The scripts Choc_GSEA and Choc_Volcano_plot are not described in the README file

Help ith my advisor's issue

Hi! My advisor ask me to do a very difficult task with my paper's pictures. Here is literally what he said:

There are some problems with the code colors in the volcano plot and the PCA plot. Firstable, the volcano plot does not differ between sub and over expressed genes in colors: both have the same color. Second, there is no difference in color between significant differentially expressed genes and non significant (all are in black dots). Please check that.Second: We had followed the code colors in other graphs for Resistant and sensitive patients (Blue cyan and red, respectively). In your graph they are inverted. Please correct. Thanks!

So, I hope that you can help me with the 2 issues.

1.- Volcano Plot

This is the code I'm using for Volcano plot.

##Indicate color code##

cols[BCresultsNR$log2FoldChange < -1.5] <- "#0066FF"
cols[BCresultsNR$log2FoldChange > 1.5] <- "#0033CC"
cols[BCresultsNR$pvalue == 0] <- "black"
cols[BCresultsNR$sig < -log10(alpha) ] <- "#000033"
cols[BCresultsNR$pvalue > 0.05] <- "#CCCCCC"

And my problem is that I couldn't have a color code with 6 colors. Please Help!

2.- PCA plot (SOLVED!!)

I had problems with PCA too. But I solved it. Here is my first script, that does not work with what I want, and here is my solution. Thanks!!

Hi Laura,

In generar your repository structure are fine, and your general README.md are well documented an explicit. But it is necessary to use this 2 big sections? (Exoma and Transcriptoma) (is your decision)

Your numerated scripts are well commented, but what about Choc_GSEA?
In your/Transcriptome/bin/ script 2 at line 25 and 34 you are using absolute paths, I suggest to use relative paths in order to avoid problems if the user do not set the /lncRNA_BC/ at ~/

You have no data or scripts in the /Exome/ directories, remember you must put your data in OSF or toy data (just like in the transcriptome section), and it looks like the .csv in bot meta directories are the same, is this correct?
Your Exome/README.md are empty
I understand this repo is in development, but this half is almost empty

Remember the evaluation criteria, at this moment you do not have any R plot and there are no discussion file

Hi Laura,

I enjoyed revising your repo that is clear and well organized. You have been particularly careful at attending the issues that I mentioned in the last evaluation. I greatly appreciate it.

Some minor comments:
Be careful with the names of folders between your readme and the repo (i.e. "transcriptome analysis" or "transcriptome"). It can be confusing if they are not the same.

The discussion of results (Repo_Abstract_and_Discussion.md) need to be mentioned in the general README, at least with a link (I almost missed it!). It would be good to link more your results and graphics to this file because right now it is a little bit isolated from the rest of your repo. The idea of such file is to make a summary of what you have done!

The files GRAPHS.txt are superfluous and can now be discarded. It would also be good to link the graphics to the codes and data they were generated with, for example in the README of each analysis. That way the reader interested by a figure can readily find the code to generate it.

Don't hesitate to get back to us for any feedback. I hope you enjoyed the course!

Edit and add info. Be organized and simple

R plot and there are no discussion file

All scripts in transcriptome folder

It is necessary for your own good

• Subdivide your cards

• Write Scripts

Hi! I'm here again with problems to construct graphs.

I have very different data of the expression of one particular lincRNA between breast cancer cell lines MCF-10A, MCF-7, BT474 and MDA-MB-231, as I show in my data Promlc here

I want to construct a barplot with these data, and I want it to look like this

But... it looks like this...

This is the R code that I've been following:

Pre-requisites:

library(plotrix)

plotrix::gap.barplot(Promlc, gap = c(150, 650), xaxlab= c("MCF-10A", "MCF-7", "BT474", "MDA-MB-231"), ytics = c( 50, 100, 800, 900), col =  c("blue", "light blue", "blue", "green"), ylim =c(0,400))

My principal problem is that I cannot stablish scales to make the barplot better. I'm not sure if I'm using the wrong tool, or I'm not providing the necessary parameters in my original code.

Please Help!!

You must reorganize your repo structure

The folder for "results" is missing in data. I suggest you make a separate folder inside the Transcriptome directory for results and graphics

Hi Laura,

I had a look at your repo and README file. In general it is good and well-structured, well done! Below are some suggestions for improvement:

General README

• I suggest you include the information from Repo_analysis.md as an introduction for your project in the general README (or at least a link to Repo_analysis.md in the general README)
• Please describe shortly what are the files included in the STB folder, with links to your presentations

Exome project
The README file of the Exome project needs to be completed, explaining briefly the goals of the projects and describing the data, scripts and code for meta that are (or will be) included.

Transcriptome project:

• Please explain the code for the meta data in the README file
• The scripts Choc_GSEA and Choc_Volcano_plot are not described in the README file
• The folder for "results" is missing in data. I suggest you make a separate folder inside the Transcriptome directory for results and graphics

Your Exome/README.md are empty

You have no data or scripts in the /Exome/ directories, remember you must put your data in OSF or toy data (just like in the transcriptome section), and it looks like the .csv in bot meta directories are the same, is this correct?

Yoy have to add in the Markdown file your issues

In README

Hi! I was trying to put in order my repo and I started with my README.

I organized my repo with the following folders:

1. Transcriptome

• Bin
• Graphs
• Metadata
• Data

2. Exome

• Bin
• Metadata
• Data

And, for specific use in my project, I need to have sub-folders in Data, just like this:

• Data
  • Results
    • Quality (for FastQC reports)
    • Tables (for the count tables)
    • DESeq objects (for DESeq objects, because it contains inside a lot of factor's info)

But I couldn't achieved that... All my folders look like they were located in the same level in my organization, just like this. I tried also to use numbered list style, but it doesn't help to follow the README...

Could you help me with that?

Hi! I have an issue that I want to discuss with you, hopping that you can give me an adecuate advice.

As you know, I want to know the lincRNA that are differentially expressed in resistant patients, and I also want to know more information about how this lincRNA are involved in resistant processes. To answer that, the simplest way is to look every lincRNA differentially expressed... but I have the problem that most of my differentially expressed lincRNA are only annotated and there is no functional or biological information about them. For that reason, I though it could be a good idea to perform a gene set enrichment analysis, to know in what kind of processes this lincRNA could be involved.

To do that, I was using SeqGSEA package in DE-only analysis mode in R, but when I'm running it, this appears...

Warning message:
In .local(object, ...) :
  in estimateDispersions: sharingMode=='gene-est-only' will cause inflated numbers of false positives unless you have many replicates.

Anyway, if I continue running the analysis, it stops in solving permutation and then appears this:

DEpermNBstat <- DENBStatPermut4GSEA(DEG, permuteMat)
There were 50 or more warnings (use warnings() to see the first 50)

And there is no object created.

In here you can find my count table for differential expression analysis.

And in here is my script.

I want to know if you could help me with GSEA analysis: If you know another package in R for GSEA, or if you know how to avoid the replicates problem... or another way to perform this analysis.

Thanks!

Your numerated scripts are well commented, but what about Choc_GSEA?
In your/Transcriptome/bin/ script 2 at line 25 and 34 you are using absolute paths, I suggest to use relative paths in order to avoid problems if the user do not set the /lncRNA_BC/ at ~/

Uptdate all the files locations in Volcano plot issue, bar plot issue and GSEA issue