Description Usage Arguments Details Value Note Author(s) Examples
CaRpools also allows you to visualize the phenotypic effects of sgRNA belonging to the same gene via 'carpools.raw.genes'. This includes plotting of sgRNA foldchanges, z-score, z-ratios or read-counts. Moreover, 'type="vioplot"' will present fold change data in comparison to the whole dataset and controls.
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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 beloning 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 foldchange or z-ratio instead of names. *Default* TRUE *Values* TRUE, FALSE |
genes |
For which gene shall the sgRNA effect plots being generated? |
none
Return either generic plots or tables.
none
Jan Winter
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | data(caRpools)
# 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" )
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