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hello all, i am doing a differential gene expression analysis using limma, i have 3 conditions S0,S1, and S3. I am creating the contrasts and doing the fit function but its giving the error ( Number of rows of contrast matrix must match number of coefficients in fit)
> contrast.matrix <- makeContrasts(
+ S1_vs_S0 = S1 - S0,
+ S3_vs_S0 = S3 - S0,
+ S1_vs_S3 = S1 - S3,
+ levels = design
+ )
>
> # Fit contrasts
> fit2 <- limma::contrasts.fit(fit, contrast.matrix)
Error in limma::contrasts.fit(fit, contrast.matrix) :
Number of rows of contrast matrix must match number of coefficients in fit
the number of row in contrast matrix is 3L and nb of coefficient in fit 24670L
> sessionInfo()
R version 4.1.1 (2021-08-10)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Ubuntu 20.04.6 LTS
Matrix products: default
BLAS/LAPACK: /shared/ifbstor1/software/miniconda/envs/r-4.1.1/lib/libopenblasp-r0.3.18.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C 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 LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] rtracklayer_1.54.0 DiffBind_3.4.11 BiocParallel_1.28.3
[4] BiocManager_1.30.23 openxlsx_4.2.5.2 TxDb.Hsapiens.UCSC.hg38.knownGene_3.14.0
[7] GenomicFeatures_1.46.5 org.Hs.eg.db_3.14.0 AnnotationDbi_1.56.1
[10] ChIPpeakAnno_3.28.0 ChIPseeker_1.30.3 magrittr_2.0.3
[13] lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1
[16] dplyr_1.1.4 purrr_1.0.2 readr_2.1.5
[19] tidyr_1.3.1 tibble_3.2.1 tidyverse_2.0.0
[22] DESeq2_1.34.0 SummarizedExperiment_1.24.0 MatrixGenerics_1.6.0
[25] matrixStats_0.62.0 GenomicRanges_1.46.1 GenomeInfoDb_1.30.1
[28] IRanges_2.28.0 S4Vectors_0.32.4 Biobase_2.54.0
[31] BiocGenerics_0.40.0 limma_3.50.3 ggplot2_3.5.1
loaded via a namespace (and not attached):
[1] utf8_1.2.2 tidyselect_1.2.1 RSQLite_2.2.8
[4] htmlwidgets_1.5.4 grid_4.1.1 scatterpie_0.1.7
[7] munsell_0.5.0 systemPipeR_2.0.4 withr_2.5.0
[10] colorspace_2.0-3 GOSemSim_2.20.0 filelock_1.0.2
[13] rstudioapi_0.16.0 DOSE_3.20.1 labeling_0.4.2
[16] bbmle_1.0.24 GenomeInfoDbData_1.2.7 mixsqp_0.3-43
[19] hwriter_1.3.2 polyclip_1.10-0 bit64_4.0.5
[22] farver_2.1.1 coda_0.19-4 vctrs_0.6.5
[25] treeio_1.18.1 generics_0.1.3 lambda.r_1.2.4
[28] timechange_0.3.0 BiocFileCache_2.2.0 regioneR_1.26.0
[31] R6_2.5.1 apeglm_1.16.0 graphlayouts_0.8.0
[34] invgamma_1.1 locfit_1.5-9.4 AnnotationFilter_1.18.0
[37] bitops_1.0-7 cachem_1.0.6 fgsea_1.20.0
[40] gridGraphics_0.5-1 DelayedArray_0.20.0 BiocIO_1.4.0
[43] scales_1.3.0 ggraph_2.0.5 enrichplot_1.14.1
[46] gtable_0.3.1 ensembldb_2.18.4 tidygraph_1.2.0
[49] rlang_1.1.3 genefilter_1.76.0 splines_4.1.1
[52] lazyeval_0.2.2 yaml_2.3.6 reshape2_1.4.4
[55] qvalue_2.26.0 RBGL_1.70.0 tools_4.1.1
[58] ggplotify_0.1.0 gplots_3.1.3.1 RColorBrewer_1.1-3
[61] Rcpp_1.0.9 plyr_1.8.7 progress_1.2.2
[64] zlibbioc_1.40.0 RCurl_1.98-1.9 prettyunits_1.1.1
[67] viridis_0.6.2 ashr_2.2-47 ggrepel_0.9.1
[70] data.table_1.14.2 futile.options_1.0.1 DO.db_2.9
[73] truncnorm_1.0-8 mvtnorm_1.1-3 SQUAREM_2021.1
[76] amap_0.8-19 ProtGenerics_1.26.0 hms_1.1.3
[79] patchwork_1.1.1 xtable_1.8-4 XML_3.99-0.9
[82] VennDiagram_1.7.0 emdbook_1.3.12 jpeg_0.1-9
[85] gridExtra_2.3 compiler_4.1.1 biomaRt_2.50.0
[88] bdsmatrix_1.3-7 KernSmooth_2.23-20 crayon_1.5.2
[91] shadowtext_0.0.9 htmltools_0.5.2 ggfun_0.0.4
[94] tzdb_0.2.0 geneplotter_1.72.0 aplot_0.1.1
[97] DBI_1.2.2 tweenr_1.0.2 formatR_1.11
[100] dbplyr_2.5.0 MASS_7.3-54 rappdirs_0.3.3
[103] boot_1.3-28 ShortRead_1.52.0 Matrix_1.3-4
[106] cli_3.6.2 parallel_4.1.1 igraph_1.3.1
[109] pkgconfig_2.0.3 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 GenomicAlignments_1.30.0
[112] numDeriv_2016.8-1.1 xml2_1.3.3 InteractionSet_1.22.0
[115] ggtree_3.2.1 annotate_1.72.0 multtest_2.50.0
[118] XVector_0.34.0 yulab.utils_0.0.4 digest_0.6.30
[121] graph_1.72.0 Biostrings_2.62.0 fastmatch_1.1-3
[124] tidytree_0.3.6 edgeR_3.36.0 restfulr_0.0.13
[127] GreyListChIP_1.26.0 curl_5.2.1 Rsamtools_2.10.0
[130] gtools_3.9.3 rjson_0.2.20 lifecycle_1.0.3
[133] nlme_3.1-153 jsonlite_1.8.8 futile.logger_1.4.3
[136] viridisLite_0.4.1 BSgenome_1.62.0 fansi_1.0.3
[139] pillar_1.9.0 lattice_0.20-45 KEGGREST_1.34.0
[142] fastmap_1.1.0 httr_1.4.7 plotrix_3.8-2
[145] survival_3.2-13 GO.db_3.14.0 glue_1.6.2
[148] zip_2.2.0 png_0.1-7 bit_4.0.4
[151] ggforce_0.3.3 stringi_1.7.8 blob_1.2.2
[154] latticeExtra_0.6-29 caTools_1.18.2 memoise_2.0.1
[157] irlba_2.3.5.1 ape_5.5
>
I dont really understand the problem becaus ethe concept of coeficient in fit is not so clear to me.
Thank u in advance.
thank you for your response. The problem is resolved. When i did a fit for the linear model i put NULL for the design fit <- lmFit(count_data, design=NULL) and thats what was causing the problem.