Title: Omics Data Process Toolbox
Version: 1.0.5
Date: 2023-06-29
Description: Processing and analyzing omics data from genomics, transcriptomics, proteomics, and metabolomics platforms. It provides functions for preprocessing, normalization, visualization, and statistical analysis, as well as machine learning algorithms for predictive modeling. 'omicsTools' is an essential tool for researchers working with high-throughput omics data in fields such as biology, bioinformatics, and medicine.The QC-RLSC (quality control–based robust LOESS signal correction) algorithm is used for normalization. Dunn et al. (2011) <doi:10.1038/nprot.2011.335>.
License: MIT + file LICENSE
Imports: bs4Dash, config (≥ 0.3.1), dplyr, DT, golem (≥ 0.3.5), magrittr, readr, shiny (≥ 1.7.2), tibble
Encoding: UTF-8
RoxygenNote: 7.2.3
Suggests: spelling, testthat (≥ 3.0.0)
Config/testthat/edition: 3
URL: https://github.com/YaoxiangLi/omicsTools
BugReports: https://github.com/YaoxiangLi/omicsTools/issues
NeedsCompilation: no
Packaged: 2023-06-30 18:20:54 UTC; bach
Author: Yaoxiang Li ORCID iD [cre, aut], Zihao Zhang [aut], Meth Jayatilake [aut], Amrita Cheema ORCID iD [aut]
Maintainer: Yaoxiang Li <liyaoxiang@outlook.com>
Repository: CRAN
Date/Publication: 2023-07-03 16:20:02 UTC

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Arguments

lhs

A value or the magrittr placeholder.

rhs

A function call using the magrittr semantics.

Value

The result of calling 'rhs(lhs)'.

Impute function

Description

This function performs data cleaning and imputation on a given data matrix. It removes blank and NIST samples, features with NA values more than the specified threshold, and imputes remaining NA values with half of the smallest non-NA value.

Usage

impute(data, percent = 0.2)

Arguments

data

A data frame containing the sample data. The first column should contain the sample identifiers, and the rest of the columns contain the peaks.

percent

A numeric value between 0 and 1 representing the threshold of the percentage of NA values a feature should have for it to be removed from the dataset. Default value is 0.2.

Value

A data frame with the first column as the sample identifiers and the rest of the columns containing the cleaned and imputed peak intensities.

Author(s)

Yaoxiang Li yl814@georgetown.edu

Georgetown University, USA

License: GPL (>= 3)

Examples


# Load the CSV data
data_file <- system.file("extdata", "example1.csv", package = "omicsTools")
data <- readr::read_csv(data_file)
# Apply the impute function
imputed_data <- omicsTools::impute(data, percent = 0.2)


# Write the imputed data to a new CSV file
readr::write_csv(imputed_data, paste0(tempdir(), "/imputed_data.csv"))

Normalize function

Description

This function performs normalization on the input data matrix using the loess regression method. Normalization is done based on Quality Control (QC) samples in the data.

Usage

normalize(data)

Arguments

data

A data frame containing the sample data. The first column should contain the sample identifiers, and the rest of the columns contain the peaks to be normalized. QC samples should be indicated in the sample identifiers with 'QC'.

Value

A data frame with the first column as the sample identifiers and the rest of the columns containing the normalized peak intensities.

Author(s)

Yaoxiang Li yl814@georgetown.edu

Georgetown University, USA

License: GPL (>= 3)

Examples


# Load the CSV data
data_file <- system.file("extdata", "example2.csv", package = "omicsTools")
data <- readr::read_csv(data_file)
# Apply the normalize function
normalized_data <- omicsTools::normalize(data)


# Write the normalized data to a new CSV file
readr::write_csv(normalized_data, paste0(tempdir(), "/normalized_data.csv"))

Run the Shiny Application

Description

Run the Shiny Application

Usage

run_app(
  onStart = NULL,
  options = list(),
  enableBookmarking = NULL,
  uiPattern = "/",
  ...
)

Arguments

onStart

A function that will be called before the app is actually run. This is only needed for shinyAppObj, since in the shinyAppDir case, a global.R file can be used for this purpose.

options

Named options that should be passed to the runApp call (these can be any of the following: "port", "launch.browser", "host", "quiet", "display.mode" and "test.mode"). You can also specify width and height parameters which provide a hint to the embedding environment about the ideal height/width for the app.

enableBookmarking

Can be one of "url", "server", or "disable". The default value, NULL, will respect the setting from any previous calls to enableBookmarking(). See enableBookmarking() for more information on bookmarking your app.

uiPattern

A regular expression that will be applied to each GET request to determine whether the ui should be used to handle the request. Note that the entire request path must match the regular expression in order for the match to be considered successful.

...

arguments to pass to golem_opts. See '?golem::get_golem_options' for more details.

Value

No return value, called for launch the application.