Error after installing apeglm

[mehdiamiri123]

Hi there,

I installed the apeglm and run deltaTE on your sample data, but it only prints the deltaTE fold changes with list of deltaTE genes in text files, and it gives this error at the end.

Error in lfcShrink(ddsMat_ribo, contrast = c("Condition", "2", "1"), res = res_ribo) :
type='apeglm' shrinkage only for use with 'coef'
Execution halted

Could you tell me how to solve this issue?

Thanks,

Mehdi

[mehdiamiri123]

I managed to get this error fixed by looking at the closed issue, but I also got the same error.

Rscript DTEG.R riboseq_counts.txt rnaseq_count.txt sample_info.txt 1
Loading required package: S4Vectors
Loading required package: stats4
Loading required package: BiocGenerics

Attaching package: ‘BiocGenerics’

The following objects are masked from ‘package:stats’:

IQR, mad, sd, var, xtabs

The following objects are masked from ‘package:base’:

anyDuplicated, append, as.data.frame, basename, cbind, colnames,
dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
union, unique, unsplit, which.max, which.min

Attaching package: ‘S4Vectors’

The following objects are masked from ‘package:base’:

expand.grid, I, unname

Loading required package: IRanges
Loading required package: GenomicRanges
Loading required package: GenomeInfoDb
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats

Attaching package: ‘MatrixGenerics’

The following objects are masked from ‘package:matrixStats’:

colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
colWeightedMeans, colWeightedMedians, colWeightedSds,
colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
rowWeightedSds, rowWeightedVars

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")'.

Attaching package: ‘Biobase’

The following object is masked from ‘package:MatrixGenerics’:

rowMedians

The following objects are masked from ‘package:matrixStats’:

anyMissing, rowMedians

                      Ribo_cond2_count1 Ribo_cond1_count2 Ribo_cond2_count2

NLRP8___ENST00000291971 0 0 0
MT1B___ENST00000334346 0 0 0
RASSF10___ENST00000529419 0 0 0
MRO___ENST00000610511 0 1 2
FKBP1C___ENST00000370659 0 0 1
FKBP6___ENST00000252037 0 0 0
Ribo_cond1_count3 Ribo_cond2_count3 X
NLRP8___ENST00000291971 0 0 0
MT1B___ENST00000334346 0 0 0
RASSF10___ENST00000529419 0 0 0
MRO___ENST00000610511 0 0 1
FKBP1C___ENST00000370659 0 0 0
FKBP6___ENST00000252037 0 0 0
mRNA_cond2_count1 mRNA_cond1_count2 mRNA_cond2_count2
NLRP8___ENST00000291971 0 0 0
MT1B___ENST00000334346 0 0 0
RASSF10___ENST00000529419 1 0 0
MRO___ENST00000610511 1 0 1
FKBP1C___ENST00000370659 0 0 0
FKBP6___ENST00000252037 0 0 0
mRNA_cond1_count3 mRNA_cond2_count3 X
NLRP8___ENST00000291971 0 0 0
MT1B___ENST00000334346 0 0 0
RASSF10___ENST00000529419 0 0 0
MRO___ENST00000610511 3 0 3
FKBP1C___ENST00000370659 1 0 0
FKBP6___ENST00000252037 0 0 0
SampleID Condition SeqType Batch
1 Ribo_cond1_count1 1 RIBO 1
2 Ribo_cond2_count1 2 RIBO 1
3 Ribo_cond1_count2 1 RIBO 2
4 Ribo_cond2_count2 2 RIBO 2
5 Ribo_cond1_count3 1 RIBO 3
6 Ribo_cond2_count3 2 RIBO 3
Warning message:
In DESeqDataSet(se, design = design, ignoreRank) :
some variables in design formula are characters, converting to factors
estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
fitting model and testing
[1] "Intercept" "Batch_2_vs_1" "Batch_3_vs_1"
[4] "Condition_2_vs_1" "SeqType_RIBO_vs_RNA" "Condition2.SeqTypeRIBO"
mkdir: Results: File exists
mkdir: fold_changes: File exists
mkdir: gene_lists: File exists

out of 16443 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up) : 594, 3.6%
LFC < 0 (down) : 995, 6.1%
outliers [1] : 0, 0%
low counts [2] : 5351, 33%
(mean count < 20)
[1] see 'cooksCutoff' argument of ?results
[2] see 'independentFiltering' argument of ?results

[1] 964
Warning message:
In DESeqDataSet(se, design = design, ignoreRank) :
some variables in design formula are characters, converting to factors
estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
fitting model and testing
[1] "Intercept" "Batch_2_vs_1" "Batch_3_vs_1" "Condition_2_vs_1"
using 'apeglm' for LFC shrinkage. If used in published research, please cite:
Zhu, A., Ibrahim, J.G., Love, M.I. (2018) Heavy-tailed prior distributions for
sequence count data: removing the noise and preserving large differences.
Bioinformatics. https://doi.org/10.1093/bioinformatics/bty895
Warning message:
In DESeqDataSet(se, design = design, ignoreRank) :
some variables in design formula are characters, converting to factors
estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
fitting model and testing
[1] "Intercept" "Batch_2_vs_1" "Batch_3_vs_1" "Condition_2_vs_1"
using 'apeglm' for LFC shrinkage. If used in published research, please cite:
Zhu, A., Ibrahim, J.G., Love, M.I. (2018) Heavy-tailed prior distributions for
sequence count data: removing the noise and preserving large differences.
Bioinformatics. https://doi.org/10.1093/bioinformatics/bty895
Error in plot.window(...) : need finite 'ylim' values
Calls: plot -> plot -> plot.default -> localWindow -> plot.window
Execution halted

[mehdiamiri123]

Here is the figures.
Result_figures.pdf