Last updated: 2020-01-23
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I performed gene filtering based on the criterion set forth in our previous paper.
Results There’s one, and turns out this over-expressed gene is one of the mitochrondrial genes.
\(~\)
Results: * Of 20,421 genes, 7,637 genes are classifed as lowly-expressed. Of these, 34 are ERCC control genes and 7,603 are endogenoeus genes.
library(knitr)
library(SingleCellExperiment)
library(dplyr)
library(heatmap3)
library(testit)
library(cowplot)
library(biomaRt)
library(knitr)
library(data.table)
sce_raw <- readRDS("data/sce-raw.rds")
anno = data.frame(colData(sce_raw))Filter out low-quality single cell samples.
anno_filter <- anno[anno$filter_all == TRUE,]
count_filter <- assay(sce_raw)[,anno$filter_all == TRUE]
dim(count_filter)[1] 20421 923There’s one, and turns out this over-expressed gene.
which_over_expressed <- which(apply(count_filter, 1, function(x) any(x>(4^6)) ))
over_expressed_genes <- rownames(count_filter)[which_over_expressed]
over_expressed_genescharacter(0)Get over-expressed gene info via biomaRt.
over_expressed_genes_info <- getBM(
attributes = c("ensembl_gene_id", "chromosome_name",
"external_gene_name", "transcript_count",
"description"),
filters = "ensembl_gene_id",
values = over_expressed_genes,
mart = ensembl)Compute CPM
cpm <- t(t(count_filter)/colSums(count_filter))*(10^6)Lowly-expressed genes := gene mean < 2 CPM
cpm <- t(t(count_filter)/anno_filter$molecules)*(10^6)
which_lowly_expressed <- which(rowMeans(cpm) < 2)
length(grep("ERCC", which_lowly_expressed))[1] 0length(grep("ENSG", which_lowly_expressed))[1] 0Get gene info via biomaRt.
lowly_expressed_genes_info <- getBM(
attributes = c("ensembl_gene_id", "chromosome_name",
"external_gene_name", "transcript_count",
"description"),
filters = "ensembl_gene_id",
values = which_lowly_expressed[grep("ENSG", which_lowly_expressed_genes)],
mart = ensembl)Including 12784 genes.
gene_filter <- unique(c(which_over_expressed, which_lowly_expressed))
genes_to_include <- setdiff(1:nrow(count_filter), gene_filter)
length(genes_to_include)[1] 11168R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.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] data.table_1.12.0 biomaRt_2.38.0
[3] cowplot_0.9.4 ggplot2_3.2.1
[5] testit_0.9 heatmap3_1.1.6
[7] dplyr_0.8.0.1 SingleCellExperiment_1.4.1
[9] SummarizedExperiment_1.12.0 DelayedArray_0.8.0
[11] BiocParallel_1.16.0 matrixStats_0.55.0
[13] Biobase_2.42.0 GenomicRanges_1.34.0
[15] GenomeInfoDb_1.18.1 IRanges_2.16.0
[17] S4Vectors_0.20.1 BiocGenerics_0.28.0
[19] knitr_1.20
loaded via a namespace (and not attached):
[1] Rcpp_1.0.3 lattice_0.20-38 prettyunits_1.0.2
[4] assertthat_0.2.1 rprojroot_1.3-2 digest_0.6.20
[7] R6_2.4.0 backports_1.1.2 RSQLite_2.1.1
[10] evaluate_0.12 httr_1.3.1 pillar_1.3.1
[13] progress_1.2.0 zlibbioc_1.28.0 rlang_0.4.0
[16] lazyeval_0.2.1 blob_1.1.1 whisker_0.3-2
[19] Matrix_1.2-17 rmarkdown_1.10 stringr_1.3.1
[22] bit_1.1-14 RCurl_1.95-4.11 munsell_0.5.0
[25] compiler_3.5.1 httpuv_1.4.5 pkgconfig_2.0.3
[28] htmltools_0.3.6 tidyselect_0.2.5 tibble_2.1.1
[31] GenomeInfoDbData_1.2.0 workflowr_1.6.0 XML_3.98-1.16
[34] crayon_1.3.4 withr_2.1.2 later_0.7.5
[37] bitops_1.0-6 grid_3.5.1 gtable_0.2.0
[40] DBI_1.0.0 git2r_0.26.1 magrittr_1.5
[43] scales_1.0.0 stringi_1.2.4 XVector_0.22.0
[46] fs_1.3.1 promises_1.0.1 fastcluster_1.1.25
[49] tools_3.5.1 bit64_0.9-7 glue_1.3.0
[52] purrr_0.3.2 hms_0.4.2 yaml_2.2.0
[55] AnnotationDbi_1.44.0 colorspace_1.3-2 memoise_1.1.0
sessionInfo()R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.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] data.table_1.12.0 biomaRt_2.38.0
[3] cowplot_0.9.4 ggplot2_3.2.1
[5] testit_0.9 heatmap3_1.1.6
[7] dplyr_0.8.0.1 SingleCellExperiment_1.4.1
[9] SummarizedExperiment_1.12.0 DelayedArray_0.8.0
[11] BiocParallel_1.16.0 matrixStats_0.55.0
[13] Biobase_2.42.0 GenomicRanges_1.34.0
[15] GenomeInfoDb_1.18.1 IRanges_2.16.0
[17] S4Vectors_0.20.1 BiocGenerics_0.28.0
[19] knitr_1.20
loaded via a namespace (and not attached):
[1] Rcpp_1.0.3 lattice_0.20-38 prettyunits_1.0.2
[4] assertthat_0.2.1 rprojroot_1.3-2 digest_0.6.20
[7] R6_2.4.0 backports_1.1.2 RSQLite_2.1.1
[10] evaluate_0.12 httr_1.3.1 pillar_1.3.1
[13] progress_1.2.0 zlibbioc_1.28.0 rlang_0.4.0
[16] lazyeval_0.2.1 blob_1.1.1 whisker_0.3-2
[19] Matrix_1.2-17 rmarkdown_1.10 stringr_1.3.1
[22] bit_1.1-14 RCurl_1.95-4.11 munsell_0.5.0
[25] compiler_3.5.1 httpuv_1.4.5 pkgconfig_2.0.3
[28] htmltools_0.3.6 tidyselect_0.2.5 tibble_2.1.1
[31] GenomeInfoDbData_1.2.0 workflowr_1.6.0 XML_3.98-1.16
[34] crayon_1.3.4 withr_2.1.2 later_0.7.5
[37] bitops_1.0-6 grid_3.5.1 gtable_0.2.0
[40] DBI_1.0.0 git2r_0.26.1 magrittr_1.5
[43] scales_1.0.0 stringi_1.2.4 XVector_0.22.0
[46] fs_1.3.1 promises_1.0.1 fastcluster_1.1.25
[49] tools_3.5.1 bit64_0.9-7 glue_1.3.0
[52] purrr_0.3.2 hms_0.4.2 yaml_2.2.0
[55] AnnotationDbi_1.44.0 colorspace_1.3-2 memoise_1.1.0