Package 'neuroimaGene'

Title: Transcriptomic Atlas of Neuroimaging Derived Phenotypes
Description: Contains functions to query and visualize the Neuroimaging features associated with genetically regulated gene expression (GReX). The primary utility, neuroimaGene(), relies on a list of user-defined genes and returns a table of neuroimaging features (NIDPs) associated with each gene. This resource is designed to assist in the interpretation of genome-wide and transcriptome-wide association studies that evaluate brain related traits. Bledsoe (2024) <doi:10.1016/j.ajhg.2024.06.002>. In addition there are several visualization functions that generate summary plots and 2-dimensional visualizations of regional brain measures. Mowinckel (2020).
Authors: Xavier Bledsoe [aut, cre] , Eric Gamazon [aut]
Maintainer: Xavier Bledsoe <[email protected]>
License: GPL (>= 3)
Version: 0.1.2
Built: 2024-12-09 09:40:33 UTC
Source: CRAN

Help Index


NIDP annotation data

Description

annotation data for all NIDPs taken from the UKbiobank

Format

A data.table with 10 columns and 3935 rows:

gwas_phenotype

character: UKB-derived neuroimaging derived phenotype (NIDP)

modality

character: MRI neuroimaging modality

atlas

character: neuroimaging cortical atlas

side

character: right or left hemisphere or midline/whole brain

primary

character: primary cortical region

secondary

character: secondary cortical region

region

character: named region of the brain

measurement

character: morphology measurement

fMRI_node_1

character: fMRI node 1

fMRI_node_2

character: fMRI node 2

NIDP

character: user-friendly name for each NIDP

Value

This script has no return. This is a documentation file for the annotation dataset for all neuroimaging derived phenotypes.

Source

Bledsoe, X. (2024) A transcriptomic atlas of the human brain reveals genetically determined aspects of neuropsychiatric health


Check neuroimaGene database downloaded

Description

Check if the NeuroimaGene database exists in the proper location prior to running the query and prompt user to download if not.

Usage

check_db(timeout = 900)

Arguments

timeout

time to spend downloading the NeuroimaGene database in seconds (default = 900)

Value

no return value, called to give information on status of neuroimaGene database and prompt user the user to download if resource file is missing.

Examples

check_db(timeout = 600)

NIDP freesurfer annotation data

Description

Freesurfer names for select cortical and subcortical NIDPs

Usage

data(fs_anno)

Format

A data.table with 7 columns and 890 rows:

gwas_phenotype

character: UKB-derived neuroimaging derived phenotype

atl

character: neuroimaging cortical atlas

hemisphere

character: right or left hemisphere or midline/whole brain

secondary

character: secondary cortical region

fs_name

character: freesurfer name

label

character: label name for the region

atlas

character: freesurfer name for neuroimaging cortical atlas

Value

This script has no return. This is a documentation file for the annotation dataset for all neuroimaging derived phenotypes in the fsbrain package.

Source

Bledsoe, X. (2024) A transcriptomic atlas of the human brain reveals genetically determined aspects of neuropsychiatric health


List NIDPs

Description

Supplies a list of all NIDPs by name for any given modality or atlas

Usage

listNIDPs(modality = NA, atlas = NA, filename = NA, verbose = FALSE)

Arguments

modality

Neuroimaging modality. Defaults to NA; see README for additional options

atlas

Neuroimaging parcellation atlas for NIDP query. Defaults to NA; see README for additional options

filename

optional filename for writing data to a table

verbose

print runtime messages to R console. Default to FALSE

Value

a list of NIDP names satisfying the required criteria

Examples

dk_names <- listNIDPs(modality = 'T1', atlas = 'Desikan')

2D visualization plot of a neuroimaGene object

Description

Generates a 2D visualization plot of the neuroimaGene object. Neuroimaging regions are defined by the atlas parameter and colored according to the magnitude and direction of the aggregate effect from each gene in the NeuroimaGene object. Colors can be defined by the user.

Usage

neuro_vis(
  ng_obj,
  atlas = "Desikan",
  lowcol = "red2",
  midcol = "white",
  highcol = "royalblue2",
  title = NA
)

Arguments

ng_obj

NeuroimaGene object produced by neuroimaGene() function

atlas

desired atlas for visualization. Desikan (default), Subcortex, DKT, Destrieux.

lowcol

color for low end of Zscore spectrum. Default is dark red

midcol

color for middle of Zscore spectrum. Default is white

highcol

color for top end of Zscore spectrum. Default is blue4

title

optional title tag for the plot

Value

class: ggplot object depicting 2D visualization of the NIDPs from the neuroimaGene object portrayed on the brain and shaded by mean effect size.

Examples

gene_list <- c('TRIM35', 'PROSER3', 'EXOSC6', 'PICK1', 'UPK1A', 'ESPNL', 'ZIC4')
ng <- neuroimaGene(gene_list, atlas = NA, mtc = 'BH', vignette = TRUE)
neuro_vis(ng, atlas = 'DKT')

Main neuroimaGene query

Description

Using a user supplied vector of genes (Ensembl ID's or HUGO names), this function queries the NeuroimaGene resource for all statistically significant GReX-NIDP associations and returns all findings as a data.table.

Usage

neuroimaGene(
  gene_list,
  modality = "T1",
  atlas = "Desikan",
  mtc = "BH",
  nidps = NA,
  filename = NA,
  verbose = FALSE,
  vignette = FALSE
)

Arguments

gene_list

List of genes to work as inputs. There are no defaults.

modality

Neuroimaging modality for NIDP query. Defaults to T1 structural NIDPs. Other common options include 'dMRI' for diffusion MRI imaging and 'fMRI' for fucntional MRI image results.

atlas

Neuroimaging parcellation atlas for NIDP query. Defaults to Desikan structural atlas. Common T1 atlases include the 'DKT', and 'Destrieux' cortical atlases and 'Subcortex' for freesurfer parcellation of subrotical regions. See package documentation or vignette for full list.

mtc

Statistical multiple testing correction for NIDP query. This defaults to 'BH' for the Benjamini Hochberg False Discovery Rate. Other options include 'BF' for the bonferroni family wise error rate and 'nom' for nominal findings at pvalue <= 0.05.

nidps

optional user defined vector of target NIDPs to query. Specific NIDP names can be obtained from the listNIDPnames() function. Use of this parameter overrides the multiple testing correction, returning all nominally significant findings.

filename

optional user defined path/filename to which the script will write the nueroimaGene output data table.

verbose

print runtime messages to R console. Default to FALSE

vignette

use for building vignette on installation. Default to FALSE

Value

a neuroimaGene object: data table with all significant associations between the user provided genes and the UKB NIDPs satisfying the multiple testing correction and atlas/modality/name filters.

Examples

gene_list <- c('TRIM35', 'PROSER3', 'EXOSC6', 'PICK1', 'UPK1A', 'ESPNL', 'ZIC4')
ng <- neuroimaGene(gene_list, atlas = NA, mtc = 'BH', vignette = TRUE)

NeuroimaGene object for vignette illustration

Description

NeuroimaGene data table containing select associations used in the package vignette.

Usage

data(ng_vignette)

Format

A data.table with 6 columns and 3824 rows:

gene

character: ENSEMBL Gene ID

gene_name

character: HUGO gene name

gwas_phenotype

character: neuroimaging derived phenotype

training_model

character: JTI derived tissue gene expression model

zscore

numeric: normalized effect size of GReX on NIDP morphology

mod_BHpval

character: Benjamini Hochberg corrected pvalue corrected by modality

Value

This script has no return. This is a documentation file for the neuroimaGene data subset required to build the vignette.

Source

Bledsoe, X. (2024) A transcriptomic atlas of the human brain reveals genetically determined aspects of neuropsychiatric health


Gene by NIDP summary plot of neuroimaGene object

Description

Generate overview plot of the neuroimagene object according to gene/NIDP pair

Usage

plot_gnNIDP(
  ng_obj,
  maxNidps = 20,
  maxGns = 15,
  title = NA,
  shortnames = TRUE,
  verbose = FALSE
)

Arguments

ng_obj

NeuroimaGene object

maxNidps

maximum number of NIDPs to visualize. default=20

maxGns

maximum number of genes to visualize. default=15

title

optional title tag for the plot

shortnames

optional boolean tag for simplified names. Default to TRUE

verbose

print runtime messages to R console. Default to FALSE

Value

a ggplot class heatmap showing tissue models per NIDP/Gene pair

Examples

gene_list <- c('TRIM35', 'PROSER3', 'EXOSC6', 'PICK1', 'UPK1A', 'ESPNL', 'ZIC4')
ng <- neuroimaGene(gene_list, atlas = NA, mtc = 'BH', vignette = TRUE)
plot_gnNIDP(ng)

Gene summary plot of neuroimaGene object

Description

Generates an overview plot of the neuroimaGene object according to each gene input.

Usage

plot_gns(ng_obj, maxGns = 15, title = NA, verbose = FALSE)

Arguments

ng_obj

NeuroimaGene Object

maxGns

maximum number of genes to visualize. default=15

title

optional title tag for the plot

verbose

print runtime messages to R console. Default to FALSE

Value

a ggplot class plot detailing NIDPs per gene, colored by brain measure type

Examples

gene_list <- c('TRIM35', 'PROSER3', 'EXOSC6', 'PICK1', 'UPK1A', 'ESPNL', 'ZIC4')
ng <- neuroimaGene(gene_list, atlas = NA, mtc = 'BH', vignette = TRUE)
plot_gns(ng)

NIDP summary plot of NeuroimaGene object

Description

Generate overview plot of the neuroimagene object according to nidps

Usage

plot_nidps(
  ng_obj,
  maxNidps = 30,
  title = NA,
  shortnames = TRUE,
  mag = TRUE,
  verbose = FALSE
)

Arguments

ng_obj

NeuroimaGene Object

maxNidps

maximum number of NIDPs to visualize. default=30

title

optional title tag for the plot

shortnames

optional boolean tag for simplified names. Default to TRUE

mag

boolean to present effect sizes by magnitude rather than as a vector. Default to TRUE

verbose

print runtime messages to R console. Default to FALSE

Value

a ggplot class object detailing mean effect size magnitude per NIDP, colored by brain region

Examples

gene_list <- c('TRIM35', 'PROSER3', 'EXOSC6', 'PICK1', 'UPK1A', 'ESPNL', 'ZIC4')
ng <- neuroimaGene(gene_list, atlas = NA, mtc = 'BH', vignette = TRUE)
plot_nidps(ng)