newFunctions.md
In markdunning/beadarray-devel: Quality assessment and low-level analysis for Illumina BeadArray data
New beadarray functionality
A demonstration of the proposed new functionality for beadarray
library(beadarray)
## Loading required package: BiocGenerics
## Loading required package: parallel
##
## Attaching package: 'BiocGenerics'
##
## The following objects are masked from 'package:parallel':
##
## clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
## clusterExport, clusterMap, parApply, parCapply, parLapply,
## parLapplyLB, parRapply, parSapply, parSapplyLB
##
## The following object is masked from 'package:stats':
##
## xtabs
##
## The following objects are masked from 'package:base':
##
## anyDuplicated, append, as.data.frame, as.vector, cbind,
## colnames, duplicated, eval, evalq, Filter, Find, get,
## intersect, is.unsorted, lapply, Map, mapply, match, mget,
## order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
## rbind, Reduce, rep.int, rownames, sapply, setdiff, sort,
## table, tapply, union, unique, unlist
##
## Loading required package: Biobase
## Welcome to Bioconductor
##
## Vignettes contain introductory material; view with
## 'browseVignettes()'. To cite Bioconductor, see
## 'citation("Biobase")', and for packages 'citation("pkgname")'.
##
## Loading required package: ggplot2
## Welcome to beadarray version 2.13.2
## beadarray versions >= 2.0.0 are substantial updates from beadarray 1.16.0 and earlier. Please see package vignette for details
library(GEOquery)
## Setting options('download.file.method.GEOquery'='curl')
library(limma)
##
## Attaching package: 'limma'
##
## The following object is masked from 'package:beadarray':
##
## imageplot
##
## The following object is masked from 'package:BiocGenerics':
##
## plotMA
library(GenomicRanges)
## Loading required package: IRanges
##
## Attaching package: 'IRanges'
##
## The following object is masked from 'package:beadarray':
##
## collapse
##
## Loading required package: XVector
A proposal is to faciliate the analyis of publicly-available data. We download the following example
url <- "ftp://ftp.ncbi.nih.gov/pub/geo/DATA/SeriesMatrix/GSE33126/"
filenm <- "GSE33126_series_matrix.txt.gz"
if (!file.exists("GSE33126_series_matrix.txt.gz")) download.file(paste(url,
filenm, sep = ""), destfile = filenm)
gse <- getGEO(filename = filenm)
## File stored at:
## /tmp/RtmpJoTabB/GPL6947.soft
head(exprs(gse))
## GSM820516 GSM820517 GSM820518 GSM820519 GSM820520 GSM820521
## ILMN_1343291 66665.4 69404.7 64128.1 68944.0 67827.2 71775.3
## ILMN_1343295 22040.1 13046.3 38679.0 16641.9 33719.9 18933.3
## ILMN_1651199 226.6 205.4 217.2 229.0 226.3 203.9
## ILMN_1651209 278.6 253.7 211.8 278.0 259.8 265.2
## ILMN_1651210 195.5 196.0 175.3 193.9 229.6 164.1
## ILMN_1651221 217.3 206.1 219.6 205.0 194.7 234.0
## GSM820522 GSM820523 GSM820524 GSM820525 GSM820526 GSM820527
## ILMN_1343291 62245.6 69713.7 69509.3 68244.6 65427.5 68436.5
## ILMN_1343295 26170.0 9906.9 17166.5 12429.0 25297.6 17535.6
## ILMN_1651199 213.4 210.4 229.5 212.7 226.1 232.2
## ILMN_1651209 321.3 273.4 253.6 310.2 275.0 275.0
## ILMN_1651210 244.7 191.0 188.1 199.3 220.6 213.4
## ILMN_1651221 233.2 222.1 244.2 209.8 227.8 256.0
## GSM820528 GSM820529 GSM820530 GSM820531 GSM820532 GSM820533
## ILMN_1343291 57608.7 69959.8 69509.3 70063.8 69647.2 70332.3
## ILMN_1343295 19749.1 17854.3 43670.7 22849.1 23725.7 28747.0
## ILMN_1651199 208.7 229.3 214.4 216.7 195.7 252.2
## ILMN_1651209 250.6 255.9 219.6 292.5 253.3 238.0
## ILMN_1651210 194.8 173.7 185.3 174.7 195.4 191.9
## ILMN_1651221 233.5 194.4 218.7 271.5 222.8 241.1
We can convert into a beadarray object
summaryData <- ExpressionSetFromGEO(gse)
## Loading required package: illuminaHumanv3.db
## Loading required package: AnnotationDbi
## Loading required package: org.Hs.eg.db
## Loading required package: DBI
summaryData
## ExpressionSetIllumina (storageMode: list)
## assayData: 48803 features, 18 samples
## element names: exprs, se.exprs, nObservations, Detection
## protocolData: none
## phenoData
## sampleNames: GSM820516 GSM820517 ... GSM820533 (18 total)
## varLabels: title geo_accession ... data_row_count (31 total)
## varMetadata: labelDescription
## featureData
## featureNames: ILMN_1343291 ILMN_1343295 ... ILMN_2416019 (48803
## total)
## fvarLabels: Row.names ID ... PROBESEQUENCE (8 total)
## fvarMetadata: labelDescription
## experimentData: use 'experimentData(object)'
## Annotation: Humanv3
## QC Information
## Available Slots:
## QC Items:
## sampleNames:
head(fData(summaryData))
## Row.names ID nuID Species
## ILMN_1343291 ILMN_1343291 ILMN_1343291 97viJ90hzUX_rZ.nvY Homo sapiens
## ILMN_1343295 ILMN_1343295 ILMN_1343295 9fQSYRUddRf4Z6p6T4 Homo sapiens
## ILMN_1651199 ILMN_1651199 ILMN_1651199 6OYpVKvaVZJlni1ChY Homo sapiens
## ILMN_1651209 ILMN_1651209 ILMN_1651209 60abGV06oA3Va4f0rU Homo sapiens
## ILMN_1651210 ILMN_1651210 ILMN_1651210 o7oTiLy97.l5Guommw Homo sapiens
## ILMN_1651221 ILMN_1651221 ILMN_1651221 EllV59GiXrVNBZYKng Homo sapiens
## SYMBOL PROBEQUALITY CODINGZONE
## ILMN_1343291 EEF1A1 Perfect Transcriptomic
## ILMN_1343295 GAPDH Perfect Transcriptomic
## ILMN_1651199 <NA> Bad Intergenic
## ILMN_1651209 SLC35E2 Perfect Transcriptomic
## ILMN_1651210 <NA> Bad Intergenic
## ILMN_1651221 EFCAB1 Bad Transcriptomic
## PROBESEQUENCE
## ILMN_1343291 TGTGTTGAGAGCTTCTCAGACTATCCACCTTTGGGTCGCTTTGCTGTTCG
## ILMN_1343295 CTTCAACAGCGACACCCACTCCTCCACCTTTGACGCTGGGGCTGGCATTG
## ILMN_1651199 ATGCGAGGCCCCAGGGTTCGGCCCCGCAGCGCCGCTGAGTCCAAGGACCG
## ILMN_1651209 TCACGGCGTACGCCCTCATGGGGAAAATCTCCCCGGTGACTTTCAGGTCC
## ILMN_1651210 TGTGGACATGAGAGTTAGTTCTGTTTTGCCTGCACGGTGGGAGCGGCGTA
## ILMN_1651221 GCCGCCCCCTGCTTCACGGAGCCTGGTCCCATCAACCGCCGAAGGGCTGA
Detection scores could be added by using the no match probes as negative controls. Possibly we could assignment of status when the object is created?
fData(summaryData)$Status <- ifelse(fData(summaryData)$PROBEQUALITY == "No match",
"negative", "regular")
Detection(summaryData) <- calculateDetection(summaryData, status = fData(summaryData)$Status)
Likewise for normalisation
summaryData.norm <- normaliseIllumina(summaryData, method = "neqc", status = fData(summaryData)$Status)
## Subsetting....
boxplot(summaryData.norm)
## Warning: Removed 6187 rows containing missing values (geom_point).
## Warning: Removed 6184 rows containing missing values (geom_point).
## Warning: Removed 6188 rows containing missing values (geom_point).
## Warning: Removed 6190 rows containing missing values (geom_point).
## Warning: Removed 6182 rows containing missing values (geom_point).
## Warning: Removed 6191 rows containing missing values (geom_point).
## Warning: Removed 6187 rows containing missing values (geom_point).
## Warning: Removed 6192 rows containing missing values (geom_point).
## Warning: Removed 6185 rows containing missing values (geom_point).
## Warning: Removed 6186 rows containing missing values (geom_point).
## Warning: Removed 6191 rows containing missing values (geom_point).
## Warning: Removed 6189 rows containing missing values (geom_point).
## Warning: Removed 6188 rows containing missing values (geom_point).
## Warning: Removed 6187 rows containing missing values (geom_point).
## Warning: Removed 6193 rows containing missing values (geom_point).
## Warning: Removed 6190 rows containing missing values (geom_point).
## Warning: Removed 6187 rows containing missing values (geom_point).
## Warning: Removed 6193 rows containing missing values (geom_point).
The user has to be able to select a column to use as Sample Groups
pData(summaryData)[1:3, ]
## title geo_accession status
## GSM820516 C1 (gene expression data) GSM820516 Public on Nov 26 2012
## GSM820517 C2 (gene expression data) GSM820517 Public on Nov 26 2012
## GSM820518 C3 (gene expression data) GSM820518 Public on Nov 26 2012
## submission_date last_update_date type channel_count
## GSM820516 Oct 20 2011 Nov 26 2012 RNA 1
## GSM820517 Oct 20 2011 Nov 26 2012 RNA 1
## GSM820518 Oct 20 2011 Nov 26 2012 RNA 1
## source_name_ch1 organism_ch1 characteristics_ch1
## GSM820516 tumor Homo sapiens tissue: Colon
## GSM820517 normal Homo sapiens tissue: Colon
## GSM820518 tumor Homo sapiens tissue: Colon
## characteristics_ch1.1 characteristics_ch1.2 molecule_ch1
## GSM820516 patient: 1 t=tumor; n=normal: T total RNA
## GSM820517 patient: 1 t=tumor; n=normal: N total RNA
## GSM820518 patient: 2 t=tumor; n=normal: T total RNA
## extract_protocol_ch1
## GSM820516 Tissues were mechanically disrupted and simultaneously homogenized in the presence of QIAzol Lysis reagent (Qiagen, Valencia, CA, USA), using a Mikrodismembrator (Braun Biotech International, Melsungen, Germany). RNA was extracted using the miRNeasy Mini kit (Qiagen) according to manufacturer’s instructions, followed by clean-up and DNase I treatment with QIAGEN RNeasy mini kit. RNA concentrations were measured with the NanoDrop ND-100 Spectrophotometer (NanoDrop Technologies, Wilmington, DE) while RNA quality was assessed with the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA) using the RNA 6000 Nano kit (Agilent Technologies). Samples, included in the present analysis, had a RIN score greater than 5 and a 28S:18S rRNA ratio near to 2:1.
## GSM820517 Tissues were mechanically disrupted and simultaneously homogenized in the presence of QIAzol Lysis reagent (Qiagen, Valencia, CA, USA), using a Mikrodismembrator (Braun Biotech International, Melsungen, Germany). RNA was extracted using the miRNeasy Mini kit (Qiagen) according to manufacturer’s instructions, followed by clean-up and DNase I treatment with QIAGEN RNeasy mini kit. RNA concentrations were measured with the NanoDrop ND-100 Spectrophotometer (NanoDrop Technologies, Wilmington, DE) while RNA quality was assessed with the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA) using the RNA 6000 Nano kit (Agilent Technologies). Samples, included in the present analysis, had a RIN score greater than 5 and a 28S:18S rRNA ratio near to 2:1.
## GSM820518 Tissues were mechanically disrupted and simultaneously homogenized in the presence of QIAzol Lysis reagent (Qiagen, Valencia, CA, USA), using a Mikrodismembrator (Braun Biotech International, Melsungen, Germany). RNA was extracted using the miRNeasy Mini kit (Qiagen) according to manufacturer’s instructions, followed by clean-up and DNase I treatment with QIAGEN RNeasy mini kit. RNA concentrations were measured with the NanoDrop ND-100 Spectrophotometer (NanoDrop Technologies, Wilmington, DE) while RNA quality was assessed with the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA) using the RNA 6000 Nano kit (Agilent Technologies). Samples, included in the present analysis, had a RIN score greater than 5 and a 28S:18S rRNA ratio near to 2:1.
## label_ch1
## GSM820516 biotin
## GSM820517 biotin
## GSM820518 biotin
## label_protocol_ch1
## GSM820516 Total RNA from each sample was labeled according to the manufacturers recommendations.
## GSM820517 Total RNA from each sample was labeled according to the manufacturers recommendations.
## GSM820518 Total RNA from each sample was labeled according to the manufacturers recommendations.
## taxid_ch1 hyb_protocol
## GSM820516 9606 Standard Illumina hybridization protocol
## GSM820517 9606 Standard Illumina hybridization protocol
## GSM820518 9606 Standard Illumina hybridization protocol
## scan_protocol description
## GSM820516 Standard Illumina scanning protocol 4660559081_A
## GSM820517 Standard Illumina scanning protocol 4660559081_G
## GSM820518 Standard Illumina scanning protocol 4668112004_B
## data_processing
## GSM820516 The data were extracted with BeadStudio software v3.8
## GSM820517 The data were extracted with BeadStudio software v3.8
## GSM820518 The data were extracted with BeadStudio software v3.8
## platform_id contact_name contact_email
## GSM820516 GPL6947 Loris,,De Cecco loris.dececco@istitutotumori.mi.it
## GSM820517 GPL6947 Loris,,De Cecco loris.dececco@istitutotumori.mi.it
## GSM820518 GPL6947 Loris,,De Cecco loris.dececco@istitutotumori.mi.it
## contact_institute contact_address contact_city
## GSM820516 IRCSS Istituto Nazionale Tumori via Venezian 1 Milan
## GSM820517 IRCSS Istituto Nazionale Tumori via Venezian 1 Milan
## GSM820518 IRCSS Istituto Nazionale Tumori via Venezian 1 Milan
## contact_zip/postal_code contact_country supplementary_file
## GSM820516 20133 Italy NONE
## GSM820517 20133 Italy NONE
## GSM820518 20133 Italy NONE
## data_row_count
## GSM820516 48803
## GSM820517 48803
## GSM820518 48803
summaryData.norm <- setSampleGroup(summaryData.norm, pData(summaryData)$source_name_ch1)
summaryData.norm <- simpleDE(summaryData.norm)
lapply(summaryData.norm@deResults, head)
## $PValue
## Contrasts
## normal-tumor
## ILMN_1343291 0.01954
## ILMN_1343295 0.00519
## ILMN_1651199 0.58731
## ILMN_1651209 0.34198
## ILMN_1651210 0.14014
## ILMN_1651221 0.72686
##
## $LogFC
## Contrasts
## normal-tumor
## ILMN_1343291 0.08385
## ILMN_1343295 -0.67556
## ILMN_1651199 0.01462
## ILMN_1651209 0.05275
## ILMN_1651210 -0.05360
## ILMN_1651221 0.01372
##
## $LogOdds
## Contrasts
## normal-tumor
## ILMN_1343291 -3.558
## ILMN_1343295 -2.323
## ILMN_1651199 -6.282
## ILMN_1651209 -5.959
## ILMN_1651210 -5.285
## ILMN_1651221 -6.373
beadarray:::volcanoplot(summaryData.norm)
A useful for function for picking the 'best' probe for each gene based on IQR (by default)
collapse
## standardGeneric for "collapse" defined from package "IRanges"
##
## function (x)
## standardGeneric("collapse")
## <environment: 0x4814af0>
## Methods may be defined for arguments: x
## Use showMethods("collapse") for currently available ones.
geneData <- beadarray:::collapse(summaryData)
## Error: no 'dimnames' attribute for array
geneData
## Error: object 'geneData' not found
A function that will get genomic locations for each probe and create a RangedData object
rng <- toRangedData(summaryData)
markdunning/beadarray-devel documentation built on May 21, 2019, noon
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New beadarray functionality
A demonstration of the proposed new functionality for beadarray
library(beadarray)
## Loading required package: BiocGenerics
## Loading required package: parallel
##
## Attaching package: 'BiocGenerics'
##
## The following objects are masked from 'package:parallel':
##
## clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
## clusterExport, clusterMap, parApply, parCapply, parLapply,
## parLapplyLB, parRapply, parSapply, parSapplyLB
##
## The following object is masked from 'package:stats':
##
## xtabs
##
## The following objects are masked from 'package:base':
##
## anyDuplicated, append, as.data.frame, as.vector, cbind,
## colnames, duplicated, eval, evalq, Filter, Find, get,
## intersect, is.unsorted, lapply, Map, mapply, match, mget,
## order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
## rbind, Reduce, rep.int, rownames, sapply, setdiff, sort,
## table, tapply, union, unique, unlist
##
## Loading required package: Biobase
## Welcome to Bioconductor
##
## Vignettes contain introductory material; view with
## 'browseVignettes()'. To cite Bioconductor, see
## 'citation("Biobase")', and for packages 'citation("pkgname")'.
##
## Loading required package: ggplot2
## Welcome to beadarray version 2.13.2
## beadarray versions >= 2.0.0 are substantial updates from beadarray 1.16.0 and earlier. Please see package vignette for details
library(GEOquery)
## Setting options('download.file.method.GEOquery'='curl')
library(limma)
##
## Attaching package: 'limma'
##
## The following object is masked from 'package:beadarray':
##
## imageplot
##
## The following object is masked from 'package:BiocGenerics':
##
## plotMA
library(GenomicRanges)
## Loading required package: IRanges
##
## Attaching package: 'IRanges'
##
## The following object is masked from 'package:beadarray':
##
## collapse
##
## Loading required package: XVector
A proposal is to faciliate the analyis of publicly-available data. We download the following example
url <- "ftp://ftp.ncbi.nih.gov/pub/geo/DATA/SeriesMatrix/GSE33126/"
filenm <- "GSE33126_series_matrix.txt.gz"
if (!file.exists("GSE33126_series_matrix.txt.gz")) download.file(paste(url,
filenm, sep = ""), destfile = filenm)
gse <- getGEO(filename = filenm)
## File stored at:
## /tmp/RtmpJoTabB/GPL6947.soft
head(exprs(gse))
## GSM820516 GSM820517 GSM820518 GSM820519 GSM820520 GSM820521
## ILMN_1343291 66665.4 69404.7 64128.1 68944.0 67827.2 71775.3
## ILMN_1343295 22040.1 13046.3 38679.0 16641.9 33719.9 18933.3
## ILMN_1651199 226.6 205.4 217.2 229.0 226.3 203.9
## ILMN_1651209 278.6 253.7 211.8 278.0 259.8 265.2
## ILMN_1651210 195.5 196.0 175.3 193.9 229.6 164.1
## ILMN_1651221 217.3 206.1 219.6 205.0 194.7 234.0
## GSM820522 GSM820523 GSM820524 GSM820525 GSM820526 GSM820527
## ILMN_1343291 62245.6 69713.7 69509.3 68244.6 65427.5 68436.5
## ILMN_1343295 26170.0 9906.9 17166.5 12429.0 25297.6 17535.6
## ILMN_1651199 213.4 210.4 229.5 212.7 226.1 232.2
## ILMN_1651209 321.3 273.4 253.6 310.2 275.0 275.0
## ILMN_1651210 244.7 191.0 188.1 199.3 220.6 213.4
## ILMN_1651221 233.2 222.1 244.2 209.8 227.8 256.0
## GSM820528 GSM820529 GSM820530 GSM820531 GSM820532 GSM820533
## ILMN_1343291 57608.7 69959.8 69509.3 70063.8 69647.2 70332.3
## ILMN_1343295 19749.1 17854.3 43670.7 22849.1 23725.7 28747.0
## ILMN_1651199 208.7 229.3 214.4 216.7 195.7 252.2
## ILMN_1651209 250.6 255.9 219.6 292.5 253.3 238.0
## ILMN_1651210 194.8 173.7 185.3 174.7 195.4 191.9
## ILMN_1651221 233.5 194.4 218.7 271.5 222.8 241.1
We can convert into a beadarray object
summaryData <- ExpressionSetFromGEO(gse)
## Loading required package: illuminaHumanv3.db
## Loading required package: AnnotationDbi
## Loading required package: org.Hs.eg.db
## Loading required package: DBI
summaryData
## ExpressionSetIllumina (storageMode: list)
## assayData: 48803 features, 18 samples
## element names: exprs, se.exprs, nObservations, Detection
## protocolData: none
## phenoData
## sampleNames: GSM820516 GSM820517 ... GSM820533 (18 total)
## varLabels: title geo_accession ... data_row_count (31 total)
## varMetadata: labelDescription
## featureData
## featureNames: ILMN_1343291 ILMN_1343295 ... ILMN_2416019 (48803
## total)
## fvarLabels: Row.names ID ... PROBESEQUENCE (8 total)
## fvarMetadata: labelDescription
## experimentData: use 'experimentData(object)'
## Annotation: Humanv3
## QC Information
## Available Slots:
## QC Items:
## sampleNames:
head(fData(summaryData))
## Row.names ID nuID Species
## ILMN_1343291 ILMN_1343291 ILMN_1343291 97viJ90hzUX_rZ.nvY Homo sapiens
## ILMN_1343295 ILMN_1343295 ILMN_1343295 9fQSYRUddRf4Z6p6T4 Homo sapiens
## ILMN_1651199 ILMN_1651199 ILMN_1651199 6OYpVKvaVZJlni1ChY Homo sapiens
## ILMN_1651209 ILMN_1651209 ILMN_1651209 60abGV06oA3Va4f0rU Homo sapiens
## ILMN_1651210 ILMN_1651210 ILMN_1651210 o7oTiLy97.l5Guommw Homo sapiens
## ILMN_1651221 ILMN_1651221 ILMN_1651221 EllV59GiXrVNBZYKng Homo sapiens
## SYMBOL PROBEQUALITY CODINGZONE
## ILMN_1343291 EEF1A1 Perfect Transcriptomic
## ILMN_1343295 GAPDH Perfect Transcriptomic
## ILMN_1651199 <NA> Bad Intergenic
## ILMN_1651209 SLC35E2 Perfect Transcriptomic
## ILMN_1651210 <NA> Bad Intergenic
## ILMN_1651221 EFCAB1 Bad Transcriptomic
## PROBESEQUENCE
## ILMN_1343291 TGTGTTGAGAGCTTCTCAGACTATCCACCTTTGGGTCGCTTTGCTGTTCG
## ILMN_1343295 CTTCAACAGCGACACCCACTCCTCCACCTTTGACGCTGGGGCTGGCATTG
## ILMN_1651199 ATGCGAGGCCCCAGGGTTCGGCCCCGCAGCGCCGCTGAGTCCAAGGACCG
## ILMN_1651209 TCACGGCGTACGCCCTCATGGGGAAAATCTCCCCGGTGACTTTCAGGTCC
## ILMN_1651210 TGTGGACATGAGAGTTAGTTCTGTTTTGCCTGCACGGTGGGAGCGGCGTA
## ILMN_1651221 GCCGCCCCCTGCTTCACGGAGCCTGGTCCCATCAACCGCCGAAGGGCTGA
Detection scores could be added by using the no match probes as negative controls. Possibly we could assignment of status when the object is created?
fData(summaryData)$Status <- ifelse(fData(summaryData)$PROBEQUALITY == "No match",
"negative", "regular")
Detection(summaryData) <- calculateDetection(summaryData, status = fData(summaryData)$Status)
Likewise for normalisation
summaryData.norm <- normaliseIllumina(summaryData, method = "neqc", status = fData(summaryData)$Status)
## Subsetting....
boxplot(summaryData.norm)
## Warning: Removed 6187 rows containing missing values (geom_point).
## Warning: Removed 6184 rows containing missing values (geom_point).
## Warning: Removed 6188 rows containing missing values (geom_point).
## Warning: Removed 6190 rows containing missing values (geom_point).
## Warning: Removed 6182 rows containing missing values (geom_point).
## Warning: Removed 6191 rows containing missing values (geom_point).
## Warning: Removed 6187 rows containing missing values (geom_point).
## Warning: Removed 6192 rows containing missing values (geom_point).
## Warning: Removed 6185 rows containing missing values (geom_point).
## Warning: Removed 6186 rows containing missing values (geom_point).
## Warning: Removed 6191 rows containing missing values (geom_point).
## Warning: Removed 6189 rows containing missing values (geom_point).
## Warning: Removed 6188 rows containing missing values (geom_point).
## Warning: Removed 6187 rows containing missing values (geom_point).
## Warning: Removed 6193 rows containing missing values (geom_point).
## Warning: Removed 6190 rows containing missing values (geom_point).
## Warning: Removed 6187 rows containing missing values (geom_point).
## Warning: Removed 6193 rows containing missing values (geom_point).
The user has to be able to select a column to use as Sample Groups
pData(summaryData)[1:3, ]
## title geo_accession status
## GSM820516 C1 (gene expression data) GSM820516 Public on Nov 26 2012
## GSM820517 C2 (gene expression data) GSM820517 Public on Nov 26 2012
## GSM820518 C3 (gene expression data) GSM820518 Public on Nov 26 2012
## submission_date last_update_date type channel_count
## GSM820516 Oct 20 2011 Nov 26 2012 RNA 1
## GSM820517 Oct 20 2011 Nov 26 2012 RNA 1
## GSM820518 Oct 20 2011 Nov 26 2012 RNA 1
## source_name_ch1 organism_ch1 characteristics_ch1
## GSM820516 tumor Homo sapiens tissue: Colon
## GSM820517 normal Homo sapiens tissue: Colon
## GSM820518 tumor Homo sapiens tissue: Colon
## characteristics_ch1.1 characteristics_ch1.2 molecule_ch1
## GSM820516 patient: 1 t=tumor; n=normal: T total RNA
## GSM820517 patient: 1 t=tumor; n=normal: N total RNA
## GSM820518 patient: 2 t=tumor; n=normal: T total RNA
## extract_protocol_ch1
## GSM820516 Tissues were mechanically disrupted and simultaneously homogenized in the presence of QIAzol Lysis reagent (Qiagen, Valencia, CA, USA), using a Mikrodismembrator (Braun Biotech International, Melsungen, Germany). RNA was extracted using the miRNeasy Mini kit (Qiagen) according to manufacturer’s instructions, followed by clean-up and DNase I treatment with QIAGEN RNeasy mini kit. RNA concentrations were measured with the NanoDrop ND-100 Spectrophotometer (NanoDrop Technologies, Wilmington, DE) while RNA quality was assessed with the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA) using the RNA 6000 Nano kit (Agilent Technologies). Samples, included in the present analysis, had a RIN score greater than 5 and a 28S:18S rRNA ratio near to 2:1.
## GSM820517 Tissues were mechanically disrupted and simultaneously homogenized in the presence of QIAzol Lysis reagent (Qiagen, Valencia, CA, USA), using a Mikrodismembrator (Braun Biotech International, Melsungen, Germany). RNA was extracted using the miRNeasy Mini kit (Qiagen) according to manufacturer’s instructions, followed by clean-up and DNase I treatment with QIAGEN RNeasy mini kit. RNA concentrations were measured with the NanoDrop ND-100 Spectrophotometer (NanoDrop Technologies, Wilmington, DE) while RNA quality was assessed with the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA) using the RNA 6000 Nano kit (Agilent Technologies). Samples, included in the present analysis, had a RIN score greater than 5 and a 28S:18S rRNA ratio near to 2:1.
## GSM820518 Tissues were mechanically disrupted and simultaneously homogenized in the presence of QIAzol Lysis reagent (Qiagen, Valencia, CA, USA), using a Mikrodismembrator (Braun Biotech International, Melsungen, Germany). RNA was extracted using the miRNeasy Mini kit (Qiagen) according to manufacturer’s instructions, followed by clean-up and DNase I treatment with QIAGEN RNeasy mini kit. RNA concentrations were measured with the NanoDrop ND-100 Spectrophotometer (NanoDrop Technologies, Wilmington, DE) while RNA quality was assessed with the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA) using the RNA 6000 Nano kit (Agilent Technologies). Samples, included in the present analysis, had a RIN score greater than 5 and a 28S:18S rRNA ratio near to 2:1.
## label_ch1
## GSM820516 biotin
## GSM820517 biotin
## GSM820518 biotin
## label_protocol_ch1
## GSM820516 Total RNA from each sample was labeled according to the manufacturers recommendations.
## GSM820517 Total RNA from each sample was labeled according to the manufacturers recommendations.
## GSM820518 Total RNA from each sample was labeled according to the manufacturers recommendations.
## taxid_ch1 hyb_protocol
## GSM820516 9606 Standard Illumina hybridization protocol
## GSM820517 9606 Standard Illumina hybridization protocol
## GSM820518 9606 Standard Illumina hybridization protocol
## scan_protocol description
## GSM820516 Standard Illumina scanning protocol 4660559081_A
## GSM820517 Standard Illumina scanning protocol 4660559081_G
## GSM820518 Standard Illumina scanning protocol 4668112004_B
## data_processing
## GSM820516 The data were extracted with BeadStudio software v3.8
## GSM820517 The data were extracted with BeadStudio software v3.8
## GSM820518 The data were extracted with BeadStudio software v3.8
## platform_id contact_name contact_email
## GSM820516 GPL6947 Loris,,De Cecco loris.dececco@istitutotumori.mi.it
## GSM820517 GPL6947 Loris,,De Cecco loris.dececco@istitutotumori.mi.it
## GSM820518 GPL6947 Loris,,De Cecco loris.dececco@istitutotumori.mi.it
## contact_institute contact_address contact_city
## GSM820516 IRCSS Istituto Nazionale Tumori via Venezian 1 Milan
## GSM820517 IRCSS Istituto Nazionale Tumori via Venezian 1 Milan
## GSM820518 IRCSS Istituto Nazionale Tumori via Venezian 1 Milan
## contact_zip/postal_code contact_country supplementary_file
## GSM820516 20133 Italy NONE
## GSM820517 20133 Italy NONE
## GSM820518 20133 Italy NONE
## data_row_count
## GSM820516 48803
## GSM820517 48803
## GSM820518 48803
summaryData.norm <- setSampleGroup(summaryData.norm, pData(summaryData)$source_name_ch1)
summaryData.norm <- simpleDE(summaryData.norm)
lapply(summaryData.norm@deResults, head)
## $PValue
## Contrasts
## normal-tumor
## ILMN_1343291 0.01954
## ILMN_1343295 0.00519
## ILMN_1651199 0.58731
## ILMN_1651209 0.34198
## ILMN_1651210 0.14014
## ILMN_1651221 0.72686
##
## $LogFC
## Contrasts
## normal-tumor
## ILMN_1343291 0.08385
## ILMN_1343295 -0.67556
## ILMN_1651199 0.01462
## ILMN_1651209 0.05275
## ILMN_1651210 -0.05360
## ILMN_1651221 0.01372
##
## $LogOdds
## Contrasts
## normal-tumor
## ILMN_1343291 -3.558
## ILMN_1343295 -2.323
## ILMN_1651199 -6.282
## ILMN_1651209 -5.959
## ILMN_1651210 -5.285
## ILMN_1651221 -6.373
beadarray:::volcanoplot(summaryData.norm)
A useful for function for picking the 'best' probe for each gene based on IQR (by default)
collapse
## standardGeneric for "collapse" defined from package "IRanges"
##
## function (x)
## standardGeneric("collapse")
## <environment: 0x4814af0>
## Methods may be defined for arguments: x
## Use showMethods("collapse") for currently available ones.
geneData <- beadarray:::collapse(summaryData)
## Error: no 'dimnames' attribute for array
geneData
## Error: object 'geneData' not found
A function that will get genomic locations for each probe and create a RangedData object
rng <- toRangedData(summaryData)
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