I get the following error message when trying to plot my statslist obtained by seeFastq:
Error: Unknown parameters: binwidth, bins, origin, right
I followed the manual pages for seeFastq() and seeFastqPlot() and this is the code I used to get the stats plot:
> fqlist <- seeFastq(fastq=infile1(args), batchsize=10000, klength=8)
> pdf("results/fastqReport.pdf", height=18, width=4*length(fqlist))
> seeFastqPlot(fqlist)
The fqlist object seems to be fine (see output of str(fqlist) at end of post).
I guess this is a problem that has to do with the geom_histogram function in ggplot2, as googling revealed the same error for another package that uses this function (see https://github.com/hadley/ggplot2/issues/1465). I am not sure, though. Hope you can help.
Thank you,
Sabrina
Below is some more info on the versions I am using (including output of systemInfo() and traceback()).
I am using ggplot2 version 2.0.0, R version 3.2.3
Output of systemInfo()
R version 3.2.3 (2015-12-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C LC_TIME=English_United States.1252
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] systemPipeR_1.4.7 RSQLite_1.0.0 DBI_0.3.1 ShortRead_1.28.0 GenomicAlignments_1.6.3
[6] SummarizedExperiment_1.0.2 Biobase_2.30.0 BiocParallel_1.4.3 Rsamtools_1.22.0 Biostrings_2.38.3
[11] XVector_0.10.0 GenomicRanges_1.22.3 GenomeInfoDb_1.6.1 IRanges_2.4.6 S4Vectors_0.8.7
[16] BiocGenerics_0.16.1
loaded via a namespace (and not attached):
[1] genefilter_1.52.0 splines_3.2.3 lattice_0.20-33 colorspace_1.2-6 rtracklayer_1.30.1
[6] Category_2.36.0 GenomicFeatures_1.22.8 base64enc_0.1-3 XML_3.98-1.3 RBGL_1.46.0
[11] survival_2.38-3 GOstats_2.36.0 RColorBrewer_1.1-2 lambda.r_1.1.7 plyr_1.8.3
[16] stringr_1.0.0 zlibbioc_1.16.0 munsell_0.4.2 gtable_0.1.2 futile.logger_1.4.1
[21] hwriter_1.3.2 latticeExtra_0.6-26 biomaRt_2.26.1 AnnotationDbi_1.32.3 GSEABase_1.32.0
[26] Rcpp_0.12.3 xtable_1.8-0 edgeR_3.12.0 scales_0.3.0 checkmate_1.7.0
[31] limma_3.26.5 graph_1.48.0 annotate_1.48.0 sendmailR_1.2-1 brew_1.0-6
[36] BatchJobs_1.6 rjson_0.2.15 ggplot2_2.0.0 fail_1.3 digest_0.6.9
[41] stringi_1.0-1 BBmisc_1.9 grid_3.2.3 tools_3.2.3 bitops_1.0-6
[46] magrittr_1.5 RCurl_1.95-4.7 futile.options_1.0.0 GO.db_3.2.2 pheatmap_1.0.8
[51] Matrix_1.2-3 AnnotationForge_1.12.2
Output from traceback()
8: stop("Unknown parameters: ", paste(extra, collapse = ", "), call. = FALSE)
7: layer(data = data, mapping = mapping, stat = stat, geom = GeomBar,
position = position, show.legend = show.legend, inherit.aes = inherit.aes,
params = list(binwidth = binwidth, bins = bins, origin = origin,
right = right, na.rm = na.rm, ...))
6: geom_histogram(fill = "#0072B2", stat = "identity")
5: fastqPlot(x = fqlist[z])
4: FUN(X[[i]], ...)
3: lapply(names(fqlist), function(z) fastqPlot(x = fqlist[z]))
2: lapply(names(fqlist), function(z) fastqPlot(x = fqlist[z]))
1: seeFastqPlot(fqlist)
Output from str(fqlist):
List of 1
$ A_bac:List of 9
..$ fqstats: Named num [1:3] 10000 1560521 8
.. ..- attr(*, "names")= chr [1:3] "batchsize" "nReads" "klength"
..$ astats :'data.frame': 125 obs. of 6 variables:
.. ..$ Cycle: Ord.factor w/ 125 levels "1"<"2"<"3"<"4"<..: 1 2 3 4 5 6 7 8 9 10 ...
.. ..$ min : num [1:125] 2 27 33 33 33 37 37 37 37 37 ...
.. ..$ low : num [1:125] 14 27 33 33 33 37 37 37 37 37 ...
.. ..$ mid : num [1:125] 33 33 33 33 33 37 37 37 37 37 ...
.. ..$ top : num [1:125] 33 33 33 33 33 37 37 37 37 37 ...
.. ..$ max : num [1:125] 33 33 33 33 33 37 37 37 37 37 ...
..$ bstats :'data.frame': 500 obs. of 3 variables:
.. ..$ Base : Factor w/ 4 levels "A","C","G","T": 1 2 3 4 1 2 3 4 1 2 ...
.. ..$ Frequency: num [1:500] 0.346 0.287 0.167 0.2 0.297 ...
.. ..$ Cycle : Ord.factor w/ 125 levels "1"<"2"<"3"<"4"<..: 1 1 1 1 2 2 2 2 3 3 ...
..$ cstats :'data.frame': 500 obs. of 3 variables:
.. ..$ Quality: num [1:500] 25.8 27.7 30.2 32.2 31.9 ...
.. ..$ Base : Factor w/ 4 levels "A","C","G","T": 1 1 1 1 1 1 1 1 1 1 ...
.. ..$ Cycle : Ord.factor w/ 125 levels "1"<"2"<"3"<"4"<..: 1 2 3 4 5 6 7 8 9 10 ...
..$ dstats :'data.frame': 125 obs. of 3 variables:
.. ..$ RelDiv: num [1:125] NA NA NA NA NA ...
.. ..$ Method: num [1:125] 1 1 1 1 1 1 1 1 1 1 ...
.. ..$ Cycle : Ord.factor w/ 125 levels "1"<"2"<"3"<"4"<..: 1 2 3 4 5 6 7 8 9 10 ...
..$ estats :'data.frame': 25 obs. of 3 variables:
.. ..$ minQuality: Ord.factor w/ 5 levels ">0"<">10"<">20"<..: 1 2 3 4 5 1 2 3 4 5 ...
.. ..$ Percent : num [1:25] 100 82.6 32.5 14.7 0 ...
.. ..$ Outliers : Ord.factor w/ 5 levels "0"<"1"<"2"<"3"<..: 1 1 1 1 1 2 2 2 2 2 ...
..$ fstats :'data.frame': 38 obs. of 2 variables:
.. ..$ Quality: Ord.factor w/ 38 levels "0"<"1"<"2"<"3"<..: 1 2 3 4 5 6 7 8 9 10 ...
.. ..$ Percent: num [1:38(1d)] 0 0 0.01 0 0 0.02 0.03 0.01 0.01 0.07 ...
.. .. ..- attr(*, "dimnames")=List of 1
.. .. .. ..$ : chr [1:38] "0" "1" "2" "3" ...
..$ gstats :'data.frame': 125 obs. of 2 variables:
.. ..$ Cycle : Ord.factor w/ 125 levels "1"<"2"<"3"<"4"<..: 1 2 3 4 5 6 7 8 9 10 ...
.. ..$ Percent: num [1:125] 0 0 0 0 0 0 0 0 0 0 ...
..$ hstats :'data.frame': 2 obs. of 2 variables:
.. ..$ nOccurrences: Ord.factor w/ 2 levels "1"<"2": 1 2
.. ..$ Percent : num [1:2] 1e+02 2e-02
