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某个 DESeq2 版本可分析无重复但极为严格

某个 DESeq2 版本可分析无重复但极为严格

作者: 生信石头 | 来源:发表于2022-01-06 10:43 被阅读0次

    分析结果

    [1] "OE11_24h" "OE11_3h"
    converting counts to integer mode
    estimating size factors
    estimating dispersions
    gene-wise dispersion estimates
    mean-dispersion relationship
    final dispersion estimates
    fitting model and testing
    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.
    bioRxiv. https://doi.org/10.1101/303255

    out of 21015 with nonzero total read count
    adjusted p-value < 0.1
    LFC > 0 (up) : 0, 0%
    LFC < 0 (down) : 0, 0%
    outliers [1] : 0, 0%
    low counts [2] : 0, 0%
    (mean count < 5)
    [1] see 'cooksCutoff' argument of ?results
    [2] see 'independentFiltering' argument of ?results
    [1] 0

    工作台信息

    R version 3.5.1 (2018-07-02)
    Platform: x86_64-conda_cos6-linux-gnu (64-bit)
    Running under: CentOS Linux 7 (Core)

    Matrix products: default
    BLAS/LAPACK: /home/chengjie_chen/anaconda3/envs/DiffExp/lib/R/lib/libRblas.so

    locale:
    [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
    [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
    [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
    [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
    [9] LC_ADDRESS=C LC_TELEPHONE=C
    [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

    attached base packages:
    [1] parallel stats4 stats graphics grDevices utils datasets
    [8] methods base

    other attached packages:
    [1] DESeq2_1.20.0 SummarizedExperiment_1.10.1
    [3] DelayedArray_0.6.6 BiocParallel_1.14.2
    [5] matrixStats_0.61.0 Biobase_2.40.0
    [7] GenomicRanges_1.32.7 GenomeInfoDb_1.16.0
    [9] IRanges_2.14.12 S4Vectors_0.18.3
    [11] BiocGenerics_0.26.0

    loaded via a namespace (and not attached):
    [1] locfit_1.5-9.4 Rcpp_1.0.7 lattice_0.20-45
    [4] digest_0.6.29 utf8_1.2.2 R6_2.5.1
    [7] backports_1.4.1 acepack_1.4.0 RSQLite_2.2.9
    [10] ggplot2_3.3.5 pillar_1.6.4 zlibbioc_1.26.0
    [13] rlang_0.4.12 rstudioapi_0.13 data.table_1.14.2
    [16] annotate_1.58.0 blob_1.2.2 rpart_4.1-15
    [19] Matrix_1.4-0 checkmate_2.0.0 splines_3.5.1
    [22] geneplotter_1.58.0 stringr_1.4.0 foreign_0.8-70
    [25] htmlwidgets_1.5.4 bit_4.0.4 RCurl_1.98-1.5
    [28] munsell_0.5.0 compiler_3.5.1 xfun_0.29
    [31] pkgconfig_2.0.3 base64enc_0.1-3 htmltools_0.5.2
    [34] nnet_7.3-16 tibble_3.1.6 gridExtra_2.3
    [37] htmlTable_2.3.0 GenomeInfoDbData_1.1.0 Hmisc_4.1-1
    [40] XML_3.99-0.3 fansi_0.5.0 crayon_1.4.2
    [43] bitops_1.0-7 grid_3.5.1 DBI_1.1.2
    [46] xtable_1.8-4 gtable_0.3.0 lifecycle_1.0.1
    [49] magrittr_2.0.1 scales_1.1.1 cachem_1.0.6
    [52] stringi_1.7.6 XVector_0.20.0 genefilter_1.62.0
    [55] latticeExtra_0.6-28 ellipsis_0.3.2 vctrs_0.3.8
    [58] Formula_1.2-4 RColorBrewer_1.1-2 tools_3.5.1
    [61] bit64_4.0.5 glue_1.6.0 fastmap_1.1.0
    [64] survival_3.2-13 AnnotationDbi_1.42.1 colorspace_2.0-2
    [67] cluster_2.1.2 memoise_2.0.1 knitr_1.37

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