OmicFlow (version 1.4.2)

proteomics: Sub-class proteomics

Description

This is a sub-class that is compatible to preprocessed data obtained from https://fragpipe.nesvilab.org/. It inherits all methods from the abstract class omics and only adapts the initialize function. It supports pre-existing data structures or paths to text files. When omics data is very large, data loading becomes very expensive. It is therefore recommended to use the reset() method to reset your changes. Every omics class creates an internal memory efficient back-up of the data, the resetting of changes is an instant process.

Super class

OmicFlow::omics -> proteomics

Public fields

countData

A path to an existing file, data.table, data.frame, matrix or sparseMatrix with zero values.

metaData

A path to an existing file, data.table or data.frame.

featureData

A path to an existing file, data.table or data.frame.

treeData

A path to an existing newick file or class "phylo", see read.tree.

Methods

Public methods

• proteomics$new()

• proteomics$print()

• proteomics$reset()

• proteomics$removeZeros()

Inherited methods

• OmicFlow::omics$DFE()
• OmicFlow::omics$alpha_diversity()
• OmicFlow::omics$autoFlow()
• OmicFlow::omics$composition()
• OmicFlow::omics$distance()
• OmicFlow::omics$feature_merge()
• OmicFlow::omics$feature_subset()
• OmicFlow::omics$normalize()
• OmicFlow::omics$ordination()
• OmicFlow::omics$rankstat()
• OmicFlow::omics$removeNAs()
• OmicFlow::omics$sample_subset()
• OmicFlow::omics$samplepair_subset()
• OmicFlow::omics$transform()
• OmicFlow::omics$validate()

---

Method new()

Initializes the proteomics class object with proteomics$new()

Usage

proteomics$new(countData = NA, metaData = NA, featureData = NA, treeData = NA)

Arguments

countData

A path to an existing file, data.table, data.frame, matrix or sparseMatrix with zero values.

metaData

A path to an existing file, data.table or data.frame.

featureData

A path to an existing file, data.table or data.frame.

treeData

A path to an existing newick file or class "phylo", see read.tree.

Returns

A new proteomics object.

---

Method print()

Displays parameters of the proteomics object via stdout.

Usage

proteomics$print()

Returns

object in place

Examples

library("OmicFlow")

metadata_file <- system.file("extdata", "metadata.tsv", package = "OmicFlow") counts_file <- system.file("extdata", "counts.tsv", package = "OmicFlow") features_file <- system.file("extdata", "features.tsv", package = "OmicFlow") tree_file <- system.file("extdata", "tree.newick", package = "OmicFlow")

prot <- proteomics$new( metaData = metadata_file, countData = counts_file, featureData = features_file, treeData = tree_file )

# method 1 to call print function prot

# method 2 to call print function prot$print()

---

Method reset()

Upon creation of a new proteomics object a small backup of the original data is created. Since modification of the object is done by reference and duplicates are not made, it is possible to reset changes to the class. The methods from the abstract class omics also contains a private method to prevent any changes to the original object when using methods such as ordination alpha_diversity or $DFE.

Usage

proteomics$reset()

Returns

object in place

Examples

library("OmicFlow")

metadata_file <- system.file("extdata", "metadata.tsv", package = "OmicFlow") counts_file <- system.file("extdata", "counts.tsv", package = "OmicFlow") features_file <- system.file("extdata", "features.tsv", package = "OmicFlow") tree_file <- system.file("extdata", "tree.newick", package = "OmicFlow")

prot <- proteomics$new( metaData = metadata_file, countData = counts_file, featureData = features_file, treeData = tree_file )

# Performs modifications prot$transform(log2)

# resets prot$reset()

---

Method removeZeros()

Removes empty (zero) values by row, column and tips from the countData and treeData. This method is performed automatically during subsetting of the object.

Usage

proteomics$removeZeros()

Returns

object in place

Examples

library("OmicFlow")

metadata_file <- system.file("extdata", "metadata.tsv", package = "OmicFlow") counts_file <- system.file("extdata", "counts.tsv", package = "OmicFlow") features_file <- system.file("extdata", "features.tsv", package = "OmicFlow") tree_file <- system.file("extdata", "tree.newick", package = "OmicFlow")

prot <- proteomics$new( metaData = metadata_file, countData = counts_file, featureData = features_file, treeData = tree_file )

# Sample subset induces empty features prot$sample_subset(treatment == "tumor")

# Remove empty features from countData and treeData prot$removeZeros()

See Also

omics

Examples

## ------------------------------------------------
## Method `proteomics$print`
## ------------------------------------------------

library("OmicFlow")

metadata_file <- system.file("extdata", "metadata.tsv", package = "OmicFlow")
counts_file <- system.file("extdata", "counts.tsv", package = "OmicFlow")
features_file <- system.file("extdata", "features.tsv", package = "OmicFlow")
tree_file <- system.file("extdata", "tree.newick", package = "OmicFlow")

prot <- proteomics$new(
 metaData = metadata_file,
 countData = counts_file,
 featureData = features_file,
 treeData = tree_file
)

# method 1 to call print function
prot

# method 2 to call print function
prot$print()


## ------------------------------------------------
## Method `proteomics$reset`
## ------------------------------------------------

library("OmicFlow")

metadata_file <- system.file("extdata", "metadata.tsv", package = "OmicFlow")
counts_file <- system.file("extdata", "counts.tsv", package = "OmicFlow")
features_file <- system.file("extdata", "features.tsv", package = "OmicFlow")
tree_file <- system.file("extdata", "tree.newick", package = "OmicFlow")

prot <- proteomics$new(
 metaData = metadata_file,
 countData = counts_file,
 featureData = features_file,
 treeData = tree_file
)

# Performs modifications
prot$transform(log2)

# resets
prot$reset()


## ------------------------------------------------
## Method `proteomics$removeZeros`
## ------------------------------------------------

library("OmicFlow")

metadata_file <- system.file("extdata", "metadata.tsv", package = "OmicFlow")
counts_file <- system.file("extdata", "counts.tsv", package = "OmicFlow")
features_file <- system.file("extdata", "features.tsv", package = "OmicFlow")
tree_file <- system.file("extdata", "tree.newick", package = "OmicFlow")

prot <- proteomics$new(
 metaData = metadata_file,
 countData = counts_file,
 featureData = features_file,
 treeData = tree_file
)

# Sample subset induces empty features
prot$sample_subset(treatment == "tumor")

# Remove empty features from countData and treeData
prot$removeZeros()