RNA-seq | RNA-seq analysis scripts | Genomics library

I have a set of 270 RNA-seq samples, and I have already subsetted out their expected counts using the following code:

Suppose I want to show in a barplot the gene expression results (logFC) based on RNA-seq and q-PCR analysis. My dataset looks like that:

When trying to pull the official image for RNA-seq aligner STAR with docker pull alexdobin/star

I got an error despite copying the Docker Pull Command as shown in the screenshot (lower right)

The error was the following:

Error response from daemon: manifest for alexdobin/star:latest not found: manifest unknown: manifest unknown

I am trying to use the script tpm_rpkm.R script. but i am getting error saying

Error in apply(counts, 2, function(x) rpkm(x, lengths)) : dim(X) must have a positive length.

(The data table should not have any error as it was generated through same programme as that the author of the script used.)

Here is the script

I'm still learning R, I have this dataset, it has 5 columns, first column is tracking_id, the next four columns have values of four groups.

First, I want to filter rows that have values equal or larger than 1, then I want to filter rows based on comparison of the last three columns ("CD44hi_CD69low_rep","CD44hi_CD69hi_CD103low_rep","CD44hi_CD69hi_CD103hi_rep") that are 8 folds higher or 4 folds lower compared to column ("CD44low_rep").

The output should have 5 columns, with values equal or larger than 1 that are 8 fold higher or 4 fold less of the last three column compared to second column.

I should get something like this:

To filter rows equal or larger than 1, I tried this:

I am trying to add some headers to a txt file. Actually i have found a script already but I want to edit a part of it. Script (you can also find it here if you like: https://ucdavis-bioinformatics-training.github.io/2017-June-RNA-Seq-Workshop/thursday/counts.html):

So I have a gene alignment result (I think it's from RNA-seq) in which specific sequences are matched to certain genes (those genes repeat themselves sometimes). I am now using C++ to find the earliest possible position at which most unique genes have been counted and I can confidently use only the first part for further analysis. The problem is that the file I have is sorted (so sequences from the same gene are put together), but I want to calculate that for non-sorted files.

What I am doing now is to manually std::shuffle my std::vector geneList before iterating through it. In each iteration I would compare every coming gene from the geneList to a unique gene list and update it if none within it matches that coming gene. Then I would sample count_gene and count_unique_gene with some interval and finally get the x% position. This is very costly...with only 140,000 genes costing me several minutes. Sample code (also included my input code for better understanding):

I'm working on an RNA-seq analysis and I'm interested in what genes are driving tissue-specific variation in gene expression. PCAsare common in RNA-seq analyses, but most packages (e.g. DESeq2) only take it as far as the 2D plot. Therefore, I've used prcomp and fviz_pca_ind to produce my 2D plot so I can take the analysis a bit further after. However, due to the input data structure, I can't seem to get my grouping information (i.e. tissues) to be included in my prcomp object and as a result can't color-code my samples or produce confidence intervals around my groups.

Packages:

I have a data frame from TCGAbiolinks and need to narrow it down to just unnormalized data. I tried writing some sort of for loop that will return the rows where the tags variable in subset.gbmexp includes "unnormalized" but can't seem to get the code right. Something along the lines of: