── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ── ✔ ggplot2 3.3.2 ✔ purrr 0.3.4 ✔ tibble 3.0.4 ✔ dplyr 1.0.2 ✔ tidyr 1.1.2 ✔ stringr 1.4.0 ✔ readr 1.4.0 ✔ forcats 0.5.0 ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ── ✖ dplyr::filter() masks stats::filter() ✖ dplyr::lag() masks stats::lag() Loading required package: S4Vectors Loading required package: stats4 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 objects are masked from ‘package:dplyr’: combine, intersect, setdiff, union 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:dplyr’: first, rename The following object is masked from ‘package:tidyr’: expand The following object is masked from ‘package:base’: expand.grid Loading required package: IRanges Attaching package: ‘IRanges’ The following objects are masked from ‘package:dplyr’: collapse, desc, slice The following object is masked from ‘package:purrr’: reduce Loading required package: GenomicRanges Loading required package: GenomeInfoDb Loading required package: SummarizedExperiment Loading required package: MatrixGenerics Loading required package: matrixStats Attaching package: ‘matrixStats’ The following object is masked from ‘package:dplyr’: count 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 converting counts to integer mode seqname source feature start end score strand frame 1 ##gff-version 3 NA NA 2 1 FIG CDS 1 1368 . + 1 3 1 FIG CDS 1379 2479 . + 2 4 1 FIG CDS 2485 3567 . + 1 5 1 FIG CDS 3631 4776 . - 1 6 1 FIG CDS 4813 5616 . - 1 att 1 2 ID=fig|729.2200.peg.1;Name=Chromosomal replication initiator protein DnaA 3 ID=fig|729.2200.peg.2;Name=DNA polymerase III beta subunit (EC 2.7.7.7);Ontology_term=KEGG_ENZYME:2.7.7.7 4 ID=fig|729.2200.peg.3;Name=DNA recombination and repair protein RecF 5 ID=fig|729.2200.peg.4;Name=N-acetylglucosamine-6-phosphate deacetylase (EC 3.5.1.25);Ontology_term=KEGG_ENZYME:3.5.1.25 6 ID=fig|729.2200.peg.5;Name=Glucosamine-6-phosphate deaminase (EC 3.5.99.6);Ontology_term=KEGG_ENZYME:3.5.99.6 seqname source feature start end score strand frame 1 1 FIG CDS 138 1231 . + 1 2 1 FIG CDS 1489 2369 . + 2 3 1 FIG CDS 2593 3459 . + 1 4 1 FIG CDS 3746 4662 . - 1 5 1 FIG CDS 4893 5536 . - 1 6 1 FIG CDS 5795 6497 . - 1 att 1 ID=fig|729.2200.peg.1;Name=Chromosomal replication initiator protein DnaA 2 ID=fig|729.2200.peg.2;Name=DNA polymerase III beta subunit (EC 2.7.7.7);Ontology_term=KEGG_ENZYME:2.7.7.7 3 ID=fig|729.2200.peg.3;Name=DNA recombination and repair protein RecF 4 ID=fig|729.2200.peg.4;Name=N-acetylglucosamine-6-phosphate deacetylase (EC 3.5.1.25);Ontology_term=KEGG_ENZYME:3.5.1.25 5 ID=fig|729.2200.peg.5;Name=Glucosamine-6-phosphate deaminase (EC 3.5.99.6);Ontology_term=KEGG_ENZYME:3.5.99.6 6 ID=fig|729.2200.peg.6;Name=N-acetylneuraminate lyase (EC 4.1.3.3);Ontology_term=KEGG_ENZYME:4.1.3.3 [1] "Generating pseudo-datasets" [1] 1 Joining, by = "Pos" [1] 2 Joining, by = "Pos" [1] 3 Joining, by = "Pos" [1] 4 Joining, by = "Pos" [1] 5 Joining, by = "Pos" [1] 6 Joining, by = "Pos" [1] 7 Joining, by = "Pos" [1] 8 Joining, by = "Pos" [1] 9 Joining, by = "Pos" [1] 10 Joining, by = "Pos" [1] "Binning read counts by gene boundaries" converting counts to integer mode Warning message: In DESeqDataSet(se, design = design, ignoreRank) : some variables in design formula are characters, converting to factors gene-wise dispersion estimates mean-dispersion relationship final dispersion estimates log2 fold change (MLE): condition EL1 vs Expected Wald test p-value: condition EL1 vs Expected DataFrame with 6 rows and 6 columns baseMean log2FoldChange lfcSE stat pvalue padj 2 0.865673 -2.67728 4.02911 -0.664485 0.506380073 0.9273558 3 0.865673 -2.67728 4.02911 -0.664485 0.506380073 0.9273558 4 1269.290835 -3.31635 1.56247 -2.122504 0.033795442 0.5165875 5 613.357293 -7.70283 2.08070 -3.702038 0.000213874 0.0237418 6 3482.843432 -3.17201 1.02943 -3.081328 0.002060798 0.0874150 7 2778.487001 -0.28657 1.63237 -0.175554 0.860644051 0.9904923 Package 'mclust' version 5.4.6 Type 'citation("mclust")' for citing this R package in publications. Attaching package: ‘mclust’ The following object is masked from ‘package:purrr’: map ---------------------------------------------------- Gaussian finite mixture model fitted by EM algorithm ---------------------------------------------------- Mclust V (univariate, unequal variance) model with 2 components: log-likelihood n df BIC ICL -4246.629 2033 5 -8531.343 -8896.436 Clustering table: 1 2 131 1902 Mixing probabilities: 1 2 0.129432 0.870568 Means: 1 2 -2.6039501 -0.8169696 Variances: 1 2 18.334311 2.274174 ------------------------------------------------------- Density estimation via Gaussian finite mixture modeling ------------------------------------------------------- Mclust V (univariate, unequal variance) model with 2 components: log-likelihood n df BIC ICL -4246.637 2033 5 -8531.36 -8897.33 null device 1 [1] "Unchanged" "Unchanged" "Unchanged" "Reduced" "Unchanged" "Unchanged" [7] "Unchanged" "Unchanged" "Unchanged" "Unchanged" converting counts to integer mode Warning message: In DESeqDataSet(se, design = design, ignoreRank) : some variables in design formula are characters, converting to factors gene-wise dispersion estimates mean-dispersion relationship final dispersion estimates log2 fold change (MAP): condition EL1 vs Expected Wald test p-value: condition EL1 vs Expected DataFrame with 6 rows and 6 columns baseMean log2FoldChange lfcSE stat pvalue padj 2 0.865673 -2.269771 0.867136 -2.617548 0.00885639 0.0468881 3 0.865673 -2.269771 0.867136 -2.617548 0.00885639 0.0468881 4 1269.290835 -1.843968 1.037373 -1.777537 0.07547995 0.3150939 5 613.357293 -1.718232 1.081208 -1.589179 0.11202005 0.4171003 6 3482.843432 -2.581940 0.804124 -3.210874 0.00132332 0.0468881 7 2778.487001 -0.163305 1.068363 -0.152855 0.87851271 0.9870420 ---------------------------------------------------- Gaussian finite mixture model fitted by EM algorithm ---------------------------------------------------- Mclust X (univariate normal) model with 1 component: log-likelihood n df BIC ICL -3263.661 2033 2 -6542.556 -6542.556 Clustering table: 1 2033 Mixing probabilities: 1 1 Means: [1] -0.578041 Variances: [1] 1.451804 ------------------------------------------------------- Density estimation via Gaussian finite mixture modeling ------------------------------------------------------- Mclust X (univariate normal) model with 1 component: log-likelihood n df BIC ICL -3263.661 2033 2 -6542.556 -6542.556 null device 1 [1] "Reduced" "Reduced" "Reduced" "Reduced" "Reduced" "Reduced" [7] "Reduced" "Reduced" "Reduced" "Unchanged"