Using #Terminal in #MacOS and want to save all of the text as a file? Use the shortcut ⌘S (or go to the "Shell" menu and select "Export Text As ...")

Welcome Dr. Montgomery! We're excited to work with you and that you'll be heading up our team!

In #bash, scripts normally run within a subshell, so any environment changes within that script go away afterwards. However, if you "source" that script, environment changes are incorporated into your current environment.

Convert #Rstats data frame to a #Seurat Object. (Assumes row names=gene IDs, columns=cells): library(Seurat) library(Matrix) df <- read.table("counts.txt", header=TRUE) mat <- Matrix(as.matrix(df), sparse=TRUE) seurat_obj <- CreateSeuratObject(counts = mat, project="proj")

Using file descriptors in #Bash #shell # Open file as read-only (file descriptor 3) exec 3< file.txt # read and print first line read line <&3 echo "First line: \"$line\"" # read and print remaining lines while read line <&3; do echo "Next line: \"$line\"" done

We have found the book "Immune" by Peter Dettmer to be an entertaining and informative starting point on #Immunology. (And, yes, our immunologist friends, it is simplified, which is why we mention it as a good "starting point")

In trying to debug some ChipSeeker code (github.com/YuLab-SMU/ChIP…), we just stumbled across the fact that max and min of NULL returns -Inf and +Inf, respectively. #Rstats This happens when you have too little data for the function plotDistToTSS.

Calling all high school students, parents and teachers! Applications for the 2024-25 Teen Leaders program are due March 15! 📣 ➡️ Learn more and share this with a teen who would be a great fit! omrf.org/about-omrf/edu…

Having started multiple jobs on a #Linux machine (e.g. using #bash) use #watch to check the last few lines of each file every 2 seconds: watch tail -n2 *.log

Removing cells from #scRNASeq #Seurat object: counts <- Read10X("filt_bc_matrix") obj <- CreateSeuratObject(counts) cells <- rownames([email protected]) remove <- c("TTTACTGG-1", "TTGGCAAG-1", "TTGGAACT-1") keep <- cells[! cells %in% remove] result <- subset(obj, cells = keep)

You can use #dynamic #variable names in #bash #shell: id_file="ids.txt" R1="sample_1.fastq.gz" for i in id_file R1; do echo "Variable '$i' contains the value '${!i}'" done

You can create dummy input files within an #Rstats document, especially useful for testing purposes: text_block <- "A,B X,1,2 Y,3,4" dat <- read.csv(text = text_block) dat A B X 1 2 Y 4 9

Hello #Bioinformatics Twitter/X: OMRF is hiring a Data Analyst in the Center for Biomedical Data Sciences. #job #career #Rstats #python #biology #research #scRNASeq #biostats social.icims.com/viewjob/pt1736…

Calculate DE between sample "WT" & "KO" for cluster "2": clust2 <- subset(obj, seurat_clusters == "2") Idents(clust2) <- "sample" markers2 <- FindMarkers(clust2, ident.1="WT", ident.2="KO") write.csv(markers2, "markers2.csv", row.names=FALSE) #Rstats #scRNAseq #Seurat

Attending #SingleCellGenomicsDay right now: satijalab.org/scgd25/