View source: R/filterread_Solo_SVMerge.r
run_bionano_filter_SVMerge_solo | R Documentation |
Getting the data from annotated smaps to extract SV information based on type of variants.
run_bionano_filter_SVMerge_solo(
input_fmt_geneList = c("Text", "dataFrame"),
input_fmt_SV = c("Text", "dataFrame"),
EnzymeType = c("SE", "SVMerge"),
smap = NULL,
svData,
dat_geneList,
fileName,
outpath,
outputFilename = "",
RZIPpath,
primaryGenesPresent = TRUE,
outputType = c("Excel", "csv"),
directoryName,
fileprefix
)
input_fmt_geneList |
character. Choice of gene list input Text or Dataframe. |
input_fmt_SV |
character. Choice of gene list input Text or Dataframe. |
EnzymeType |
Character. Enzyme type used. Options SVMerge or SE. |
smap |
character. SV file name. |
svData |
Dataframe Input data containing SV data. |
dat_geneList |
Dataframe Input data containing geneList data. |
fileName |
Character Name of file containing Gene List data. |
outpath |
Character Directory to the output file. |
outputFilename |
Character Output filename. |
RZIPpath |
Character Path for the Rtools Zip package. |
primaryGenesPresent |
boolean Checks whether the primary gene List is present or not. |
outputType |
Character. Variants in excel tabs or in different csv files. Options Excel or csv. |
directoryName |
Character. Directory name where individual SV files will be stored. |
fileprefix |
Character. fileprefix to use for each of the files in the directory. |
Excel file containing the annotated SV map, tabs divided based on type of SVs.
smapName <- "NA12878_Q.S_VAP_SVmerge_solo5.txt"
outputFilename <- "NA12878_Q.S_VAP_SVmerge_solo5_out"
smappath <- system.file("extdata", smapName, package = "nanotatoR")
outpath <- system.file("extdata", smapName, package = "nanotatoR")
RZIPpath <- system.file("extdata", "zip.exe", package = "nanotatoR")
smap = system.file("extdata", smapName, package="nanotatoR")
bedFile <- system.file("extdata", "HomoSapienGRCH19_lift37.bed", package="nanotatoR")
outpath <- system.file("extdata", package="nanotatoR")
directoryName <- system.file("extdata", package="nanotatoR")
datcomp<-overlapnearestgeneSearch(smap = smap,
bed=bedFile, inputfmtBed = "bed", outpath,
n = 3, returnMethod_bedcomp = c("dataFrame"),
input_fmt_SV = "Text",
EnzymeType = "SVMerge",
bperrorindel = 3000, bperrorinvtrans = 50000)
hgpath=system.file("extdata", "GRCh37_hg19_variants_2016-05-15.txt", package="nanotatoR")
datDGV <- DGVfrequency (hgpath = hgpath,
smap_data = datcomp,
win_indel_DGV = 10000,
EnzymeType = "SVMerge",
input_fmt_SV = "dataFrame",
perc_similarity_DGV = 0.5,returnMethod="dataFrame")
indelconf = 0.5; invconf = 0.01;transconf = 0.1;
datInf <- internalFrequency_solo(smapdata = datDGV,
buildSVInternalDB=TRUE, win_indel=10000,
win_inv_trans=50000,
labelType = c("SE"),
EnzymeType = "SVMerge",
SE_path = system.file("extdata", "SoloFile/", package="nanotatoR"),
SE_pattern = "*_DLE1_*", perc_similarity_parents =0.9,
Samplecodes = system.file("extdata", "nanotatoR_sample_codes.csv", package="nanotatoR"),
mergeKey = system.file("extdata", "nanotatoR_control_sample_codes.csv", package="nanotatoR"),
mergedKeyoutpath = system.file("extdata", package="nanotatoR"),
mergedKeyFname = "Sample_index.csv",
indexfile = system.file("extdata", mergedKeyFname, package="nanotatoR"),
perc_similarity = 0.5, indelconf = 0.5, invconf = 0.01,
transconf = 0.1, limsize = 1000, win_indel_parents = 5000,
win_inv_trans_parents=40000,
returnMethod="dataFrame", input_fmt_SV = "dataFrame")
path <- system.file("extdata", "Bionano_config/", package = "nanotatoR")
pattern <- "*_hg19_*"
datBNDB <- BNDBfrequency(smapdata = datInf,
buildBNInternalDB=TRUE,
input_fmt_SV = "dataFrame",
dbOutput="dataframe",
EnzymeType = "SVMerge",
BNDBpath = path,
BNDBpattern = pattern,
fname, outpath,
win_indel = 10000,
win_inv_trans = 50000,
perc_similarity = 0.5,
indelconf = 0.5,
invconf = 0.01,
limsize = 1000,
transconf = 0.1,
returnMethod=c("dataFrame"))
decipherpath = system.file("extdata", "population_cnv.txt", package="nanotatoR")
datdecipher <- Decipherfrequency (decipherpath = decipherpath,
smap_data = datBNDB, win_indel = 10000,
perc_similarity = 0.5,returnMethod="dataFrame",
input_fmt_SV = "dataFrame", EnzymeType = c("SVMerge"))
run_bionano_filter_SVMerge_solo (input_fmt_geneList = c("Text"),
input_fmt_SV = c("dataFrame"),
svData = datdecipher,
dat_geneList = dat_geneList,
RZIPpath = RZIPpath, EnzymeType = c("SVMerge"),
outputType = c("csv"),
primaryGenesPresent = FALSE,
directoryName = directoryName,
fileprefix = "AnnotatedSamplesNA12878_SVMerge")
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