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SGDDNB / translational_regulation

Detection of differential translated genes using Ribo-seq
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Error after installing apeglm #8

Open mehdiamiri123 opened 1 year ago

mehdiamiri123 commented 1 year ago

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 commented 1 year ago

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

NLRP8ENST00000291971 0 0 0 MT1BENST00000334346 0 0 0 RASSF10ENST00000529419 0 0 0 MROENST00000610511 0 1 2 FKBP1CENST00000370659 0 0 1 FKBP6ENST00000252037 0 0 0 Ribo_cond1_count3 Ribo_cond2_count3 X NLRP8ENST00000291971 0 0 0 MT1BENST00000334346 0 0 0 RASSF10ENST00000529419 0 0 0 MROENST00000610511 0 0 1 FKBP1CENST00000370659 0 0 0 FKBP6ENST00000252037 0 0 0 mRNA_cond2_count1 mRNA_cond1_count2 mRNA_cond2_count2 NLRP8ENST00000291971 0 0 0 MT1BENST00000334346 0 0 0 RASSF10ENST00000529419 1 0 0 MROENST00000610511 1 0 1 FKBP1CENST00000370659 0 0 0 FKBP6ENST00000252037 0 0 0 mRNA_cond1_count3 mRNA_cond2_count3 X NLRP8ENST00000291971 0 0 0 MT1BENST00000334346 0 0 0 RASSF10ENST00000529419 0 0 0 MROENST00000610511 3 0 3 FKBP1CENST00000370659 1 0 0 FKBP6ENST00000252037 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 commented 1 year ago

Here is the figures. Result_figures.pdf