Package 'KRSA'

Title: KRSA: Kinome Random Sampling Analyzer
Description: The goal of this package is to analyze the PamChip data and identify the changes in the active kinome. The package can preprocess the PamChip data output from BioNavigator and use Random Sampling and Permutation Analysis to identify upstream kinases. Additionally, this package provides a set of useful visualizations for the PamChip data.
Authors: Ali Sajid Imami [aut, cre] , Khaled Alganem [aut]
Maintainer: Ali Sajid Imami <[email protected]>
License: MIT + file LICENSE
Version: 1.99.41
Built: 2024-07-02 03:26:12 UTC
Source: https://github.com/CogDisResLab/KRSA

Help Index

Protein-Protein Interactions based on PhosphositePlus database

Description

A data frame of the known Protein-Protein Interactions based on PhosphositePlus database

Usage

data("ballModel_edges")

Format

A data frame with 592 rows and 2 variables:

Source

Kinase Family Name Source

Target

Kinase Family Name Target

Protein-Protein Interactions based on PhosphositePlus database

Description

A data frame of the known Protein-Protein Interactions based on PhosphositePlus database

Usage

data("ballModel_nodes")

Format

A data frame with 179 rows and 2 variables:

FinName

Kinase Family Name

count

Number of collapsed kinases under that kinase family, it's not used in package

Runs enrichr api (single GET call for a geneset library)

Description

This function takes in the geneset library name from Enrichr and userListId (id created by enrichr api) sand retruns tidy dataframe of all geneset terms in that library

Usage

enrichr_lib_call(lib, userListId)

Arguments

lib

geneset library name from Enrichr
userListId

id created by the POST enrichr api call

Value

df tidy dataframe of all geneset terms in that library

See Also

Other helper functions: krsa_ce_output_kinases(), krsa_ce_output_peptides(), krsa_enrichr(), krsa_extractEndPoint(), krsa_extractEndPointMaxExp(), krsa_get_diff(), krsa_get_diff_byChip(), krsa_sampling(), krsa_show_peptides(), krsa_top_hits()

Examples

TRUE

Main KRSA function. It performs the random sampling analysis and generates a Z score table and a count matrix

Description

Takes in a vector of the peptides that are considered "hits" and kinase-substrate and coverage dataframes and returns the Z score table

Usage

krsa(
  peptides,
  itr = 2000,
  seed = 123,
  return_count = F,
  map_file = KRSA_file,
  cov_file = chipCov
)

Arguments

peptides

a vector of the peptides that are considered "hits"
itr

number of iterations for the random sampling (default = 2000)
seed

seed number (default = 123)
return_count

boolean to return the kinase count matrix
map_file

kinase-substrate dataframe
cov_file

kinase coverage dataframe

Value

Z score tibble or list if return_count = TRUE

See Also

Other core functions: krsa_group_diff(), krsa_quick_filter(), krsa_read(), krsa_scaleModel()

Examples

TRUE

Generates a kinase ball model using the Z score table

Description

This function takes in a Z score table and produces a kinase ball model

Usage

krsa_ball_model(kinase_hits, Ztable, frq, Nsize, Tsize)

Arguments

kinase_hits

a vector of kinases
Ztable

Z score table
frq

= cutoff for number of connections with other nodes
Nsize

= size of nodes scale
Tsize

= size of text scale

Value

igraph network

See Also

Other plots: krsa_coverage_plot(), krsa_curve_plot(), krsa_cv_plot(), krsa_heatmap(), krsa_heatmap_grouped(), krsa_histogram_plot(), krsa_reverse_krsa_plot(), krsa_violin_plot(), krsa_violin_plot_grouped(), krsa_waterfall(), krsa_zscores_plot()

Examples

TRUE

It prepares a KRSA kinase file to be used for creedenzymatic

Description

Takes in the Z score table and output kinase with their scores

Usage

krsa_ce_output_kinases(krsa_table, file_name)

Arguments

krsa_table

a df of the Z score table
file_name

file name and path to save file as txt tab delimited file

Value

saved txt file to be used in creedenzymatic

See Also

Other helper functions: enrichr_lib_call(), krsa_ce_output_peptides(), krsa_enrichr(), krsa_extractEndPoint(), krsa_extractEndPointMaxExp(), krsa_get_diff(), krsa_get_diff_byChip(), krsa_sampling(), krsa_show_peptides(), krsa_top_hits()

It prepares a KRSA peptide file (log2 FC) to be used for creedenzymatic

Description

Takes in the Z score table and output kinase with their scores

Usage

krsa_ce_output_peptides(peptide_table, metric, file_name)

Arguments

peptide_table

a df of the log2 FC scores of peptides
metric

which col to use as the score (totalMeanLFC, LFC, ... etc)
file_name

file name and path to save file as txt tab delimited file

Value

saved txt file to be used in creedenzymatic

See Also

Other helper functions: enrichr_lib_call(), krsa_ce_output_kinases(), krsa_enrichr(), krsa_extractEndPoint(), krsa_extractEndPointMaxExp(), krsa_get_diff(), krsa_get_diff_byChip(), krsa_sampling(), krsa_show_peptides(), krsa_top_hits()

Generates a coverage plot (Percentage of total coverage of kinases on chip)

Description

This function takes in the chipCov map, Z score table, and chip type to produce a coverage plot (Percentage of total coverage of kinases on chip)

Usage

krsa_coverage_plot(chipCov, Ztable, chipType = c("STK", "PTK"))

Arguments

chipCov

df of kinase mapping for either STK or PTK chip
Ztable

Z score table
chipType

type of chip, either STK or PTK

Value

ggplot object

See Also

Other plots: krsa_ball_model(), krsa_curve_plot(), krsa_cv_plot(), krsa_heatmap(), krsa_heatmap_grouped(), krsa_histogram_plot(), krsa_reverse_krsa_plot(), krsa_violin_plot(), krsa_violin_plot_grouped(), krsa_waterfall(), krsa_zscores_plot()

Examples

TRUE

KRSA kinase coverage file for PamChip 86402 PTK (v1 mapping)

Description

A data frame of the built-in KRSA kinase coverage file for PamChip 86402 PTK (v1 mapping)

Usage

data("KRSA_coverage_PTK_PamChip_86402_v1")

Format

A data frame with 1278 rows and 2 variables:

Kin

Kinase Family Name

Substrates

Peptides IDs

KRSA kinase coverage file for PamChip 87102 STK (v1 mapping)

Description

A data frame of the built-in KRSA kinase coverage file for PamChip 87102 STK (v1 mapping)

Usage

data("KRSA_coverage_STK_PamChip_87102_v1")

Format

A data frame with 2423 rows and 2 variables:

Kin

Kinase Family Name

Substrates

Peptides IDs

KRSA kinase coverage file for PamChip 87102 STK (v2 mapping, removed PDK kinase)

Description

A data frame of the built-in KRSA kinase coverage file for PamChip 87102 STK (v2 mapping)

Usage

data("KRSA_coverage_STK_PamChip_87102_v2")

Format

A data frame with 2423 rows and 2 variables:

Kin

Kinase Family Name

Substrates

Peptides IDs

Generates curves plots per peptide using the last cycle data

Description

This function takes in the PW data (that includes all exposure times), list of peptides, and optional arguments of samples or groups names vector

Usage

krsa_curve_plot(data, peptides, byGroup = T, samples = NULL, groups = NULL)

Arguments

data

PW data (that includes all exposure times)
peptides

a vector of peptides to plot
byGroup

fit lines by group
samples

(optional) sample names
groups

(optional) group names

Value

ggplot object

See Also

Other plots: krsa_ball_model(), krsa_coverage_plot(), krsa_cv_plot(), krsa_heatmap(), krsa_heatmap_grouped(), krsa_histogram_plot(), krsa_reverse_krsa_plot(), krsa_violin_plot(), krsa_violin_plot_grouped(), krsa_waterfall(), krsa_zscores_plot()

Examples

TRUE

Generates CV (coefficient of variation) plot

Description

This function takes in the modeled pw data, list of peptides, and sample names (optional)

Usage

krsa_cv_plot(data, peptides, samples = NULL)

Arguments

data

krsa modeled pw data (scaled)
peptides

peptide list
samples

sample names

Value

ggplot object

See Also

Other plots: krsa_ball_model(), krsa_coverage_plot(), krsa_curve_plot(), krsa_heatmap(), krsa_heatmap_grouped(), krsa_histogram_plot(), krsa_reverse_krsa_plot(), krsa_violin_plot(), krsa_violin_plot_grouped(), krsa_waterfall(), krsa_zscores_plot()

Examples

TRUE

Runs enrichr analysis using a list of PamChip peptide IDs or genes

Description

This function takes in a list of PamChip peptide IDs or genes and geneset libraries names and connects to Enrichr api and returns enriched terms the geneset library name from Enrichr and userListId (id created by enrichr api) sand retruns tidy dataframe of all geneset terms in that library

Usage

krsa_enrichr(
  peptides = NULL,
  genes = NULL,
  libs = c("GO_Biological_Process_2021", "GO_Cellular_Component_2021",
    "GO_Molecular_Function_2021", "WikiPathway_2021_Human", "Reactome_2016",
    "KEGG_2021_Human", "BioPlanet_2019")
)

Arguments

peptides

a vector of PamChip peptide IDs
genes

(optional) a vector of HGNC symbols. This will override the list of peptides
libs

geneset libraries names from Enrichr. default: c("GO_Biological_Process_2021", "GO_Cellular_Component_2021","GO_Molecular_Function_2021", "WikiPathway_2021_Human","Reactome_2016", "KEGG_2021_Human", "BioPlanet_2019")

Value

df tidy dataframe of all geneset terms in that library

See Also

Other helper functions: enrichr_lib_call(), krsa_ce_output_kinases(), krsa_ce_output_peptides(), krsa_extractEndPoint(), krsa_extractEndPointMaxExp(), krsa_get_diff(), krsa_get_diff_byChip(), krsa_sampling(), krsa_show_peptides(), krsa_top_hits()

Examples

TRUE

Visualize the enrichr analysis

Description

This function takes in the Enrichr dataframe and plot the results

Usage

krsa_enrichr_plot(enrichr_df, terms_to_plot = 10, size = 2.5)

Arguments

enrichr_df

the Enrichr dataframe generated from the krsa_enrichr function
terms_to_plot

number of terms to plot per library. default is 10
size

size of label text. default is 2.5

Value

ggplot

Examples

TRUE

Extracts end point data (last cycle)

Description

This function takes in raw data and chip type and returns end point data (last cycle)

Usage

krsa_extractEndPoint(df, type = c("STK", "PTK"))

Arguments

df

krsa raw tidy data
type

chip type

Value

end point signals df

See Also

Other helper functions: enrichr_lib_call(), krsa_ce_output_kinases(), krsa_ce_output_peptides(), krsa_enrichr(), krsa_extractEndPointMaxExp(), krsa_get_diff(), krsa_get_diff_byChip(), krsa_sampling(), krsa_show_peptides(), krsa_top_hits()

Examples

TRUE

Extracts end point data at max exposure (last cycle)

Description

This function takes in raw data and chip type and returns end point data at max exposure (last cycle)

Usage

krsa_extractEndPointMaxExp(df, type = c("STK", "PTK"))

Arguments

df

krsa raw tidy data
type

chip type

Value

end point data at max exposure df

See Also

Other helper functions: enrichr_lib_call(), krsa_ce_output_kinases(), krsa_ce_output_peptides(), krsa_enrichr(), krsa_extractEndPoint(), krsa_get_diff(), krsa_get_diff_byChip(), krsa_sampling(), krsa_show_peptides(), krsa_top_hits()

Examples

TRUE

Filters out peptides with low signals based on the pw data (max exposure)

Description

This function takes in the pw data (max exposure), signal threshold, and samples and group names (optional)

Usage

krsa_filter_lowPeps(data, threshold, samples = NULL, groups = NULL)

Arguments

data

krsa pw data (max exposure)
threshold

signal threshold
samples

(optional) sample names
groups

(optional) group names

Value

vector

See Also

Other QC functions: krsa_filter_nonLinear(), krsa_filter_ref_pep(), krsa_qc_steps()

Examples

TRUE

Filters out peptides with none linear signals based on the pw data

Description

This function takes in the pw data, r2 threshold, and samples and group names (optional)

Usage

krsa_filter_nonLinear(data, threshold, samples = NULL, groups = NULL)

Arguments

data

krsa modeled pw data (scaled)
threshold

r2 threshold
samples

(optional) sample names
groups

(optional) group names

Value

vector

See Also

Other QC functions: krsa_filter_lowPeps(), krsa_filter_ref_pep(), krsa_qc_steps()

Examples

TRUE

Filters out ref peptides

Description

This function takes in a list of peptides and filter out the ref peptides

Usage

krsa_filter_ref_pep(peptides)

Arguments

peptides

list of peptides

Value

vector of peptides

See Also

Other QC functions: krsa_filter_lowPeps(), krsa_filter_nonLinear(), krsa_qc_steps()

Examples

TRUE

Extract differential peptides based on LFC cutoff

Description

This function takes in the LFC table, column name, and an LFC cutoff to extracts differentially phosphorylated peptides

Usage

krsa_get_diff(data, col, lfc_thr, sd_thr = Inf)

Arguments

data

LFC table
col

LFC column name
lfc_thr

LFC cutoffs
sd_thr

SD cutoff

Value

peptides

See Also

Other helper functions: enrichr_lib_call(), krsa_ce_output_kinases(), krsa_ce_output_peptides(), krsa_enrichr(), krsa_extractEndPoint(), krsa_extractEndPointMaxExp(), krsa_get_diff_byChip(), krsa_sampling(), krsa_show_peptides(), krsa_top_hits()

Examples

TRUE

Extract differential peptides based on LFC cutoff by chip/barcode

Description

This function takes in the LFC table, column name, and an LFC cutoff to extracts differentially phosphorylated peptides per chip/barcode

Usage

krsa_get_diff_byChip(data, col, lfc_thr)

Arguments

data

LFC table
col

LFC column name
lfc_thr

LFC cutoffs

Value

peptides

See Also

Other helper functions: enrichr_lib_call(), krsa_ce_output_kinases(), krsa_ce_output_peptides(), krsa_enrichr(), krsa_extractEndPoint(), krsa_extractEndPointMaxExp(), krsa_get_diff(), krsa_sampling(), krsa_show_peptides(), krsa_top_hits()

Examples

TRUE

Calculates LFC based on modeled pw data and grouping

Description

This function takes in the modeled pw data, groups, peptides, and an option to perform the calculation per chip (byChip)

Usage

krsa_group_diff(
  data,
  groups,
  peps,
  samples = NULL,
  byChip = T,
  Barcodes = NULL
)

Arguments

data

modeled pw data
groups

a vector. format: (case, control)
peps

peptide list
samples

sample names
byChip

T or F, to calculate per chip
Barcodes

(optional) Barcodes vector

Value

LFC krsa table

See Also

Other core functions: krsa(), krsa_quick_filter(), krsa_read(), krsa_scaleModel()

Examples

TRUE

Generates a heatmap based on the modeled pw data

Description

This function takes in the modeled pw data, peptides and produces and pheatmap

Usage

krsa_heatmap(data, peptides, samples = NULL, groups = NULL, ...)

Arguments

data

modeled pw data
peptides

peptide list
samples

(optional) sample names
groups

(optional) group names
...

to pass to the pheatmap function

Value

pheatmap object

See Also

Other plots: krsa_ball_model(), krsa_coverage_plot(), krsa_curve_plot(), krsa_cv_plot(), krsa_heatmap_grouped(), krsa_histogram_plot(), krsa_reverse_krsa_plot(), krsa_violin_plot(), krsa_violin_plot_grouped(), krsa_waterfall(), krsa_zscores_plot()

Examples

TRUE

Generates a grouped heatmap

Description

This function takes in the grouped modeled pw data, peptides and produces a pheatmap object

Usage

krsa_heatmap_grouped(data, peptides, groups = NULL, ...)

Arguments

data

grouped modeled pw data
peptides

peptide list
groups

(optional) group names
...

arguments passed to pheatmap()

Value

pheatmap object

See Also

Other plots: krsa_ball_model(), krsa_coverage_plot(), krsa_curve_plot(), krsa_cv_plot(), krsa_heatmap(), krsa_histogram_plot(), krsa_reverse_krsa_plot(), krsa_violin_plot(), krsa_violin_plot_grouped(), krsa_waterfall(), krsa_zscores_plot()

Examples

TRUE

Generates kinase histogram plots based on the KRSA function output

Description

This function takes in Z score table, and count matrix (an output from krsa()) and generates distribution histograms for a list of kinases

Usage

krsa_histogram_plot(data, data2, kinases)

Arguments

data

Z score table from krsa()
data2

count matrix from krsa()
kinases

a vector of kinases

Value

ggplot object

See Also

Other plots: krsa_ball_model(), krsa_coverage_plot(), krsa_curve_plot(), krsa_cv_plot(), krsa_heatmap(), krsa_heatmap_grouped(), krsa_reverse_krsa_plot(), krsa_violin_plot(), krsa_violin_plot_grouped(), krsa_waterfall(), krsa_zscores_plot()

Examples

TRUE

KRSA kinase-substrate mapping file for PamChip 86402 PTK (v1 mapping)

Description

A data frame of the built-in KRSA kinase-substrate mapping file for PamChip 86402 PTK (v1 mapping)

Usage

data("KRSA_Mapping_PTK_PamChip_86402_v1")

Format

A data frame with 192 rows and 2 variables:

Substrates

Peptide IDs

Kinases

mapped kinases separated by spaces

KRSA kinase-substrate mapping file for PamChip 87102 STK (v1 mapping)

Description

A data frame of the built-in KRSA kinase-substrate mapping file for PamChip 87102 STK (v1 mapping)

Usage

data("KRSA_Mapping_STK_PamChip_87102_v1")

Format

A data frame with 141 rows and 2 variables:

Substrates

Peptide IDs

Kinases

mapped kinases separated by spaces

QC pre-processing of raw data (deals with negative values, and adjust signal saturation values)

Description

This function takes in the raw data and QC pre-processes it (deals with negative values, and adjust signal saturation values)

Usage

krsa_qc_steps(df, sat_qc = T)

Arguments

df

krsa raw data
sat_qc

to filter out data point with high SignalSaturation

Value

df

See Also

Other QC functions: krsa_filter_lowPeps(), krsa_filter_nonLinear(), krsa_filter_ref_pep()

Examples

TRUE

Filters out low signal peptides AND none linear peptides

Description

This function takes in pw data max exposure, modeled pw data, signal threshold, R2 threshold, and samples and groups names (optional) and returns peptides that passed these conditions

Usage

krsa_quick_filter(
  data,
  data2,
  signal_threshold,
  r2_threshold,
  samples = NULL,
  groups = NULL
)

Arguments

data

pw data max exposure
data2

modeled pw data
signal_threshold

signal threshold
r2_threshold

R2 threshold
samples

sample names
groups

group names

Value

vector of peptides

See Also

Other core functions: krsa(), krsa_group_diff(), krsa_read(), krsa_scaleModel()

Examples

TRUE

Read crosstab format files exported from bioNavigator and tidy them

Description

This function takes in paths to the median signal minus background (Median_SigmBg) and signal saturation (Signal_Saturation) files and parse and tidy them

Usage

krsa_read(signal_file, signal_saturation)

Arguments

signal_file

path to median signal minus background file (Median_SigmBg)
signal_saturation

path to signal saturation file (Signal_Saturation)

Value

tbl_df

See Also

Other core functions: krsa(), krsa_group_diff(), krsa_quick_filter(), krsa_scaleModel()

Examples

TRUE

Generates the reverse krsa plot (to examine kinase activity)

Description

This function takes in chipCov df, the LFC table, kinases, LFC threshold, and generates the reverse krsa plot (to examine kinase activity)

Usage

krsa_reverse_krsa_plot(
  chipCov,
  lfc_table,
  kinases,
  lfc_thr,
  byChip = T,
  facet = F
)

Arguments

chipCov

chipCov df for eaither STK or PTK
lfc_table

the LFC table
kinases

vector of kinases
lfc_thr

LFC threshold
byChip

will facet by Barcode
facet

facet by chip

Value

ggplot object

See Also

Other plots: krsa_ball_model(), krsa_coverage_plot(), krsa_curve_plot(), krsa_cv_plot(), krsa_heatmap(), krsa_heatmap_grouped(), krsa_histogram_plot(), krsa_violin_plot(), krsa_violin_plot_grouped(), krsa_waterfall(), krsa_zscores_plot()

Examples

TRUE

Performs random sampling of peptides and mapped kinases

Description

This function takes number of iterations, coverage file, kinase-substrate mapping df, and the length of the set of peptides to resample

Usage

krsa_sampling(x, CovFile, map, sum_num)

Arguments

x

number of iterations
CovFile

kinase coverage df
map

kinase-substrate mapping df
sum_num

number of peptides to resample

Value

count of kinases hits to random peptides

See Also

Other helper functions: enrichr_lib_call(), krsa_ce_output_kinases(), krsa_ce_output_peptides(), krsa_enrichr(), krsa_extractEndPoint(), krsa_extractEndPointMaxExp(), krsa_get_diff(), krsa_get_diff_byChip(), krsa_show_peptides(), krsa_top_hits()

Examples

TRUE

Fits, scales, transforms, and normalize kinome array data

Description

Runs a linear model on the tidy kinome array data of the signal as a function of exposure time. It also scales, transforms, and normalize kinome array data based on the barcode

Usage

krsa_scaleModel(df, pep, nobs_filter = 0)

Arguments

df

kinome array data tidy data
pep

Peptide List
nobs_filter

min number of data points to fit linear model

Value

list of scaled , normalized and grouped modeled data

See Also

Other core functions: krsa(), krsa_group_diff(), krsa_quick_filter(), krsa_read()

Examples

TRUE

Determine number of peptides inside lists

Description

Takes in list of significant peptides and calculates length of each set

Usage

krsa_show_peptides(sigPeps_list)

Arguments

sigPeps_list

list of significant peptides

Value

tibble with length of peptide sets

See Also

Other helper functions: enrichr_lib_call(), krsa_ce_output_kinases(), krsa_ce_output_peptides(), krsa_enrichr(), krsa_extractEndPoint(), krsa_extractEndPointMaxExp(), krsa_get_diff(), krsa_get_diff_byChip(), krsa_sampling(), krsa_top_hits()

Examples

TRUE

Extracts top kinase hits based on a Z cutoff

Description

Take in Z score table and extract top kinases based on a Z score cutoff

Usage

krsa_top_hits(zTable, z_thr)

Arguments

zTable

Z score table from krsa()
z_thr

Z score cutoff

Value

vector of top kinases

See Also

Other helper functions: enrichr_lib_call(), krsa_ce_output_kinases(), krsa_ce_output_peptides(), krsa_enrichr(), krsa_extractEndPoint(), krsa_extractEndPointMaxExp(), krsa_get_diff(), krsa_get_diff_byChip(), krsa_sampling(), krsa_show_peptides()

Examples

TRUE

Generates violin plots based on peptides signals intensities

Description

Takes in the scaled dataset from krsa_scaleModel() and plot violin figures using ggplot2

Usage

krsa_violin_plot(
  data,
  peptides,
  facet_factor,
  facet = T,
  samples = NULL,
  groups = NULL,
  show_legend = F
)

Arguments

data

the scaled dataset from krsa_scaleModel
peptides

vector of peptides
facet_factor

Column used to facet by. Will be used in facet_wrap(). Needs argument facet to be True.
facet

boolean to facet the plot by a variable
samples

(optional) a vector of sample names
groups

(optional) a vector of group names
show_legend

to show legend (default = FALSE)

Value

ggplot figure

See Also

Other plots: krsa_ball_model(), krsa_coverage_plot(), krsa_curve_plot(), krsa_cv_plot(), krsa_heatmap(), krsa_heatmap_grouped(), krsa_histogram_plot(), krsa_reverse_krsa_plot(), krsa_violin_plot_grouped(), krsa_waterfall(), krsa_zscores_plot()

Examples

TRUE

Generates grouped violin plots based on peptides signals intensities with t tests options

Description

Takes in the scaled dataset from krsa_scaleModel() and plot violin figures using ggplot2

Usage

krsa_violin_plot_grouped(
  data,
  peptides,
  grp_comp = NULL,
  groups = NULL,
  test = F,
  test_method = "wilcox.test",
  violin = TRUE,
  dots = FALSE,
  lines = FALSE,
  avg_line = T,
  ...
)

Arguments

data

the scaled dataset from krsa_scaleModel
peptides

vector of peptides
grp_comp

list of group comparison names
groups

(optional) a vector of group names
test

perform two group test
test_method

type of test (default is wilcox.test)
violin

add violin layer
dots

add dotplot layer
lines

add lines layer
avg_line

draw averaged line across the two groups
...

arguments passed to ggsignif

Value

ggplot figure

See Also

Other plots: krsa_ball_model(), krsa_coverage_plot(), krsa_curve_plot(), krsa_cv_plot(), krsa_heatmap(), krsa_heatmap_grouped(), krsa_histogram_plot(), krsa_reverse_krsa_plot(), krsa_violin_plot(), krsa_waterfall(), krsa_zscores_plot()

Examples

TRUE

Generates a waterfall figure based on the LFC table

Description

Takes in the LFC table and a LFC cuttoff and generates a waterfall plot using a ggplot.

Usage

krsa_waterfall(data, lfc_thr, byChip = T, sd_thr = Inf)

Arguments

data

LFC table
lfc_thr

LFC cutoff for plot
byChip

boolean Select T if the LFC is based on a byChip analysis
sd_thr

SD cutoff for plot

Value

ggplot object

See Also

Other plots: krsa_ball_model(), krsa_coverage_plot(), krsa_curve_plot(), krsa_cv_plot(), krsa_heatmap(), krsa_heatmap_grouped(), krsa_histogram_plot(), krsa_reverse_krsa_plot(), krsa_violin_plot(), krsa_violin_plot_grouped(), krsa_zscores_plot()

Examples

TRUE

Generates a waterfall figure based on the Z score table

Description

Takes in the Z score table and generates a waterfall plot using a ggplot.

Usage

krsa_zscores_plot(Ztable)

Arguments

Ztable

Z score table

Value

ggplot object

See Also

Other plots: krsa_ball_model(), krsa_coverage_plot(), krsa_curve_plot(), krsa_cv_plot(), krsa_heatmap(), krsa_heatmap_grouped(), krsa_histogram_plot(), krsa_reverse_krsa_plot(), krsa_violin_plot(), krsa_violin_plot_grouped(), krsa_waterfall()

Examples

TRUE

Parse bionavigator crosstab files

Description

Main function that parses bionavigator crosstab view files. Takes in path to file and type (either Signal or SignalSaturation)

Usage

parse_BN_crosstabFile(file_path, type = c("Signal", "SignalSaturation"))

Arguments

file_path

path to BN crosstab file
type

Name of the value (either Signal or SignalSaturation)

Value

tbl_df

Examples

TRUE

CDRL Complete mapping of peptides to HGNC symbols (PTK PamChip 86402)

Description

A data frame of CDRL Complete mapping CDRL Complete mapping of peptides to HGNC symbols (PTK PamChip 86402)

Usage

data("ptk_pamchip_86402_mapping")

Format

A data frame with 193 rows and 2 variables:

CDRL Complete mapping of peptides to HGNC symbols (STK PamChip 87102)

Description

A data frame of CDRL Complete mapping CDRL Complete mapping of peptides to HGNC symbols (STK PamChip 87102)

Usage

data("stk_pamchip_87102_mapping")

Format

A data frame with 141 rows and 2 variables: