Calculate conditional celltype associations using MAGMA

Source: R/calculate_conditional_celltype_associations.R

Run cell-type enrichment analysis on a GWAS previously mapped to genes (using map_snps_to_genes) while controlling for certain cell-types. This allows one to conduct cell-type enrichment analyses while controlling for the strongest cell-type-specific signatures. Which cell-types are controlled for can be specified by either of the following arguments:

  • controlTopNcellsAutomatically selects the top N mostly significantly enriched cell-types.

  • controlledCTsA user-provided list of cell-types present in the ctd.

Three sets of analyses are run:

  • Baseline enrichment resultsNo conditioning.

  • Conditional results: separate conditioning on each specified cell-type separately

  • Conditional results: grouped conditioning all specified cell-types at once.

calculate_conditional_celltype_associations(
  ctd,
  ctd_species = infer_ctd_species(ctd),
  gwas_sumstats_path = NULL,
  magma_dir = NULL,
  analysis_name = "MainRun",
  prepare_ctd = TRUE,
  upstream_kb = 35,
  downstream_kb = 10,
  controlledAnnotLevel = 1,
  controlTopNcells = NA,
  controlledCTs = NA,
  EnrichmentMode = "Linear",
  qvalue_thresh = 0.05,
  force_new = FALSE,
  version = NULL,
  verbose = TRUE
)

Arguments

ctd

Cell type data structure containing specificity_quantiles.

ctd_species

Species name relevant to the CellTypeDataset (ctd). See list_species for all available species. If ctd_species=NULL (default), the ctd species will automatically be inferred using infer_species.

gwas_sumstats_path

File path of the summary statistics file.

magma_dir

Path to folder containing the pre-computed MAGMA GWAS files (.gsa.rawand .gsa.out).

analysis_name

Used in file names which area created.

prepare_ctd

Whether to run prepare_quantile_groups on the ctd first.

upstream_kb

How many kb upstream of the gene should SNPs be included?

downstream_kb

How many kb downstream of the gene should SNPs be included?

controlledAnnotLevel

Which annotation level should be controlled for.

controlTopNcells

How many of the most significant cell types at that annotation level should be controlled for?

controlledCTs

Array of the celltype to be controlled for, e.g. c('Interneuron type 16','Medium Spiny Neuron').

EnrichmentMode

[Optional] Should either 'Linear' or 'Top 10%' mode be used for testing enrichment?

qvalue_thresh

Multiple-testing corrected p-value threshold to filter by when determining which celltypes to condition with.

force_new

[Optional] Force new MAGMA analyses even if the pre-existing results files are detected.

version

MAGMA version to use.

verbose

Print messages.

Value

A concatenated results table containing:

  • Baseline enrichment results.

  • Conditional results: conditioning on each specified cell-type individually.

  • Conditional results: conditioning all specified cell-types at once.

Examples

#### Prepare cell-type data ####
ctd <- ewceData::ctd()
#> see ?ewceData and browseVignettes('ewceData') for documentation
#> loading from cache
#### Prepare GWAS MAGMA data ####
magma_dir <- MAGMA.Celltyping::import_magma_files(ids = "ieu-a-298")
#> Using built-in example files: ieu-a-298.tsv.gz.35UP.10DOWN
#> Returning MAGMA directories.
#### Run pipeline ####
ctAssocs <- calculate_conditional_celltype_associations(
    ctd = ctd,
    controlledAnnotLevel = 1,
    controlTopNcells = 1,
    qvalue_thresh = 1,
    magma_dir = magma_dir,
    ctd_species = "mouse", 
    force = TRUE) 
#> WARNING: Setting qvalue_thresh>0.05 is not reccommended in practice.
#> Installed MAGMA version: v1.10
#> Skipping MAGMA installation.
#> The desired_version of MAGMA is currently installed: v1.10
#> Using: magma_v1.10
#> Standardising CellTypeDataset
#> Found 5 matrix types across 2 CTD levels.
#> Processing level: 1
#> Processing level: 2
#> Converting to sparse matrix.
#> Converting to sparse matrix.
#> Installed MAGMA version: v1.10
#> Skipping MAGMA installation.
#> The desired_version of MAGMA is currently installed: v1.10
#> Using: magma_v1.10
#> ctd is already standardised. Returning original ctd.
#>  Set force_standardise=TRUE to re-standardise.
#> Converting to sparse matrix.
#> Converting to sparse matrix.
#> Running MAGMA: Linear mode
#> Mapping gene symbols in specificity_quantiles matrix to entrez IDs.
#> Reading enrichment results file into R.
#> Running MAGMA: Linear mode
#> Mapping gene symbols in specificity_quantiles matrix to entrez IDs.
#> Reading enrichment results file into R.
#> Mapping gene symbols in specificity_quantiles matrix to entrez IDs.
#> Mapping gene symbols in specificity_quantiles matrix to entrez IDs.
#> magma  
#>   --gene-results '/tmp/RtmpUbtMhH/MAGMA_Files/ieu-a-298.tsv.gz.35UP.10DOWN/ieu-a-298.tsv.gz.35UP.10DOWN.genes.raw' 
#>   --gene-covar '/tmp/RtmpUbtMhH/file1eb24a56104e' 
#>   --model direction=pos condition='oligodendrocytes' 
#>   --out '/tmp/RtmpUbtMhH/MAGMA_Files/ieu-a-298.tsv.gz.35UP.10DOWN/ieu-a-298.tsv.gz.35UP.10DOWN.level1.35UP.10DOWN.Linear.ControlFor_oligodendrocytes'
#> Reading enrichment results file into R.
#> magma  
#>   --gene-results '/tmp/RtmpUbtMhH/MAGMA_Files/ieu-a-298.tsv.gz.35UP.10DOWN/ieu-a-298.tsv.gz.35UP.10DOWN.genes.raw' 
#>   --gene-covar '/tmp/RtmpUbtMhH/file1eb24a56104e' 
#>   --model direction=pos condition='oligodendrocytes' 
#>   --out '/tmp/RtmpUbtMhH/MAGMA_Files/ieu-a-298.tsv.gz.35UP.10DOWN/ieu-a-298.tsv.gz.35UP.10DOWN.level1.35UP.10DOWN.ControlFor_oligodendrocytes'
#> Reading enrichment results file into R.
#> Mapping gene symbols in specificity_quantiles matrix to entrez IDs.
#> magma  
#>   --gene-results '/tmp/RtmpUbtMhH/MAGMA_Files/ieu-a-298.tsv.gz.35UP.10DOWN/ieu-a-298.tsv.gz.35UP.10DOWN.genes.raw' 
#>   --gene-covar '/tmp/RtmpUbtMhH/file1eb25d06c45b' 
#>   --model direction=pos condition='oligodendrocytes' 
#>   --out '/tmp/RtmpUbtMhH/MAGMA_Files/ieu-a-298.tsv.gz.35UP.10DOWN/ieu-a-298.tsv.gz.35UP.10DOWN.level2.35UP.10DOWN.Linear.ControlFor_oligodendrocytes'
#> Reading enrichment results file into R.
#> magma  
#>   --gene-results '/tmp/RtmpUbtMhH/MAGMA_Files/ieu-a-298.tsv.gz.35UP.10DOWN/ieu-a-298.tsv.gz.35UP.10DOWN.genes.raw' 
#>   --gene-covar '/tmp/RtmpUbtMhH/file1eb25d06c45b' 
#>   --model direction=pos condition='oligodendrocytes' 
#>   --out '/tmp/RtmpUbtMhH/MAGMA_Files/ieu-a-298.tsv.gz.35UP.10DOWN/ieu-a-298.tsv.gz.35UP.10DOWN.level2.35UP.10DOWN.ControlFor_oligodendrocytes'
#> Reading enrichment results file into R.