MMRFVariant_PlotbyEffectImpact: MMRFVariant_PlotbyEffectImpact

In marziasettino/MMRFVariant: R package for variant analysis from MMRF-CoMMpass data source

MMRFVariant_PlotbyEffectImpact

Description

draws plot of annotated variants by Impact and Effect

Usage

MMRFVariant_PlotbyEffectImpact(
  variant.ann,
  ListSNPs,
  topN = 20,
  filenm = "PlotbyEffectImpact",
  height = 10,
  width = 10
)

Arguments

variant.ann	is the dataframe of annotated variants downloaded from MMRF-Commpass Researcher Gateway (i.e. MMRF_CoMMpass_IA14a_All_Canonical_Variants file) and imported into environment
topN	is the top number of variant count
filenm	is the name of the png file. If filenm is Null, the plot is draw but it is not saved.
height	Image height
width	Image width
ListSNP	is the list of the SNPs to analyze.

Value

plot with the top count of the dbSNP variant categorized by Impact

Examples

variant.ann<- data.frame(public_id=c("MMRF_0000","MMRF_0001",
                                     "MMRF_0002","MMRF_0003",
                                     "MMRF_0004","MMRF_0005",
                                     "MMRF_0006","MMRF_0007",
                                     "MMRF_0008",""),                  
                 dbSNP=c(rep("rs755588843",2),rep("rs569344016",5),rep("rs2066497",2),rep(".",1)),                                                    
                 Effect=c(rep("intragenic_variant",3),
                           rep("missense_variant",2),
                           rep("intron_variant",1),
                           rep("5_prime_UTR_variant",4)),
                  Gene=c(rep("PRDM16",3),
                           rep("AGO1",2),
                           rep("FPGT-TNNI3K",1),
                           rep("TNNI3K",4)), 
                 REF=c(rep("C",3),
                           rep("G",2),
                           rep("A",1),
                           rep("T",4)),                            
                 ALT=c(rep("GGCCT",3),
                           rep("G",2),
                           rep("T",1),
                           rep("A",4)),    
                  Biotype=c(rep("protein_coding",6),
                           rep("antisense",2),
                           rep("processed_pseudogene",2)),   
                           
                 Impact= c(rep("MODERATE",2),rep("MODIFIER",2),
                            rep("LOW",3),rep("HIGH",2),rep("MODIFIER",1)),
                 feature_type= c(rep("ENST00000388718",2),rep("ENST00000344616",2),
                            rep("ENST00000431492",3),rep("ENST00000390268",2),rep("ENST00000316407",1)),
                            
                 SIFT= c(rep("0.035,0.035,0.057,0.057,0.035,0.042,0.04,0.058",2),rep("0.002,0.002,0.001,0.002",2),
                            rep("0.614,0.614,0.781",6)),           
                            
                 Polyphen2=c(rep("0.021,0.986,0.884,0.977",2),rep("0.99",2),
                            rep("0.614,0.781",6))           
                                                              
                                 
 )




summary.plot<-MMRFVariant_PlotbyEffectImpact(variant.ann,topN=50,height=10, width=15, filenm="PlotbyEffect")

marziasettino/MMRFVariant documentation built on March 28, 2023, 3:16 p.m.