Package 'HoloFoodR'

Title: R interface to EBI HoloFood resource
Description: Utility package to facilitate integration and analysis of EBI HoloFood data in R. This package streamlines access to the resource, allowing for direct loading of data into formats optimized for downstream analytics.
Authors: Tuomas Borman [aut, cre] , Leo Lahti [aut]
Maintainer: Tuomas Borman <[email protected]>
License: Artistic-2.0 | file LICENSE
Version: 1.1.0
Built: 2024-11-01 03:35:31 UTC
Source: https://github.com/bioc/HoloFoodR

Help Index

Add results from MGnifyR to HoloFoodR results

Description

Add results from MGnifyR to HoloFoodR results

Usage

addMGnify(x, y, ...)

## S4 method for signature 'SummarizedExperiment,MultiAssayExperiment'
addMGnify(
  x,
  y,
  exp.name1 = "metagenomic",
  exp.name2 = "metagenomic_amplicon",
  replace = TRUE,
  ...
)

## S4 method for signature 'SummarizedExperiment,SummarizedExperiment'
addMGnify(x, y, ...)

## S4 method for signature 'SummarizedExperiment,ANY'
addMGnify(x, y, id.col1 = "sample_biosample", id.col2 = "accession", ...)

Arguments

x

SummarizedExperiment. Results from MGnifyR::getResult().
y

MultiAssayExperiment or SummarizedExperiment or data.frame-like table. Results from HoloFoodR::getResult() or sample metadata from it.
...

optional arguments not used currently.
exp.name1

Character scalar. Specifies the name of experiment that will be added to y. (Default: "metagenomic")
exp.name2

Character scalar. Specifies the name of experiment from HoloFoodR results. This experiment is used to match IDs with MGnify data. (Default: "metagenomic_amplicon")
replace

Logical scalar. Whether to replace the template experiment. (Default: TRUE)
id.col1

Character scalar. Specifies the name of column from colData(x) that includes HoloFood identifiers. (Default: "sample_biosample")
id.col2

Character scalar. Specifies the name of column from colData(y[[exp.name2]]) that includes HoloFood identifiers. (Default: "accession")

Details

Metagenomic data is found in MGnify rather than HoloFoodR, and the two databases use different sample identifiers. However, MGnify's sample metadata includes references to the identifiers used in the HoloFood database, making it straightforward to convert sample IDs for alignment with HoloFood data. Despite this, HoloFood contains additional metadata not available in MGnify. Moreover, integrating data into a MultiAssayExperiment while maintaining accurate sample and system matches can be challenging.

This function is designed to simplify these tasks, enabling seamless integration of MGnify data with HoloFood data after retrieval from the database. You need only to input the returned data from MGnifyR::getResult() and HoloFoodR::getResult() functions.

Value

MultiAssayExperiment

Examples

## Not run: 
# Get data from HoloFood database
mae <- HoloFoodR::getResult(
    salmon_sample_ids,
    use.cache = TRUE
)

# Get data from MGnify database
mg <- MgnifyClient(
    useCache = TRUE,
    cacheDir = ".MGnifyR_cache"
)
tse <- MGnifyR::getResult(
    mg,
    accession = mgnify_analyses_ids,
    get.func = FALSE
)

# Add MGnify data to HoloFood data
mae <- addMGnify(tse, mae)

## End(Not run)

Search HoloFood database for animals, genome catalogues, samples, or viral catalogues

Description

Search HoloFood database for animals, genome catalogues, samples, or viral catalogues

Usage

doQuery(type, flatten = TRUE, ...)

Arguments

type

Character scalar specifying the type of data to query. Must be one of the following options: "animals", "genome-catalogues", "samples" or "viral-catalogues".
flatten

Logical scalar specifying whether to flatten the resulting data.frame. This means that columns with multiple values are separated to multiple columns. (Default: TRUE)
...

optional arguments:

  • max.hits NULL or integer scalar specifying the maximum number of results to fetch. When NULL, all results are fetched. (Default: NULL)

  • spread.sample.types Logical scalar specifying whether to create spread sample types column of animals data. In animals data, sample types column might have multiple values that might be hard to explore. This argument specifies whether to create presence/absence table from sample types. (Default: TRUE)

  • use.cache Logical scalar specifying whether to use cache. (Default: FALSE)

  • cache.dir Character scalar specifying cache directory. (Default: tempdir())

  • clear.cache Logical scalar specifying whether to remove and clear cache (Default: FALSE)

Details

doQuery is a flexible query function which can be utilized to search available animals, genome catalogues, samples, or viral catalogues. Search results can be filtered; for example, animals can be filtered based on available samples. See [Api browser](https://www.holofooddata.org/api/docs) for information on filters. You can find help on customizing queries from [here](https://emg-docs.readthedocs.io/en/latest/api.html#customising-queries).

Value

data.frame

Examples

# Find animals results. The maximum amount of results is 100. Use filter
# so that only chicken is searched.
res <- doQuery("animals", max.hits = 100, system = "chicken")
head(res)

Get data from HoloFood database

Description

Get data from HoloFood database

Usage

getData(
  type = NULL,
  accession.type = NULL,
  accession = NULL,
  flatten = FALSE,
  ...
)

Arguments

type

NULL or character scalar specifying the type of data to query. Must be one of the following options: "analysis-summaries", "animals", "genome-catalogues", "samples", "sample_metadata_markers" or "viral-catalogues". When genome or viral catalogues is fetched by their accession ID, the type can also be "genomes" or "fragments". (Default: NULL)
accession.type

NULL or character scalar specifying the type of accession IDs. Must be one of the following options: "animals", "genome-catalogues", "samples" or "viral-catalogues". (Default: NULL)
accession

NULL or character vector specifying the accession IDs of type accession.type. (Default: NULL)
flatten

Logical scalar specifying whether to flatten the resulting data.frame. This means that columns with multiple values are separated to multiple columns. (Default: FALSE)
...

optional arguments:

  • max.hits NULL or integer scalar specifying the maximum number of results to fetch. When NULL, all results are fetched. (Default: NULL)

  • use.cache Logical scalar specifying whether to use cache (Default: FALSE)

  • cache.dir Character scalar specifying cache directory. (Default: tempdir())

  • clear.cache Logical scalar specifying whether to remove and clear cache (Default: FALSE)

Details

With getData, you can fetch data from the database. Compared to getResult, this function is more flexible since it can fetch any kind of data from the database. However, this function returns the data without further wrangling as list or data.frame which are not optimized format for fetching data on samples.

Search results can be filtered; for example, animals can be filtered based on available samples. See [Api browser](https://www.holofooddata.org/api/docs) for information on filters. You can find help on customizing queries from [here](https://emg-docs.readthedocs.io/en/latest/api.html#customising-queries).

Value

list or data.frame

See Also

getResult

Examples

# Find genome catalogues
catalogues <- getData(type = "genome-catalogues")
head(catalogues)

# Find genomes based on certain genome catalogue iD
res <- getData(
    type = "genomes", accession.type = "genome-catalogues",
    accession = catalogues[1, "id"], max.hits = 100)
# See the data.
head(res)
# It includes for instance summary of the CAZy
# (Carbohydrate-Active enZymes) annotations as a counts per category
cazy <- res[ , grepl("annotations.cazy", colnames(res)), drop = FALSE]
head(cazy)
# Moreover, it includes a sample list. This sample list represents a 
# collection of samples where the MAG was identified. Thr data has also the
# completeness of MAG in a sample.
head(res[ c("metadata.Sample_accession", "metadata.Completeness")])

Get metabolomic data from MetaboLights database

Description

Get metabolomic data from MetaboLights database

Usage

getMetaboLights(study.id, ...)

getMetaboLightsFile(study.id, file, ...)

Arguments

study.id

character vector specifying the study identifier of data that is going to be fetched from the MetaboLights database.
...

optional arguments:

  • cache.dir Character scalar specifying directory where downloaded file is stored. (Default: tempdir())

  • timeout Integer scalar specifying timeout in seconds for loading a file. (Default: 5*60)

file

character vector specifying the files that are being fetched.

Details

The HoloFood database primarily comprises targeted metabolomic data, omitting non-targeted metabolomic information. Nonetheless, it features URLs linking to studies within the MetaboLights database. This functionality enables users to access non-targeted metabolomic data. The getMetaboLights function returns a structured list encompassing processed data in data.frame format for study metadata, assay metadata, and assay.

The metadata includes the file names of spectra data. Those files can be loaded with getMetaboLightsFile. Alternatively, once you've identified the study and files to fetch, you can refer to this [vignette](https://rformassspectrometry.github.io/MsIO/articles/MsIO.html#loading-data-from-metabolights) for instructions on loading the data directly into an MsExperiment object, specifically designed for metabolomics spectra data.

Value

list

See Also

getResult getData

Examples

# This example is not run, because the server fails to respond sometimes.
if( FALSE ){
    res <- getMetaboLights("MTBLS4381")
    file_paths <- getMetaLightsFile(
        study.id = "MTBLS4381",
        file = res[["assay_meta"]][["Raw Spectral Data File"]]
        )
}

Get data on samples from HoloFood database

Description

Get data on samples from HoloFood database

Usage

getResult(accession, ...)

Arguments

accession

Character vector specifying the accession IDs of type samples.
...

optional arguments:

  • use.cache Logical scalar specifying whether to use cache. Note that when get.metabolomic = TRUE is specified, the file from the MetaboLights is stored in the local system to the location specified by cache.dir despite of the value of use.cache. (Default: FALSE)

  • cache.dir Character scalar specifying cache directory. (Default: tempdir())

  • clear.cache Logical scalar specifying whether to use.cache (Default: FALSE)

  • assay.type Character scalar specifying the name of assay in resulting TreeSummarizedExperiment object. (Default: "counts")

  • get.metabolomic Logical scalar specifying whether to retrieve processed metabolomic data from MetaboLights database. For retrieving spectra data, refer to getMetaboLights documentation. (Default: FALSE)

Details

With getResult, you can fetch data on samples from the HoloFood database. Compared to getData, this function is more convenient for fetching the samples data because it converts the data to MultiAssayExperiment where different omics are stored as TreeSummarizedExperiment objects which are optimized for downstream analytics. Columns of returned MultiAssayExperiment are individual animals. These columns are linked with individual samples that are stored in TreeSummarizedExperiment objects.

The HoloFood database lacks non-targeted metabolomic data but they can be fetched from MetaboLights resource. Certain datasets include processed features. Those datasets can be retrieved with the function getResult which integrates metabolomic data with other datasets from HoloFood.

Furthermore, while the HoloFoodR database does not include metagenomic assembly data, users can access such data from the MGnify database. The MGnifyR package provides a convenient interface for accessing this database. By employing MGnifyR::getResult(), users can obtain data formatted as a MultiAssayExperiment object, containing multiple TreeSummarizedExperiment objects. Consequently, data from both HoloFood and MGnify databases are inherently compatible for subsequent downstream analysis.

Value

MultiAssayExperiment

See Also

getData TreeSummarizedExperiment MultiAssayExperiment MGnifyR:getResult

Examples

# Find samples on certain animal
samples <- doQuery("samples", animal_accession = "SAMEA112904746")

# Get the data
mae <- getResult(samples[["accession"]])
mae

HoloFoodR package

Description

HoloFoodR implements an interface to the EBI HoloFood database. See the vignette for a general introduction to this package, [about HoloFood](https://www.holofood.eu/) for general HoloFood information, and [API documentation](https://docs.holofooddata.org/api.html) for details on the JSONAPI implementation.

Author(s)

Maintainer: Tuomas Borman [email protected] (ORCID)

Authors:

See Also

TreeSummarizedExperiment MultiAssayExperiment