You summarised my entire semester of listening to droning lectures. I don't know why we don't have more effective teaching in schools. THIS WAS SO MUCH BETTER.
Thank you, I'm glad you found it helpful. It was one of those topics that had me thinking "am I really the right person to cover this", but it has ended up being one of my most successful videos!
Thanks, yes it was really an exercise in prioritization. I had to cut things like DDA vs. DIA as well as SWATH, both of which would have required major detours to fit in. They are probably topics that should be covered in a "deeper dive" presentation later.
I was not thinking of SWATH, although SWATH is compatible with multiplexing (as far as I know). What I had in mind was labeling approaches such as iTRAQ and TMT, which allow you to multiplex 8 and 16 samples respectively.
Thank you for the excellent presentation Professor. I have a question if you could answer or link to another video of you would be greatful. What are the different types of proteomics quantification methods? 1. Does it always LC-MSMS data analysis use peak area of XIC for quantification? Is isn’t possible to use peak intensity values? 2. In Label Free Quantification (LFQ / MaxQuant) what does it use ? What is the mechanism behind this?
I'm not completely sure what you mean. To do quantification you need to integrate the peak intensity, which in turn requires detecting where the peaks start and end. XIC is the most common peak detection algorithm as far as I know. I'm sure you can use other peak-detection algorithms than XIC, but I don't think you can avoid detecting peaks and integrating the area under them. Regarding LFQ in MaxQuant, the algorithm is called MaxLFQ - explaining it would take an entire paper (pubmed.ncbi.nlm.nih.gov/24942700/).
It should be the proteinGroups.txt that contains the identified proteins (or rather protein groups) and the intensity for each of them in each sample. Those are the values you need as input for a statistical analysis to identify differentially expressed proteins.
Aside from the references to where figures are from, I unfortunately do not have them. This overview was simply based on what I know - I do not know where I know each thing from, and digging up references for it would be equivalent to doing the work for writing a review article on the topic.
I'm the wrong person to ask. While I'm a bioinformatician and work with many types of proteomics data, I'm not an expert on the many technologies. So I cannot tell you which upcoming technologies are likely to be successful and which are not.
can someone explain what does the peak intensity mean? it is the number of ions we measure that have the same m/z ratio? How do we use this information? Also, does it relate with the term 'base peaks'?
Yes, pretty much. Peak intensity is not the number of ions itself, but it should be proportional to the abundance of ions at the m/z ratio. The base peak in a spectrum is simply the most intense peak, and peak intensities are thus commonly normalized so that the base peak intensity is 100%.
You summarised my entire semester of listening to droning lectures. I don't know why we don't have more effective teaching in schools. THIS WAS SO MUCH BETTER.
Thanks, that comment made my day! Sorry that you had to sit through those lectures, though. We've all been there and carry the scars 😉
"A mass spectrometre is nothing but a fancy scale" is definitely a quote I will remember :D
Miraculously, I managed to make this presentation without making my mass spectrometry colleagues hate me :-D
Terrific! Great summary of proteomic process. Very clear and easy to understand, even if you do not know much about MS-based proteomics.
Thank you so much! I'm happy it was worth the effort that made into making it.
Lovely 10 min course, a great introduction for students!
Thank you - it was a tough topic to try to cover in a short format!
This is a very great introduction for beginners in HRMS. Thank you.
You are very welcome, I'm glad you liked it!
Wow, great explanation. This has given me a general insight into Mass spectrometry.
Thank you! I'm always happy when people find my videos useful :-)
This was such a great overview, thank you so much!! 😊
Thank you, I'm glad you found it helpful. It was one of those topics that had me thinking "am I really the right person to cover this", but it has ended up being one of my most successful videos!
An excellent introduction and as you said it is a difficult one to fit in 10 mins and you did it.
Thanks, yes it was really an exercise in prioritization. I had to cut things like DDA vs. DIA as well as SWATH, both of which would have required major detours to fit in. They are probably topics that should be covered in a "deeper dive" presentation later.
This was really well done. Thank you, it actually helped me a great deal
Happy to hear - it was a really challenging topic to try to condense down like this!
Does the multiplex approach that you mentioned refers to the SWATH method ?
I was not thinking of SWATH, although SWATH is compatible with multiplexing (as far as I know). What I had in mind was labeling approaches such as iTRAQ and TMT, which allow you to multiplex 8 and 16 samples respectively.
Thank you for the excellent presentation Professor. I have a question if you could answer or link to another video of you would be greatful.
What are the different types of proteomics quantification methods?
1. Does it always LC-MSMS data analysis use peak area of XIC for quantification? Is isn’t possible to use peak intensity values?
2. In Label Free Quantification (LFQ / MaxQuant) what does it use ? What is the mechanism behind this?
I'm not completely sure what you mean. To do quantification you need to integrate the peak intensity, which in turn requires detecting where the peaks start and end. XIC is the most common peak detection algorithm as far as I know. I'm sure you can use other peak-detection algorithms than XIC, but I don't think you can avoid detecting peaks and integrating the area under them. Regarding LFQ in MaxQuant, the algorithm is called MaxLFQ - explaining it would take an entire paper (pubmed.ncbi.nlm.nih.gov/24942700/).
That was great! Thank you. But I dont know which Maxquant output should I use for DEP analysis. Which files?
It should be the proteinGroups.txt that contains the identified proteins (or rather protein groups) and the intensity for each of them in each sample. Those are the values you need as input for a statistical analysis to identify differentially expressed proteins.
@@larsjuhljensen Thank you 🌹🌹🙏
great video, thank you
hey! this is a great overeview, cn you share proper refeerences
Aside from the references to where figures are from, I unfortunately do not have them. This overview was simply based on what I know - I do not know where I know each thing from, and digging up references for it would be equivalent to doing the work for writing a review article on the topic.
What do you think of Quantum SI's approach? Will they become the leader in single molecule, protein sequencing?
I'm the wrong person to ask. While I'm a bioinformatician and work with many types of proteomics data, I'm not an expert on the many technologies. So I cannot tell you which upcoming technologies are likely to be successful and which are not.
can someone explain what does the peak intensity mean? it is the number of ions we measure that have the same m/z ratio? How do we use this information? Also, does it relate with the term 'base peaks'?
Yes, pretty much. Peak intensity is not the number of ions itself, but it should be proportional to the abundance of ions at the m/z ratio. The base peak in a spectrum is simply the most intense peak, and peak intensities are thus commonly normalized so that the base peak intensity is 100%.
good expression
cool chair
Thanks - it has attracted a lot of attention in both RUclips videos and Zoom meetings. It is the Varier Peel designed by Olav Eldøy.
Why are you reading. Can you just explain informally at a slow pace.
I’m not reading - I don’t have a teleprompter. But I intentionally keep it fast instead of making the videos longer than strictly necessary.