I trying to combine 2 vectors using cbind, both vectors are the same size, and I am having an error while i run the code, the vectors are quite big, length = 57605.
final=cbind (counts1,tx_by_gene)
> > Error: cannot allocate vector of size 225 Kb R(473,0xa0cb8540) malloc: *** mmap(size=233472) failed (error code=12)
> *** error: can't allocate region
> *** set a breakpoint in malloc_error_break to debug R(473,0xa0cb8540) malloc: *** mmap(size=233472) failed (error code=12)
> *** error: can't allocate region
> *** set a breakpoint in malloc_error_break to debug
Can anyone help me why am I having this error? or some other way of combining the 2 vectors?
thank you
> str(counts1) = int [1:57605] 0 0 0 0 0 0 0 0 0 0 ...
>str(tx_by_gene)
> Formal class 'GRangesList' [package "GenomicRanges"] with 5 slots ..# partitioning :Formal class 'PartitioningByEnd' [package
> "IRanges"] with 5 slots .. .. ..# end : int [1:57605] 3 5
> 12 17 27 36 42 46 58 60 ... .. .. ..# NAMES : chr [1:57605]
> "ENSG00000000003" "ENSG00000000005" "ENSG00000000419"
> "ENSG00000000457" ... .. .. ..# elementMetadata: NULL .. .. ..#
> elementType : chr "integer" .. .. ..# metadata : list()
> ..# unlistData :Formal class 'GRanges' [package "GenomicRanges"]
> with 7 slots .. .. ..# seqnames :Formal class 'Rle' [package
> "IRanges"] with 5 slots .. .. .. .. ..# values : Factor w/
> 93 levels "chr1","chr2",..: 8 20 1 6 1 8 6 3 7 13 ... .. .. .. ..
> ..# lengths : int [1:41694] 5 7 30 18 21 6 2 9 43 23 ... ..
> .. .. .. ..# elementMetadata: NULL .. .. .. .. ..# elementType :
> chr "ANY" .. .. .. .. ..# metadata : list() .. .. ..# ranges
> :Formal class 'IRanges' [package "IRanges"] with 6 slots .. .. .. ..
> ..# start : int [1:191891] 99883667 99887538 99888439
> 99839799 99848621 49551404 49551404 49551404 49551433 49551482 ...
> .. .. .. .. ..# width : int [1:191891] 8137 4149 6550 15084
> 3908 23684 23684 23689 10966 23577 ... .. .. .. .. ..# NAMES
> : NULL .. .. .. .. ..# elementMetadata: NULL .. .. .. .. ..#
> elementType : chr "integer" .. .. .. .. ..# metadata :
> list() .. .. ..# strand :Formal class 'Rle' [package
> "IRanges"] with 5 slots .. .. .. .. ..# values : Factor w/ 3
> levels "+","-","*": 2 1 2 1 2 1 2 1 2 1 ... .. .. .. .. ..# lengths
> : int [1:28670] 3 2 12 10 9 6 16 2 13 8 ... .. .. .. .. ..#
> elementMetadata: NULL .. .. .. .. ..# elementType : chr "ANY"
> .. .. .. .. ..# metadata : list() .. .. ..# seqlengths :
> Named int [1:93] 249250621 243199373 198022430 191154276 180915260
> 171115067 159138663 155270560 146364022 141213431 ... .. .. .. ..-
> attr(*, "names")= chr [1:93] "chr1" "chr2" "chr3" "chr4" ... .. ..
> ..# elementMetadata:Formal class 'DataFrame' [package "IRanges"] with
> 6 slots .. .. .. .. ..# rownames : NULL .. .. .. .. ..#
> nrows : int 191891 .. .. .. .. ..# elementMetadata: NULL
> .. .. .. .. ..# elementType : chr "ANY" .. .. .. .. ..# metadata
> : list() .. .. .. .. ..# listData :List of 2 .. .. .. .. ..
> ..$ tx_id : int [1:191891] 93738 93739 93740 93736 93737 175481
> 175482 175480 175483 175484 ... .. .. .. .. .. ..$ tx_name: chr
> [1:191891] "ENST00000373020" "ENST00000496771" "ENST00000494424"
> "ENST00000373031" ... .. .. ..# elementType : chr "ANY" .. ..
> ..# metadata : list() ..# elementMetadata:Formal class
> 'DataFrame' [package "IRanges"] with 6 slots .. .. ..# rownames
> : NULL .. .. ..# nrows : int 57605 .. .. ..#
> elementMetadata: NULL .. .. ..# elementType : chr "ANY" .. ..
> ..# metadata : list() .. .. ..# listData : list() ..#
> elementType : chr "GRanges" ..# metadata : list()
The object tx_by_gene isn't a vector. You can check using the is.vector function
is.vector(counts1)
is.vector(tx_by_gene)
Of course, there could be method defined so that the two objects can be combined
Those vectors should not be too big for R. You probably used up a lot of memory before the cbind() operation. Look at what objects you currently have with ls() and delete those you don't need any more with rm().
Related
I am currently trying to test for collinearity amongst my climate raster layers using the 'vifcor' function in R. However I keep getting this error:
Error in m[, i] <- getValues(x#layers[[i]]) :
number of items to replace is not a multiple of replacement length
My full R code is as follows:
predictors.files <- list.files(path="/Users/josh/Desktop/Predictors/",pattern='asc$',full.names=TRUE)
preds.stack<-stack(predictors.files)
vif(preds.stack)
v1<-vifcor(preds.stack,th=0.7)
Then it goes wrong. Can anyone help me with this issue?
The output of str(preds.stack)
Formal class 'RasterStack'
[package "raster"] with 11 slots ..# filename: chr "" ..# layers :List of 19 .. ..$ :Formal class 'RasterLayer'
[package "raster"] with 12 slots .. .. .. ..# file :Formal class '.RasterFile'
[package "raster"] with 13 slots .. .. .. .. .. ..# name : chr "/Users/josh/Desktop/Predictors/isothermality.asc" .. .. .. .. .. ..# datanotation: chr "FLT4S" .. .. .. .. .. ..# byteorder : chr "little" .. .. .. .. .. ..# nodatavalue : num -Inf .. .. .. .. .. ..# NAchanged : logi FALSE
Thanks :)
I have a list vector containing S4 correlation templates from the monitoR::makeCorTemplate function.
temps_0 <- vector(mode = 'list',length=length(tru_files_info_0$species_id))
for (j in 1: length(tru_files_info_0$species_id)) {
temps_0[j] <- MonitoR::makeCorTemplate(paste0('tru_tp_files','/',paste0(tru_files_info_0$recording_id[j],'',
'.wav')), t.lim =c(tru_files_info_0$t_min[j], tru_files_info_0$t_max[j]),
frq.lim = c(tru_files_info_0$f_min[j]/1000, tru_files_info_0$f_max[j]/1000),
select = 'auto', dens =1, score.cutoff = 0.2, name = tru_files_info_0$new_name[j])
+ }```
Resulting object
Formal class 'corTemplateList' [package "monitoR"] with 1 slot
..# templates:List of 1
.. ..$ 00d442df7_0:Formal class 'corTemplate' [package "monitoR"] with 15 slots
.. .. .. ..# clip.path : chr "tru_tp_files/00d442df7.wav"
.. .. .. ..# samp.rate : int 48000
.. .. .. ..# pts : num [1:1924, 1:3] 1 1 1 1 1 1 1 1 1 1 ...
.. .. .. .. ..- attr(*, "dimnames")=List of 2
.. .. .. .. .. ..$ : NULL
.. .. .. .. .. ..$ : chr [1:3] "t" "frq" "amp"
.. .. .. ..# t.step : num 0.0107
.. .. .. ..# frq.step : num 0.0938
.. .. .. ..# n.t.bins : int 73
.. .. .. ..# first.t.bin : num 19.4
.. .. .. ..# n.frq.bins : int 25
.. .. .. ..# duration : num 0.779
.. .. .. ..# frq.lim : num [1:2] 5.91 8.25
.. .. .. ..# wl : int 512
.. .. .. ..# ovlp : int 0
.. .. .. ..# wn : chr "hanning"
.. .. .. ..# score.cutoff: num 0.2
.. .. .. ..# comment : chr ""
The next processing step is to combine these 10 templates via combineCorTemplates:
> ctemps_0 <- monitoR::combineCorTemplates(temps_0[[1]], temps_0[[2]], temps_0[[3]], temps_0[[4]], temps_0[[5]], temps_0[[6]], temps_0[[7]], temps_0[[8]], temps_0[[9]], temps_0[[10]])
> ctemps_0
Object of class "corTemplateList"
containing 10 templates
original.recording sample.rate lower.frequency
00d442df7_0 tru_tp_files/00d442df7.wav 48000 5.906
0ea8ea68a_0 tru_tp_files/0ea8ea68a.wav 48000 5.906
2e40b2294_0 tru_tp_files/2e40b2294.wav 48000 5.906
45c356538_0 tru_tp_files/45c356538.wav 48000 5.906
My question, how to extract the S4 from the list vector without writing out
each list element as combineCorTemplates(temps_0[[1]], temps_0[[2]], & etc
as this is error prone.
We could use do.call
c_temps_0 <- do.call(monitoR::combineCorTemplates, temps_0)
-testing
c_temps_1 <- combineCorTemplates(temps_0[[1]], temps_0[[2]],
temps_0[[3]], temps_0[[4]])
identical(c_temps_0, c_temps_1)
#[1] TRUE
NOTE: The reproducible example is created from ?combineCorTemplates
I have some WRF output data that was subsetted and masked using pythons xarray module.
I'm now performing calculations on raster bricks using R's raster package and finding very different speeds for very similar files.
Knowns:
There are 3 netCDF files, all the exact same size - 9.47 GB, that contain 9 variables
They all have the exact same dimensions (nrow 327, ncol 348, nlayer 365)
All calculations are on individual files (layer calculations)
All calculations are on the same variable with the same values (except for the second which is masked)
system.time(sum(d97[[1:365]]))
user system elapsed
5.428 2.771 8.840
The second file is the exact same file but a masked portion, with all the masked values converted to NaN.
system.time(sum(masked_d97[[1:365]]))
user system elapsed
10.784 2.157 13.052
The last file is a slightly modified version (daily values rather than cummulative values) of the first file. It was modified using Xarray in Python.
system.time(sum(mod_d97[[1:365]]))
user system elapsed
22.015 1.773 24.474
What on earth is happening here? I'm happy to provide more details (code, ncdumps, etc) as requested.
EDIT: added str() of files
d97 <- brick(files[8], varname = "TMIN")
masked_97 <- brick(files[3], varname = "TMIN")
d03 <- brick(files[11], varname = "TMIN")
str(d97)
Formal class 'RasterBrick' [package "raster"] with 12 slots
..# file :Formal class '.RasterFile' [package "raster"] with 13 slots
.. .. ..# name : chr "/Users/charlesbecker/Desktop/Data/Project Data/Shiny/WY1997_yearly_stats.nc"
.. .. ..# datanotation: chr "FLT4S"
.. .. ..# byteorder : chr "little"
.. .. ..# nodatavalue : num NaN
.. .. ..# NAchanged : logi FALSE
.. .. ..# nbands : int 365
.. .. ..# bandorder : chr "BIL"
.. .. ..# offset : int 0
.. .. ..# toptobottom : logi TRUE
.. .. ..# blockrows : int 0
.. .. ..# blockcols : int 0
.. .. ..# driver : chr "netcdf"
.. .. ..# open : logi FALSE
..# data :Formal class '.MultipleRasterData' [package "raster"] with 14 slots
.. .. ..# values : logi[0 , 0 ]
.. .. ..# offset : num 0
.. .. ..# gain : num 1
.. .. ..# inmemory : logi FALSE
.. .. ..# fromdisk : logi TRUE
.. .. ..# nlayers : int 365
.. .. ..# dropped : NULL
.. .. ..# isfactor : logi FALSE
.. .. ..# attributes: list()
.. .. ..# haveminmax: logi FALSE
.. .. ..# min : num [1:365] Inf Inf Inf Inf Inf ...
.. .. ..# max : num [1:365] -Inf -Inf -Inf -Inf -Inf ...
.. .. ..# unit : chr "K"
.. .. ..# names : chr [1:365] "X1" "X2" "X3" "X4" ...
..# legend :Formal class '.RasterLegend' [package "raster"] with 5 slots
.. .. ..# type : chr(0)
.. .. ..# values : logi(0)
.. .. ..# color : logi(0)
.. .. ..# names : logi(0)
.. .. ..# colortable: logi(0)
..# title : chr "TMIN"
..# extent :Formal class 'Extent' [package "raster"] with 4 slots
.. .. ..# xmin: num 0.5
.. .. ..# xmax: num 348
.. .. ..# ymin: num 0.5
.. .. ..# ymax: num 328
..# rotated : logi FALSE
..# rotation:Formal class '.Rotation' [package "raster"] with 2 slots
.. .. ..# geotrans: num(0)
.. .. ..# transfun:function ()
..# ncols : int 348
..# nrows : int 327
..# crs :Formal class 'CRS' [package "sp"] with 1 slot
.. .. ..# projargs: chr NA
..# history : list()
..# z :List of 1
.. ..$ : int [1:365] 1 2 3 4 5 6 7 8 9 10 ...
str(masked_d97)
Formal class 'RasterBrick' [package "raster"] with 12 slots
..# file :Formal class '.RasterFile' [package "raster"] with 13 slots
.. .. ..# name : chr "/Users/charlesbecker/Desktop/Data/Project Data/Shiny/AVA_WY1997_yearly_stats.nc"
.. .. ..# datanotation: chr "FLT4S"
.. .. ..# byteorder : chr "little"
.. .. ..# nodatavalue : num NaN
.. .. ..# NAchanged : logi FALSE
.. .. ..# nbands : int 365
.. .. ..# bandorder : chr "BIL"
.. .. ..# offset : int 0
.. .. ..# toptobottom : logi TRUE
.. .. ..# blockrows : int 0
.. .. ..# blockcols : int 0
.. .. ..# driver : chr "netcdf"
.. .. ..# open : logi FALSE
..# data :Formal class '.MultipleRasterData' [package "raster"] with 14 slots
.. .. ..# values : logi[0 , 0 ]
.. .. ..# offset : num 0
.. .. ..# gain : num 1
.. .. ..# inmemory : logi FALSE
.. .. ..# fromdisk : logi TRUE
.. .. ..# nlayers : int 365
.. .. ..# dropped : NULL
.. .. ..# isfactor : logi FALSE
.. .. ..# attributes: list()
.. .. ..# haveminmax: logi FALSE
.. .. ..# min : num [1:365] Inf Inf Inf Inf Inf ...
.. .. ..# max : num [1:365] -Inf -Inf -Inf -Inf -Inf ...
.. .. ..# unit : chr ""
.. .. ..# names : chr [1:365] "X1" "X2" "X3" "X4" ...
..# legend :Formal class '.RasterLegend' [package "raster"] with 5 slots
.. .. ..# type : chr(0)
.. .. ..# values : logi(0)
.. .. ..# color : logi(0)
.. .. ..# names : logi(0)
.. .. ..# colortable: logi(0)
..# title : chr "TMIN"
..# extent :Formal class 'Extent' [package "raster"] with 4 slots
.. .. ..# xmin: num 0.5
.. .. ..# xmax: num 348
.. .. ..# ymin: num 0.5
.. .. ..# ymax: num 328
..# rotated : logi FALSE
..# rotation:Formal class '.Rotation' [package "raster"] with 2 slots
.. .. ..# geotrans: num(0)
.. .. ..# transfun:function ()
..# ncols : int 348
..# nrows : int 327
..# crs :Formal class 'CRS' [package "sp"] with 1 slot
.. .. ..# projargs: chr NA
..# history : list()
..# z :List of 1
.. ..$ : int [1:365] 1 2 3 4 5 6 7 8 9 10 ...
str(d03)
Formal class 'RasterBrick' [package "raster"] with 12 slots
..# file :Formal class '.RasterFile' [package "raster"] with 13 slots
.. .. ..# name : chr "/Users/charlesbecker/Desktop/Data/Project Data/Shiny/WY2003_yearly_stats.nc"
.. .. ..# datanotation: chr "FLT4S"
.. .. ..# byteorder : chr "little"
.. .. ..# nodatavalue : num NaN
.. .. ..# NAchanged : logi FALSE
.. .. ..# nbands : int 365
.. .. ..# bandorder : chr "BIL"
.. .. ..# offset : int 0
.. .. ..# toptobottom : logi TRUE
.. .. ..# blockrows : int 0
.. .. ..# blockcols : int 0
.. .. ..# driver : chr "netcdf"
.. .. ..# open : logi FALSE
..# data :Formal class '.MultipleRasterData' [package "raster"] with 14 slots
.. .. ..# values : logi[0 , 0 ]
.. .. ..# offset : num 0
.. .. ..# gain : num 1
.. .. ..# inmemory : logi FALSE
.. .. ..# fromdisk : logi TRUE
.. .. ..# nlayers : int 365
.. .. ..# dropped : NULL
.. .. ..# isfactor : logi FALSE
.. .. ..# attributes: list()
.. .. ..# haveminmax: logi FALSE
.. .. ..# min : num [1:365] Inf Inf Inf Inf Inf ...
.. .. ..# max : num [1:365] -Inf -Inf -Inf -Inf -Inf ...
.. .. ..# unit : chr "K"
.. .. ..# names : chr [1:365] "X1" "X2" "X3" "X4" ...
..# legend :Formal class '.RasterLegend' [package "raster"] with 5 slots
.. .. ..# type : chr(0)
.. .. ..# values : logi(0)
.. .. ..# color : logi(0)
.. .. ..# names : logi(0)
.. .. ..# colortable: logi(0)
..# title : chr "TMIN"
..# extent :Formal class 'Extent' [package "raster"] with 4 slots
.. .. ..# xmin: num 0.5
.. .. ..# xmax: num 348
.. .. ..# ymin: num 0.5
.. .. ..# ymax: num 328
..# rotated : logi FALSE
..# rotation:Formal class '.Rotation' [package "raster"] with 2 slots
.. .. ..# geotrans: num(0)
.. .. ..# transfun:function ()
..# ncols : int 348
..# nrows : int 327
..# crs :Formal class 'CRS' [package "sp"] with 1 slot
.. .. ..# projargs: chr NA
..# history : list()
..# z :List of 1
.. ..$ : int [1:365] 1 2 3 4 5 6 7 8 9 10 ...
system.time(sum(d97[[1:365]]))
user system elapsed
5.569 2.219 8.048
system.time(sum(masked_97[[1:365]]))
user system elapsed
11.887 2.342 14.569
system.time(sum(d03[[1:365]]))
user system elapsed
22.253 1.772 24.879
The most likely difference is that data in your new netCDF file is now compressed differently. Two forms of compression are common with netCDF files:
scale/offset encoding, e.g., to decode from int16 via a formula like scale_factor * values + add_offset.
zlib compression on individual chunks of the array (only supported with netCDF4 files).
If you don't slice or manipulate your variables, xarray will preserve compression setting via the encoding attribute, but this is generally dropped by xarray operations. See the xarray docs on reading/writing encoded data for more details.
I am generating a chlorophyll map for lake. I want to fill the lake with blue colour where there is a very low chlorophyll concentration and light blue for NA values. I am using a code as given below
gplot(Chlorophyll_map_5) + geom_tile(aes(fill=value)) + scale_fill_gradient(low = 'blue', high = 'red', na.value='blue',name="Chl-a (ug/l)",limits=c(0,1000)) + coord_equal()+theme_bw()
Which gives me a plot like this for na.value='blue':
na.value='blue'
When I use na.value='transparent' I got this image:
na.value='transparent'
If I change the colour of the na.value it also changes the background. Is there a way to fill the lake with colour without changing the background?
The output of my data:`The output of my data:
Formal class 'RasterLayer' [package "raster"] with 12 slots
..# file :Formal class '.RasterFile' [package "raster"] with 13 slots
.. .. ..# name : chr "/private/var/folders/68/hm_5ts9x7psb6j3wnb91_bfr0000gn/T/RtmpZ3BLZD/raster/r_tmp_2017-07-18_133827_28365_34843.grd"
.. .. ..# datanotation: chr "FLT8S"
.. .. ..# byteorder : Named chr "little"
.. .. .. ..- attr(*, "names")= chr "value"
.. .. ..# nodatavalue : num -1.7e+308
.. .. ..# NAchanged : logi FALSE
.. .. ..# nbands : int 1
.. .. ..# bandorder : Named chr "BIL"
.. .. .. ..- attr(*, "names")= chr "value"
.. .. ..# offset : int 0
.. .. ..# toptobottom : logi TRUE
.. .. ..# blockrows : int 0
.. .. ..# blockcols : int 0
.. .. ..# driver : chr "raster"
.. .. ..# open : logi FALSE
..# data :Formal class '.SingleLayerData' [package "raster"] with 13 slots
.. .. ..# values : logi(0)
.. .. ..# offset : num 0
.. .. ..# gain : num 1
.. .. ..# inmemory : logi FALSE
.. .. ..# fromdisk : logi TRUE
.. .. ..# isfactor : logi FALSE
.. .. ..# attributes: list()
.. .. ..# haveminmax: logi TRUE
.. .. ..# min : num 0.00335
.. .. ..# max : num 3870657
.. .. ..# band : int 1
.. .. ..# unit : chr ""
.. .. ..# names : chr "layer"
..# legend :Formal class '.RasterLegend' [package "raster"] with 5 slots
.. .. ..# type : chr(0)
.. .. ..# values : logi(0)
.. .. ..# color : logi(0)
.. .. ..# names : logi(0)
.. .. ..# colortable: logi(0)
..# title : chr(0)
..# extent :Formal class 'Extent' [package "raster"] with 4 slots
.. .. ..# xmin: num 35.8
.. .. ..# xmax: num 36.7
.. .. ..# ymin: num 2.4
.. .. ..# ymax: num 4.65
..# rotated : logi FALSE
..# rotation:Formal class '.Rotation' [package "raster"] with 2 slots
.. .. ..# geotrans: num(0)
.. .. ..# transfun:function ()
..# ncols : int 3240
..# nrows : int 8321
..# crs :Formal class 'CRS' [package "sp"] with 1 slot
.. .. ..# projargs: chr "+proj=longlat +ellps=WGS84 +no_defs"
..# history : list()
..# z : list()
x <- trim(Chlorophyll_map_5)
ggplot(Chlorophyll_map_5) +
geom_tile(aes(fill=value)) +
scale_fill_gradient(low = 'blue', high = 'red', na.value='blue',name="Chl-a (ug/l)",limits=c(0,1000)) +
coord_equal()+theme_bw()
Per documentation, the trim function "crops a RasterLayer by removing the outer rows and columns that
only contain NA values"
Although I understand OOP, I've only just encountered them in R
I am using a package from Bioconductor to churn through some genomic data.
The object it creates is called readCounts and typing this into the command gives the following.
QDNAseqReadCounts (storageMode: lockedEnvironment)
assayData: 206391 features, 1 samples
element names: counts
protocolData: none
phenoData
sampleNames: SLX-10457.FastSeqA.BloodDMets_11AF_-AHMMH.s_1.r_1.fq.gz
varLabels: name total.reads used.reads expected.variance
varMetadata: labelDescription
featureData
featureNames: 1:825001-840000 1:840001-855000 ... 22:51165001-51180000 (168063 total)
fvarLabels: chromosome start ... use (9 total)
fvarMetadata: labelDescription
experimentData: use 'experimentData(object)'
Annotation:
I am trying to plot readcounts on a simple xy graph as follows:
plot(readCounts, logTransform=TRUE, ylim=c(-1000, binSize * 15))
However when I do so I get the following error:
Error in sort.int(x, partial = unique(c(lo, hi))) :
index 180 outside bounds
with the traceback() showing:
6: sort.int(x, partial = unique(c(lo, hi)))
5: FUN(newX[, i], ...)
4: apply(copynumber, 2, sdFUN, na.rm = TRUE)
3: .local(x, y, ...)
2: plot(readCounts, logTransform = TRUE, ylim = c(-1000, binSize *
15))
1: plot(readCounts, logTransform = TRUE, ylim = c(-1000, binSize *
15))
so having googled I thought it might be a missing values problem so I tried na.omit(readCounts) but got the same error again but this time setting the out of bounds index as being 207.
I have tried to inspect the data but I can't find anything wrong at row 207 although I'm not really sure which slot this refers to. I really don't know how to debug this. I'm happy to give more info regarding what I'm trying to do but I don't really know how to determine what the problem is with this error in a R object.
When I do str(readCounts) I get:
Formal class 'QDNAseqReadCounts' [package "QDNAseq"] with 7 slots
..# assayData :<environment: 0x13a99ed90>
..# phenoData :Formal class 'AnnotatedDataFrame' [package "Biobase"] with 4 slots
.. .. ..# varMetadata :'data.frame': 4 obs. of 1 variable:
.. .. .. ..$ labelDescription: chr [1:4] NA NA NA NA
.. .. ..# data :'data.frame': 1 obs. of 4 variables:
.. .. .. ..$ name : chr "SLX-10457.FastSeqA.BloodDMets_11AF_-AHMMH.s_1.r_1.fq.gz"
.. .. .. ..$ total.reads : num 0
.. .. .. ..$ used.reads : num 0
.. .. .. ..$ expected.variance: num Inf
.. .. ..# dimLabels : chr [1:2] "sampleNames" "sampleColumns"
.. .. ..# .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slot
.. .. .. .. ..# .Data:List of 1
.. .. .. .. .. ..$ : int [1:3] 1 1 0
..# featureData :Formal class 'AnnotatedDataFrame' [package "Biobase"] with 4 slots
.. .. ..# varMetadata :'data.frame': 9 obs. of 1 variable:
.. .. .. ..$ labelDescription: chr [1:9] "Chromosome name" "Base pair start position" "Base pair end position" "Percentage of non-N nucleotides (of full bin size)" ...
.. .. ..# data :'data.frame': 168063 obs. of 9 variables:
.. .. .. ..$ chromosome : chr [1:168063] "1" "1" "1" "1" ...
.. .. .. ..$ start : num [1:168063] 825001 840001 855001 870001 885001 ...
.. .. .. ..$ end : num [1:168063] 840000 855000 870000 885000 900000 915000 930000 945000 960000 975000 ...
.. .. .. ..$ bases : num [1:168063] 100 100 100 100 100 100 100 100 100 100 ...
.. .. .. ..$ gc : num [1:168063] 48 61.8 65.1 65.5 62.6 ...
.. .. .. ..$ mappability: num [1:168063] 58.6 91.5 94.1 93.2 93.9 ...
.. .. .. ..$ blacklist : num [1:168063] 0.727 0 0 0 0 ...
.. .. .. ..$ residual : num [1:168063] -0.0627 0.05036 0.09384 0.00541 -0.00588 ...
.. .. .. ..$ use : logi [1:168063] TRUE TRUE TRUE TRUE TRUE TRUE ...
.. .. .. ..- attr(*, "na.action")=Class 'omit' Named int [1:38328] 1 2 3 4 5 6 7 8 9 10 ...
.. .. .. .. .. ..- attr(*, "names")= chr [1:38328] "1:1-15000" "1:15001-30000" "1:30001-45000" "1:45001-60000" ...
.. .. ..# dimLabels : chr [1:2] "featureNames" "featureColumns"
.. .. ..# .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slot
.. .. .. .. ..# .Data:List of 1
.. .. .. .. .. ..$ : int [1:3] 1 1 0
..# experimentData :Formal class 'MIAME' [package "Biobase"] with 13 slots
.. .. ..# name : chr ""
.. .. ..# lab : chr ""
.. .. ..# contact : chr ""
.. .. ..# title : chr ""
.. .. ..# abstract : chr ""
.. .. ..# url : chr ""
.. .. ..# pubMedIds : chr ""
.. .. ..# samples : list()
.. .. ..# hybridizations : list()
.. .. ..# normControls : list()
.. .. ..# preprocessing : list()
.. .. ..# other : list()
.. .. ..# .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slot
.. .. .. .. ..# .Data:List of 2
.. .. .. .. .. ..$ : int [1:3] 1 0 0
.. .. .. .. .. ..$ : int [1:3] 1 1 0
..# annotation : chr(0)
..# protocolData :Formal class 'AnnotatedDataFrame' [package "Biobase"] with 4 slots
.. .. ..# varMetadata :'data.frame': 0 obs. of 1 variable:
.. .. .. ..$ labelDescription: chr(0)
.. .. ..# data :'data.frame': 1 obs. of 0 variables
.. .. ..# dimLabels : chr [1:2] "sampleNames" "sampleColumns"
.. .. ..# .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slot
.. .. .. .. ..# .Data:List of 1
.. .. .. .. .. ..$ : int [1:3] 1 1 0
..# .__classVersion__:Formal class 'Versions' [package "Biobase"] with 1 slot
.. .. ..# .Data:List of 4
.. .. .. ..$ : int [1:3] 3 1 2
.. .. .. ..$ : int [1:3] 2 26 0
.. .. .. ..$ : int [1:3] 1 3 0
.. .. .. ..$ : int [1:3] 1 2 4