Gene_Centric_Noncoding_Results_Summary: Summarize gene-centric noncoding analysis results generated...

In xihaoli/STAARpipelineSummary: Summarization and Visualization of Analysis Results Generated by STAARpipeline

Summarize gene-centric noncoding analysis results generated by STAARpipeline package

Description

The Gene_Centric_Noncoding_Results_Summary function takes in the objects of gene-centric noncoding analysis results generated by STAARpipeline package, the object from fitting the null model, and the set of known variants to be adjusted for in conditional analysis to summarize the gene-centric noncoding analysis results and analyze the conditional association between a quantitative/dichotomous phenotype (including imbalanced case-control design) and the rare variants in the unconditional significant noncoding masks.

Usage

Gene_Centric_Noncoding_Results_Summary(
  agds_dir,
  gene_centric_noncoding_jobs_num,
  input_path,
  output_path,
  gene_centric_results_name,
  ncRNA_jobs_num,
  ncRNA_input_path,
  ncRNA_output_path,
  ncRNA_results_name,
  obj_nullmodel,
  known_loci = NULL,
  cMAC_cutoff = 0,
  method_cond = c("optimal", "naive"),
  rare_maf_cutoff = 0.01,
  QC_label = "annotation/filter",
  variant_type = c("SNV", "Indel", "variant"),
  geno_missing_imputation = c("mean", "minor"),
  Annotation_dir = "annotation/info/FunctionalAnnotation",
  Annotation_name_catalog,
  Use_annotation_weights = FALSE,
  Annotation_name = NULL,
  alpha = 2.5e-06,
  alpha_ncRNA = 2.5e-06,
  ncRNA_pos = NULL,
  manhattan_plot = FALSE,
  QQ_plot = FALSE,
  cond_null_model_name = NULL,
  cond_null_model_dir = NULL,
  SPA_p_filter = FALSE,
  p_filter_cutoff = 0.05
)

Arguments

agds_dir	a data farme containing directory of GDS/aGDS files.
gene_centric_noncoding_jobs_num	the number of results for gene-centric noncoding analysis of protein-coding genes generated by STAARpipeline package.
input_path	the directory of gene-centric noncoding analysis results for protein-coding genes that generated by STAARpipeline package.
output_path	the directory for the output files of the summary of gene-centric noncoding analysis results for protein-coding genes.
gene_centric_results_name	the file name of gene-centric noncoding analysis results for protein-coding genes generated by STAARpipeline package.
ncRNA_jobs_num	the number of results for gene-centric noncoding analysis of ncRNA genes generated by STAARpipeline package..
ncRNA_input_path	the directory of gene-centric noncoding analysis results for ncRNA genes that generated by STAARpipeline package.
ncRNA_output_path	the directory for the output files of the summary of gene-centric noncoding analysis results for ncRNA genes.
ncRNA_results_name	file name of gene-centric noncoding analysis results for ncRNA genes that generated by STAARpipeline package.
obj_nullmodel	an object from fitting the null model, which is either the output from fit_nullmodel function in the STAARpipeline package, or the output from fitNullModel function in the GENESIS package and transformed using the genesis2staar_nullmodel function in the STAARpipeline package.
known_loci	the data frame of variants to be adjusted for in conditional analysis and should contain 4 columns in the following order: chromosome (CHR), position (POS), reference allele (REF), and alternative allele (ALT) (default = NULL).
cMAC_cutoff	the cutoff of the minimum number of the cumulative minor allele of variants in the masks when summarizing the results (default = 0).
method_cond	a character value indicating the method for conditional analysis. optimal refers to regressing residuals from the null model on known_loci as well as all covariates used in fitting the null model (fully adjusted) and taking the residuals; naive refers to regressing residuals from the null model on known_loci and taking the residuals (default = optimal).
rare_maf_cutoff	the cutoff of maximum minor allele frequency in defining rare variants (default = 0.01).
QC_label	channel name of the QC label in the GDS/aGDS file (default = "annotation/filter").
variant_type	type of variant included in the analysis. Choices include "SNV", "Indel", or "variant" (default = "SNV").
geno_missing_imputation	method of handling missing genotypes. Either "mean" or "minor" (default = "mean").
Annotation_dir	channel name of the annotations in the aGDS file (default = "annotation/info/FunctionalAnnotation").
Annotation_name_catalog	a data frame containing the name and the corresponding channel name in the aGDS file.
Use_annotation_weights	use annotations as weights or not (default = FALSE).
Annotation_name	a vector of annotation names used in STAAR (default = NULL).
alpha	p-value threshold of significant results of protein coding genes (default = 2.5E-06).
alpha_ncRNA	p-value threshold of significant results of ncRNA genes (default = 2.5E-06).
ncRNA_pos	positions of ncRNA genes, required for generating the Manhattan plot and Q-Q plot of the results of ncRNA genes (default=NULL).
manhattan_plot	output manhattan plot or not (default = FALSE).
QQ_plot	output Q-Q plot or not (default = FALSE).
cond_null_model_name	the null model name for conditional analysis in the SPA setting, only used for imbalanced case-control setting (default = NULL).
cond_null_model_dir	the directory of storing the null model for conditional analysis in the SPA setting, only used for imbalanced case-control setting (default = NULL).
SPA_p_filter	logical: are only the variants with a normal approximation based p-value smaller than a pre-specified threshold use the SPA method to recalculate the p-value, only used for imbalanced case-control setting (default = FALSE).
p_filter_cutoff	threshold for the p-value recalculation using the SPA method, only used for imbalanced case-control setting (default = 0.05).

Value

The function returns the following analysis results:

noncoding_sig.csv: a matrix that summarized the unconditional significant region detected by STAAR-O or STAAR-B in imbalanced case-control setting (STAAR-O/-B pvalue smaller than the threshold alpha), including gene name ("Gene name"), chromosome ("chr"), coding functional category ("Category"), number of variants ("#SNV"), and the unconditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting).

noncoding_sig_cond.csv: a matrix that summarized the conditional analysis results of the unconditional significant region detected by STAAR-O or STAAR-B in imbalanced case-control setting (available if known_loci is not a NULL), including gene name ("Gene name"), chromosome ("chr"), coding functional category ("Category"), number of variants ("#SNV"), and the conditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting).

results_UTR_genome: a matrix contains the STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the noncoding masks defined by UTR variants (UTR) for all protein-coding genes across the genome.

UTR_sig.csv: a matrix contains the unconditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant UTR masks.

UTR_sig_cond.csv: a matrix contains the conditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant UTR masks (available if known_loci is not a NULL).

results_upstream_genome: a matrix contains the STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the noncoding masks defined by upstream variants (upstream) for all protein-coding genes across the genome.

upstream_sig.csv: a matrix contains the unconditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant upstream masks.

upstream_sig_cond.csv: a matrix contains the conditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant upstream masks (available if known_loci is not a NULL).

results_downstream_genome: a matrix contains the STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the noncoding masks defined by downstream variants (downstream) for all protein-coding genes across the genome.

downstream_sig.csv: a matrix contains the unconditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant downstream masks.

downstream_sig_cond.csv: a matrix contains the conditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant downstream masks (available if known_loci is not a NULL).

results_promoter_CAGE_genome: a matrix contains the STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the noncoding masks defined by variants overlaid with CAGE sites in the promoter (promoter_CAGE) for all protein-coding genes across the genome.

promoter_CAGE_sig.csv: a matrix contains the unconditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant promoter_CAGE masks.

promoter_CAGE_sig_cond.csv: a matrix contains the conditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant promoter_CAGE masks (available if known_loci is not a NULL).

results_promoter_DHS_genome: a matrix contains the STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the noncoding masks defined by variants overlaid with DHS sites in the promoter (promoter_DHS) for all protein-coding genes across the genome.

promoter_DHS_sig.csv: a matrix contains the unconditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant promoter_DHS masks.

promoter_DHS_sig_cond.csv: a matrix contains the conditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant promoter_DHS masks (available if known_loci is not a NULL).

results_enhancer_CAGE_genome: a matrix contains the STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the noncoding masks defined by variants overlaid with CAGE sites in the enhancer (enhancer_CAGE) for all protein-coding genes across the genome.

enhancer_CAGE_sig.csv: a matrix contains the unconditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant enhancer_CAGE masks.

enhancer_CAGE_sig_cond.csv: a matrix contains the conditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant enhancer_CAGE masks (available if known_loci is not a NULL).

results_enhancer_DHS_genome: a matrix contains the STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the noncoding masks defined by variants overlaid with DHS sites in the enhancer (enhancer_DHS) for all protein-coding genes across the genome.

enhancer_DHS_sig.csv: a matrix contains the unconditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant enhancer_DHS masks.

enhancer_DHS_sig_cond.csv: a matrix contains the conditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant enhancer_DHS masks (available if known_loci is not a NULL).

results_ncRNA_genome: a matrix contains the STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the noncoding masks defined by exonic and splicing ncRNA variants (ncRNA) for all ncRNA genes across the genome.

ncRNA_sig.csv: a matrix contains the unconditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant ncRNA masks.

ncRNA_sig_cond.csv: a matrix contains the conditional STAAR p-values (including STAAR-O or STAAR-B in imbalanced case-control setting) of the unconditional significant ncRNA masks (available if known_loci is not a NULL).

manhattan plot (optional) and Q-Q plot (optional) of the gene-centric noncoding analysis results.

References

Li, Z., Li, X., et al. (2022). A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies. Nature Methods, 19(12), 1599-1611. (pub)

xihaoli/STAARpipelineSummary documentation built on July 27, 2024, 4:30 p.m.