeCK raw data output (internally used).
Default NULL
Value (character)

filename
Filename of raw MAGeCK data output.
Default “data”
Values (character)

adjust.method
Method to adjust p-value for multiple testing. See MAGeCK documentation.
Default “fdr” Values see MAGeCK documentation

fdr.pval
FDR used for correction. Default 0.05
Values (numeric)

carpools.waterfall.pval()

Usage
carpools.waterfall.pval (type=NULL,dataset=NULL, pval=0.05, mageck.type="pos", log=TRUE)

type
This indicates which kind of analysis method was used for p-value calculation.
Default NULL
Values “mageck”, “deseq2”, “wilcox”

dataset
Result from either stat.wilcox, stat.DEseq or stat.mageck.
Default NULL
Values Result from either stat.wilcox, stat.DEseq or stat.mageck

pval
The significance value set for the analysis which is to be plotted.
Default 0.05
Values numeric

mageck.type
Only for plotting p-value calculate by MAGeCK. Indicates whether enriched (“pos”) or depleted (“neg”) genes are used.
Default “pos”
Values “pos”, “neg”

log
-log10 of the p-values is plotted if set to TRUE.
Default TRUE
Values TRRUE, FALSE (boolean)

Examples

mageck.result = carpools.hitident(data.mageck, type="mageck", title="MAGeCK", inches=0.1, print.names=TRUE, plot.p=0.05, offsetplot=1.2, sgRNA.top=1)

wilcox.result = carpools.hitident(data.wilcox, type="wilcox", title="Wilcox", inches=0.1, print.names=TRUE, plot.p=0.05, offsetplot=1.2, sgRNA.top=1)

carpools.hit.overview()

Usage
carpools.hit.overview(wilcox=NULL, deseq=NULL, mageck=NULL, cutoff.deseq = 0.001, cutoff.wilcox = 0.05, cutoff.mageck = 0.05, cutoff.override=FALSE, cutoff.hits=NULL, plot.genes="overlapping", type="all")

wilcox
Data output from stat.wilcox.
Default NULL
Values Data output from stat.wilcox.

deseq
Data output from stat.deseq.
Default NULL
Values Data output from stat.deseq.

mageck
Data output from stat.mageck.
Default NULL
Values Data output from stat.mageck.

cutoff.deseq
P-Value threshold used to determine significance.
Default 0.001
Values numeric

cutoff.wilcox
P-Value threshold used to determine significance.
Default 0.001
Values numeric

cutoff.mageck
P-Value threshold used to determine significance.
Default 0.001
Values numeric

cutoff.override
Shall the p-value threshold be ignored? If this is TRUE, the top percentage gene of cutoff.hits is used instead.
Default FALSE
Values TRUE, FALSE

cutoff.hits
The percentage of top genes being used if cutoff.override=TRUE.
*Default** NULL
Values numeric

plot.genes
Defines what kind of data is used. By default, overlapping genes are highlighted in red color.
Default “overlapping”
Values “overlapping”

type
Defines whether all genes are plotted or only those being enriched or depleted.
Default “all”
Values “all”, “enriched”, “depleted”

generate.hits()

Usage
generate.hits(wilcox=NULL, deseq=NULL, mageck=NULL, type="enriched", cutoff.deseq = 0.001, cutoff.wilcox = 0.05, cutoff.mageck = 0.05, cutoff.override=FALSE, cutoff.hits=NULL, plot.genes="overlapping")

wilcox
Data output from stat.wilcox.
Default NULL
Values Data output from stat.wilcox.

deseq
Data output from stat.deseq.
Default NULL
Values Data output from stat.deseq.

mageck
Data output from stat.mageck.
Default NULL
Values Data output from stat.mageck.

cutoff.deseq
P-Value threshold used to determine significance.
Default 0.001
Values numeric

cutoff.wilcox
P-Value threshold used to determine significance.
Default 0.001
Values numeric

cutoff.mageck
P-Value threshold used to determine significance.
Default 0.001
Values numeric

cutoff.override
Shall the p-value threshold be ignored? If this is TRUE, the top percentage gene of cutoff.hits is used instead.
Default FALSE
Values TRUE, FALSE

cutoff.hits
The percentage of top genes being used if cutoff.override=TRUE.
*Default** NULL
Values numeric

plot.genes
Defines what kind of data is returned, by default only overlapping genes or MAGeCK.
Default “overlapping”
Values “overlapping”

type
Defines whether all genes are plotted or only those being enriched or depleted.
Default “all”
Values “all”, “enriched”, “depleted”

carpools.hit.scatter()

Usage
carpools.hit.scatter = function(wilcox=NULL, deseq=NULL, mageck=NULL, dataset, dataset.names = NULL, namecolumn=1, fullmatchcolumn=2, title="Read Count", xlab="Readcount Dataset1", ylab="Readcount Dataset2", labelgenes=NULL, labelcolor="orange", extractpattern=expression("^(.+?)_.+"), plotline=TRUE, normalize=TRUE, norm.function=median, offsetplot=1.2, center=FALSE, aggregated=FALSE, type="enriched", cutoff.deseq = 0.001, cutoff.wilcox = 0.05, cutoff.mageck = 0.05, cutoff.override=FALSE, cutoff.hits=NULL, plot.genes="overlapping", pch=16, col = rgb(0, 0, 0, alpha = 0.65))

wilcox
Data output from stat.wilcox.
Default NULL
Values Data output from stat.wilcox.

deseq
Data output from stat.deseq.
Default NULL
Values Data output from stat.deseq.

mageck
Data output from stat.mageck.
Default NULL
Values Data output from stat.mageck.

cutoff.deseq
P-Value threshold used to determine significance.
Default 0.001
Values numeric

cutoff.wilcox
P-Value threshold used to determine significance.
Default 0.001
Values numeric

cutoff.mageck
P-Value threshold used to determine significance.
Default 0.001
Values numeric

dataset A list of data frames of read-count data as created by load.file().
Default none
Values A list of data frames

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

dataset.names
A list of names that must be according to the list of data sets given in dataset.
Default NULL
Value NULL or list of data names (list)

norm.function
The mathematical function to normalize data. By default, the median is used.
Default median
Values Any mathematical function of R (function)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

cutoff.override
Shall the p-value threshold be ignored? If this is TRUE, the top percentage gene of cutoff.hits is used instead.
Default FALSE
Values TRUE, FALSE

cutoff.hits
The percentage of top genes being used if cutoff.override=TRUE.
*Default** NULL
Values numeric

plot.genes
Defines what kind of data is used. By default, overlapping genes are highlighted in red color.
Default “overlapping”
Values “overlapping”

type
Defines whether all genes are plotted or only those being enriched or depleted.
Default “all”
Values “all”, “enriched”, “depleted”

labelgenes
For which gene shall the sgRNA effects being plotted? This expects a gene identifier or a vector of gene identifiers.
Default NULL
Values A gene identifier or vector of gene identifiers (character)

xlab
Label of X-Axis, only if pairs=FALSE
Default “X-Axis”
Values “Label of X-Axis” (character)

ylab
Label of Y-Axis only if pairs=FALSE
Default “Y-Axis”
Values “Label of Y-Axis” (character)

pch
The type of point used in the plot. See ?par().
Default 16
Values Any number describing the point, e.g. 16 (numeric)

col
The color of the plotted data. Can be any R color or RGB object. See ?rgb() for further information.
Default rgb(0, 0, 0, alpha = 0.65)
Values Any R color name or RGB color object (character OR color object)

plotline
You can draw additional lines indicating a fold change of 0, 2, 4.
Default TRUE
*Values** TRUE, FALSE (boolean)

normalize
Whether you would like to normalize read-counts first. Recommended if not done already.
Default TRUE
Values TRUE, FALSE (boolean)

offsetplot
Offetplot is used to stretch the x- and y-axis for nicer graphs. This will extend plotting area by offsetplot.
Default 1.2 (Plotting area is stretched to 1.2 times)
Values any number (numeric)

center
If you like you can center your data within the plot.
Default FALSE
Values TRUE, FALSE (boolean)

aggregated
If you want to highlight genes, set this to true if you provide already aggregated gene read count instead of sgRNA read counts.
Default FALSE
Values TRUE, FALSE (boolean)

carpools.hit.sgrna()

Usage
carpools.hit.sgrna(wilcox=NULL, deseq=NULL, mageck=NULL, dataset=NULL, dataset.names = NULL, namecolumn=1, fullmatchcolumn=2, norm.function=median, extractpattern=expression("^(.+?)_.+"), put.names=TRUE, type="enriched", labelgenes=NULL, cutoff.deseq = 0.05, cutoff.wilcox = 0.05, cutoff.mageck = 0.05, cutoff.override=FALSE, plot.genes="overlapping", cutoff.hits=NULL, plot.type=NULL, controls.target=NULL, controls.nontarget=NULL)

wilcox
Data output from stat.wilcox.
Default NULL
Values Data output from stat.wilcox.

deseq
Data output from stat.deseq.
Default NULL
Values Data output from stat.deseq.

mageck
Data output from stat.mageck.
Default NULL
Values Data output from stat.mageck.

cutoff.deseq
P-Value threshold used to determine significance.
Default 0.001
Values numeric

cutoff.wilcox
P-Value threshold used to determine significance.
Default 0.001
Values numeric

cutoff.mageck
P-Value threshold used to determine significance.
Default 0.001
Values numeric

dataset A list of data frames of read-count data as created by load.file().
Default none
Values A list of data frames

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

dataset.names
A list of names that must be according to the list of data sets given in dataset.
Default NULL
Value NULL or list of data names (list)

norm.function
The mathematical function to normalize data. By default, the median is used.
Default median
Values Any mathematical function of R (function)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

cutoff.override
Shall the p-value threshold be ignored? If this is TRUE, the top percentage gene of cutoff.hits is used instead.
Default FALSE
Values TRUE, FALSE

cutoff.hits
The percentage of top genes being used if cutoff.override=TRUE.
*Default** NULL
Values numeric

plot.genes
Defines what kind of data is used. By default, overlapping genes are highlighted in red color.
Default “overlapping”
Values “overlapping”

type
Defines whether all genes are plotted or only those being enriched or depleted.
Default “all”
Values “all”, “enriched”, “depleted”

labelgenes
For which gene shall the sgRNA effects being plotted? This expects a gene identifier or a vector of gene identifiers.
Default NULL
Values A gene identifier or vector of gene identifiers (character)

controls.target
If type="controls", this is the gene identifier of the positive control.
Default NULL
Value Gene Identifier (character)

controls.nontarget
If type="controls", this is the gene identifier of the non-targeting control.
Default “random”
Value Gene Identifier (character)

put.names
Do you want the sgRNA identifiers to be plotted?
Default FALSE
Values TRUE, FALSE

plot.type
Which kind of plot is to be drawn? If NULL, fold-change and violine plots are generated.
Default NULL
Values NULL, “foldchange”, “z-score”, “z-ratio”, “vioplot”

carpools.sgrna.table()

Usage
carpools.sgrna.table (wilcox=NULL, deseq=NULL, mageck=NULL, dataset=NULL, dataset.names = NULL, namecolumn=1, fullmatchcolumn=2, norm.function=median, extractpattern=expression("^(.+?)_.+"), type="enriched", cutoff.deseq = 0.05, cutoff.wilcox = 0.05, cutoff.mageck = 0.05, cutoff.override=FALSE, plot.genes="overlapping", cutoff.hits=NULL, sgrna.file=NULL, labelgenes=NULL, write=FALSE, datapath=getwd(), analysis.name="Screen")

wilcox
Data output from stat.wilcox.
Default NULL
Values Data output from stat.wilcox.

deseq
Data output from stat.deseq.
Default NULL
Values Data output from stat.deseq.

mageck
Data output from stat.mageck.
Default NULL
Values Data output from stat.mageck.

cutoff.deseq
P-Value threshold used to determine significance.
Default 0.001
Values numeric

cutoff.wilcox
P-Value threshold used to determine significance.
Default 0.001
Values numeric

cutoff.mageck
P-Value threshold used to determine significance.
Default 0.001
Values numeric

dataset A list of data frames of read-count data as created by load.file().
Default none
Values A list of data frames

namecolumn
In which column are the sgRNA identifiers?
Default 1
Values column number (numeric)

fullmatchcolumn
In which column are the read counts?
Default 2
Values column number (numeric)

dataset.names
A list of names that must be according to the list of data sets given in dataset.
Default NULL
Value NULL or list of data names (list)

norm.function
The mathematical function to normalize data. By default, the median is used.
Default median
Values Any mathematical function of R (function)

extractpattern
PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier.
e.g. in AAK1_107_0 it will extract AAK1, since this is the gene identifier belonging to this sgRNA identifier. Please see: Read-Count Data Files
Default expression(“^(.+?)(_.+)“), will work for most available libraries.
Values PERL regular expression with parenthesis indicating the gene identifier (expression)

cutoff.override
Shall the p-value threshold be ignored? If this is TRUE, the top percentage gene of cutoff.hits is used instead.
Default FALSE
Values TRUE, FALSE

cutoff.hits
The percentage of top genes being used if cutoff.override=TRUE.
*Default** NULL
Values numeric

plot.genes
Defines what kind of data is used. By default, overlapping genes are highlighted in red color.
Default “overlapping”
Values “overlapping”

type
Defines whether all genes are plotted or only those being enriched or depleted.
Default “all”
Values “all”, “enriched”, “depleted”

sgRNA.file
This is the library reference file loaded via load.file providing the sgRNA target sequence.
Default NULL
Values object from load.file

labelgenes
For which gene shall the sgRNA effects being generated? This expects a gene identifier or a vector of gene identifiers.
Default NULL
Values A gene identifier or vector of gene identifiers (character)

write
If you want to write directly to a file, this must be TRUE. Leave FALSE if you want the function to return a table.
Default FALSE
Values TRUE, FALSE

datapath
If write=TRUE, this is the directory the file is written.
Default getwd()
Values absolute path

analysis.name
The name of the file if write=TRUE
Default “Screen”
Values any file name (character)