From: "Gloria K. Muday" <muday@wfu.edu>
Subject: Re: [EXTERNAL] Questions about sample labeling Salmon and IGB files
Date: May 4, 2023 at 4:00:13 PM EDT
To: Molly Davis <mdavi258@uncc.edu>
Cc: Ann.Loraine@uncc.edu, Robert Reid <RobertReid@uncc.edu>,  Mark Johnson <mark_johnson_1@brown.edu>, Anthony Postiglione <postae18@wfu.edu>,  "Ali, Mohammad Foteh" <alimf@wfu.edu>

Molly and Ann,

Thanks for these plots.  These plots warm our hearts as it is so clear now that the data is logically grouping now the samples are linked to the appropriate names!!!

Thanks to you all for all you have done to ID the sample problems and now highlight the sample strengths!

Gloria

On Thu, May 4, 2023 at 2:22 PM Molly Davis <mdavi258@uncc.edu> wrote:
Hello Muday Lab, 

Great news! 

We finished renaming samples using your spreadsheet and checked them using MDS plots. 

Here are the reports:

	•	https://bitbucket.org/hotpollen/flavonoid-rnaseq/src/main/72_F3H_PollenTube/AddGeneAnnotations.pdf 
	•	https://bitbucket.org/hotpollen/flavonoid-rnaseq/src/main/72_F3H_PollenTube/MakeMdsPlots.pdf 

Note: In above links, click three dots and choose "open raw" to download above PDFs and open them on your computer for review.

Thank you! :-)

On Tue, May 2, 2023 at 9:25 AM Gloria K. Muday <muday@wfu.edu> wrote:
Ann,

THANK YOU! This is wonderful news!

Gloria

On Tue, May 2, 2023 at 9:22 AM Ann Loraine <Ann.Loraine@uncc.edu> wrote:
I am working on it. 

On Tue, May 2, 2023 at 9:20 AM Gloria K. Muday <muday@wfu.edu> wrote:
Ann, Rob, and Molly,

Happy end of the semester! We are now in the midst of finals week at WFU, but are excited that the fog of the semester will soon lift! I expect Molly might be in the throw of finals and hope those go well for her. I had hoped to connect with you all last week at the GTTR meetings, but you all must have had a conflict.

I wanted to ask about the analysis of these RNAseq  samples and the timeline for your relabeling of them and getting a new set of DE genes, volcano plots, and PCA plots. I am presenting at a conference that begins May 22 and I had hoped to talk about the results from this RNA Seq experiment at that meeting. 

The other pressing time concern on our end is that Anthony graduates this summer and as the lead on this experiment, he'd really like to have the dataset in hand so he can finish that analysis of DE genes for inclusion in the last chapter of his thesis.

I hope that the error on the part of Azenta is now clear and our spreadsheet on how to relabel the samples. Please let Anthony and I know if you have any questions.

I hope that it is easy to rerun scripts once you rename the samples. Can you give us a sense of your timeline?

Thanks,
Gloria

On Wed, Apr 19, 2023 at 4:41 PM Gloria K. Muday <muday@wfu.edu> wrote:
Ann and Molly and Rob,

We now have fully resolved the problem with our RNA Seq samples and how Azenta ignored our sample labels and incorrectly reported sample names in replicates 8 and 9.
 
Anthony and I separated worked through the misordered samples and both came up with the same pattern.  In the attached Excel sheet, you can see in the FIRST column what the original sample names were (before that switch of a couple of the are samples). In the SECOND column are what those samples really are.

When you rename the samples, we'd like you to keep the old name on the sheet someone to prevent in any confusion. What would be really helpful to us is if after you rename the lanes, you could put them in the intended order.

We are also planning to examine this data to look at the abundance of transcripts of specific genes.  Ann did note that we should look at normalized reads.  We'd love to have such a spreadsheet that had the normalized reads.  We'd also be so appreciative if you could export those values to an excel sheet with the SolyIDs of each gene and the gene names.

Now that we have clear sample identities, we'd love to see if the PCA plot shows groups based on temperature and genotypes and DE genes!

Thank you for all the effort to try to resolve the problem.  

It is unfortunate that it took Azenta so long to send the photo and that they totally ignored the sample names and ran the samples in a random and confused order.  If you want to see what happened, you can look at the attached powerpoint file.

Thanks,
Gloria, Anthony, and Foteh

On Sun, Apr 16, 2023 at 8:50 PM Ann Loraine <Ann.Loraine@uncc.edu> wrote:
Hi,

Molly and I are working with this file as the start of the data analysis pipeline work:
https://bitbucket.org/hotpollen/flavonoid-rnaseq/src/main/ExternalDataSets/muday-144-SL5_salmon.merged.gene_counts.tsv

The order of columns is determined by this configuration file, used to run the pipeline:
https://bitbucket.org/hotpollen/flavonoid-rnaseq/src/main/ExternalDataSets/muday-144_samples.csv

The above "original salmon" file shows the counts observed for each gene from the fastq files. Samples are named after the file (sample) that they came from.

(Just making sure we're all on the same page with respect to input data files :-) 

Based on y'alls visual analysis a few weeks ago, we tried to correct the sample switching problem in the next step of the data analysis workflow, which creates another counts file by adding a new column with gene descriptions to this original data file. It also renames the columns using sample codes, the same ones you see in IGB. Also at this step, we re-label some samples based on what you and Anthony figured out using IGB.

The report on what we did, and how, is here:
	•	https://bitbucket.org/hotpollen/flavonoid-rnaseq/src/main/muday-144-analysis/AddGeneAnnotations.pdf (click "open raw" to get the latest version). 
The output file is:
	•	https://bitbucket.org/hotpollen/flavonoid-rnaseq/src/main/muday-144-analysis/results/muday-144-SL5_counts-salmon.txt 
This new file was used as inputs for all the subsequent steps, e.g., MDS plots that you presented in your last presentation to the group.

Please note that none of these "counts" files is normalized. The libraries were sequenced to different depths, which means that even genes with totally stable expression unaffected by time or treatment will appear to be variably expressed simply due to the differences in total numbers of reads sequenced. You know that, of course! I always repeat this because it's such an important thing to keep in mind when working with RNA-Seq data. 

To compare counts across sample types, you have to normalize them in some way. If you like, we can very easily provide normalized "counts per million" fukes instead of "raw counts". If you say "yes yes yes I need it!" I will do it sooner rather than later :-) Otherwise I will prioritize other tasks.

Regarding the IGB visualizations:

The current datasets listed in the "Available Data" section of IGB faithfully show the reads, coverage graphs, etc for the original data files, without any renaming of samples to reflect y'alls visual analysis.  I didn't rename any samples in the IGB setup because I thought it would be unwise to do so at this stage, due to our not being completely sure if our sample re-naming scheme is right. I wanted to make sure we could easily  revisit that crucial visual analysis you did to come up with the new names. 

That said, I could very easily make two "folders" in IGB that would show pre- and post-sample renaming. 

By making "before" and "after" sample relabeling visualizations in IGB, I can make it much easier for all of us to check our work. With many eyes on the problem, we are more likely to avoid mistakes.

What Molly and I have been focusing on this past week was setting us up to determine if we can distinguish VF36 from F3H-OX3 samples. It turned out that searching for selective marker sequences (from the kanamycin resistance gene) amongst the fastq files did not yield definitive results, despite the appealing simplicity of the approach. So, we decided to try my original idea of aligning all the sequences against the construct, much as we did in that soybean paper I mentioned a bunch of ties. This last week, Molly created some data files we needed for that. 

I would say we should meet up later in the week after Molly and I make progress on this next strategy, and after I set up "before" and "after" sample relabeling visualizations in IGB. 

Also see: 
	•	https://jira.bioviz.org/browse/IGBF-3290 (describes our sample relabeling task)

On Sat, Apr 15, 2023 at 5:22 PM Gloria K. Muday <muday@wfu.edu> wrote:
Ann, Rob, and Molly,

After Rob's suggestion that we look at the Salmon file in Bitbucket, we decided to make a comparison Excel sheet lining up the data from the two Salmon files and IGB to understand the data better. The attached excel file has a comparison of the reads of the F3H gene.

Please look at the third sheet whose title is COMMENTS ON SHEET LABELING

Anthony pulled together this spreadsheet and I spent some time trying to make labels that clarify what we think we are seeing. Anthony's explanation is below. 
Here is my summary: 

The order of the samples in the Bitbucket Salmon file are not in the EXPECTED ORDER for Replicate 8.  Anthony listed his expected order based on a pattern of samples organized by replicate, then by genotype, then by cool and warm within each time of pollen tube growth.  That is the first row of the spreadsheet.  Below that is the sample order in the Salmon sheet, and below that are comments on the presence or absence of the are SNP in IGB.  To us it looks like the sample names are not the same in the Salmon file and in IGB.  Rather the IGB samples appear to be labeled based on the EXPECTED ORDER, but not the SALMON FILE ORDER.

To test this hypothesis, Anthony looked at expression levels in IGB of the samples from replicate 8. A screen shot of that is attached.  The levels of F3H transcripts show no clear pattern.  When he assigns the samples the names that go with Salmon FILE ORDER and not the EXPECTED ORDER, the transcript abundance is more consistent within genotypes.

Do you think we are accurately reading the data and making an appropriate hypothesis? If you could double check things on your end and let us know whether this might be correct (or if you have alternative hypotheses), we'd be appreciative.

If this does make sense, is it the case that the PCAs might have been made with the EXPECTED ORDER rather than the SALMON FILE order? 

We also pasted the read count from Rob's Salmon file in this Excel file.  Those values are very different from the values in the newer Salmon file.  Any ideas why that is?

Anthony and I would like to discuss this on Monday or Tuesday if you all have time. (I am out of town the rest of the week)
Times that work for conversations are: 
Monday any time before 3:30
Tuesday 11:30 to 12:30 or after 4:00.
(We have a job candidate talking during the regular tech meeting slot, so that does not work for us).

Thanks,
Gloria

On Sat, Apr 15, 2023 at 12:52 PM Postiglione, Anthony <postae18@wfu.edu> wrote:
Gloria,

I have included an Excel document that contains three sheets: one being the new Salmon file pulled from Bitbucket, one is the original Salmon file we received that can be found in the PGRP Google Drive folder, and comments that I have on a number of odd looking samples within each Salmon file. I have some questions pertaining to each Salmon file, but for different reasons.

The BitBucket Salmon file has sample labels that go out of order in one of the replicates, #8. For example, a sample labeled "are" is included in the middle of a group of OE3 samples. This could explain why there are some samples in IGB that appear to be "are"  in terms of F3H expression, but are labeled "OE3" and vice versa. I have attached the IGB pictures of what the scaled graphs look like as they are currently labeled and then what they look like if you simply put them in the correct order.

The Original Salmon file from the Google Drive looks to have the labeling in the correct order, but a few samples that have read counts that appear to be outliers when compared to rest of their genotype. Coincidentally, they are the same exact samples that are out of order in terms of labeling in the BitBucket Salmon file (Replicate #8). 

All of these comments can be viewed in more detail in the attached Excel document, under the final tab in the document titled: "Comments on sheet labeling".

Hopefully this clears some things up,

Anthony

Anthony Postiglione 

PhD Candidate, Muday Lab
Biology Department
Wake Forest University
Wake Downtown 2901 

-- 
Anthony Postiglione 

PhD Candidate, Muday Lab
Biology Department
Wake Forest University
Wake Downtown 2901 

-- 
Gloria Muday
Director, Center for Molecular Signaling
Charles M. Allen, Professor of Biology
Wake Forest University
336-758-5316

-- 

Ann Loraine, Ph.D.
Professor, Bioinformatics & Genomics
Genome Visualization Lab
College of Computing & Informatics
University of North Carolina, Charlotte
https://lorainelab.org
https://bioviz.org

-- 
Gloria Muday
Director, Center for Molecular Signaling
Charles M. Allen, Professor of Biology
Wake Forest University
336-758-5316

-- 
Gloria Muday
Director, Center for Molecular Signaling
Charles M. Allen, Professor of Biology
Wake Forest University
336-758-5316

-- 
Gloria Muday
Director, Center for Molecular Signaling
Charles M. Allen, Professor of Biology
Wake Forest University
336-758-5316

-- 

Ann Loraine, Ph.D.
Professor, Bioinformatics & Genomics
Genome Visualization Lab
College of Computing & Informatics
University of North Carolina, Charlotte
https://lorainelab.org
https://bioviz.org

-- 
Gloria Muday
Director, Center for Molecular Signaling
Charles M. Allen, Professor of Biology
Wake Forest University
336-758-5316

-- 
Molly Davis 
Bioinformatician 
704-657-5229
mdavi258@uncc.edu 
molly.davis.bioinformatics@gmail.com 

-- 
Gloria Muday
Director, Center for Molecular Signaling
Charles M. Allen, Professor of Biology
Wake Forest University
336-758-5316