From cbb7c1d7a354d8e413efc2367509a521b4b096fc Mon Sep 17 00:00:00 2001 From: Davis McCarthy <dmccarthy@svi.edu.au> Date: Tue, 1 Oct 2019 19:19:02 +1000 Subject: [PATCH] Bug fix in exprs-norm --- course_files/exprs-norm.Rmd | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/course_files/exprs-norm.Rmd b/course_files/exprs-norm.Rmd index c4df548..dd8614f 100644 --- a/course_files/exprs-norm.Rmd +++ b/course_files/exprs-norm.Rmd @@ -541,7 +541,7 @@ instead of transcripts. `scater` uses the [biomaRt](https://bioconductor.org/packages/release/bioc/html/biomaRt.html) package, which allows one to annotate genes by other attributes: -```{r, message = FALSE, warning = FALSE} +```{r, message = FALSE, warning = FALSE, eval=FALSE} umi.qc <- getBMFeatureAnnos( umi.qc, filters = "ensembl_gene_id", @@ -579,19 +579,19 @@ umi.qc <- getBMFeatureAnnos( Some of the genes were not annotated, therefore we filter them out: -```{r} +```{r, eval=FALSE} umi.qc.ann <- umi.qc[!is.na(rowData(umi.qc)$ensembl_gene_id), ] ``` Now we compute the total gene length in Kilobases by using the `end_position` and `start_position` fields: -```{r} +```{r, eval=FALSE} eff_length <- abs(rowData(umi.qc.ann)$end_position - rowData(umi.qc.ann)$start_position) / 1000 ``` -```{r length-vs-mean, fig.cap = "Gene length vs Mean Expression for the raw data"} +```{r length-vs-mean, eval=FALSE, fig.cap = "Gene length vs Mean Expression for the raw data"} plot(eff_length, rowMeans(counts(umi.qc.ann))) ``` @@ -608,12 +608,12 @@ page](https://www.biostars.org/p/83901/). Now we are ready to perform the normalisations: -```{r} +```{r, eval=FALSE} tpm(umi.qc.ann) <- log2(calculateTPM(umi.qc.ann, eff_length) + 1) ``` Plot the results as a PCA plot: -```{r norm-pca-fpkm, fig.cap = "PCA plot of the tung data after TPM normalisation"} +```{r norm-pca-fpkm, eval=FALSE, fig.cap = "PCA plot of the tung data after TPM normalisation"} tmp <- runPCA( umi.qc.ann, exprs_values = "tpm", @@ -626,11 +626,11 @@ plotPCA( ) ``` -```{r} +```{r, eval=FALSE} tpm(umi.qc.ann) <- log2(calculateFPKM(umi.qc.ann, eff_length) + 1) ``` -```{r norm-pca-tpm, fig.cap = "PCA plot of the tung data after FPKM normalisation"} +```{r norm-pca-tpm, eval=FALSE, fig.cap = "PCA plot of the tung data after FPKM normalisation"} tmp <- runPCA( umi.qc.ann, exprs_values = "tpm", -- GitLab