Video

Sure send me tha photos so I can check

Sure send me the email

@@bioinfotips I do not find your Email.😅

My bad. I thought you had sent a previous one: bioinfotips@gmail.com

No problem :) Glad I could help! :)

Glad I could help 😁

My bad. Just saw your email. I will send it to you now.

@@bioinfotips I am also having trouble with this, It seems the website migrated and it is hard to find the file.

@@gabrielbaldissera7453 Send me an email to bioinfotips@gmail.com and I'll send it to you

Thank you. Glad I could help!

Glad I could help! Your comment means a lot!

Let me check if I still have it

@@bioinfotips you’ll be a life saver

Send me an email do bioinfotips@gmail.com and i'll send it to you

How so? You mean the histogram for the transformed data?

​@@bioinfotips the same question

If I understood the question, just plot the histogram of the transformed data.

Hi Kam. You need to have 2 separate graphpad datasheets, analyse them separately, and then, make the graph as in the video.

Do you have images Fiji? I'm pretty sure I did not had to install anything in mine.

@@bioinfotips ok. Actually I had image j. Would you kindly explain how to calculate the staining intensity not the percentage area.

Sure. Basically, you do the same thing but on the "measurements" menu, go to "set measurements" and make sure the "intesnsity" ones are checked

Hi Juan. You mean like expansion of the spheroids? If that's the case, probably measuring the area before and after the cell migration should do it.

Have you tried any of the other transformations? Like log?

Ahaha thank you so much. Glad I could help you

No problem 😁 hope you have fantastic results!

Hi. Thank you. You mean the pixel density?

@@bioinfotips I'm working with cells overexpressed with a certain protein which makes them cluster more than the control cells. From visual interpretation I can tell my protein of interest is resulting in a higher cell-cell adhesion. So my question is, how do I quantify that? The control cells have many blank spaces in between which the mutant doesn't have

In that case, I think you can try to measure the area of the sferoid with the wand tool, so it quantifies all the continuous area, after thresholding the image. Just make sure you use the same threshold value for every image. Let me know if that works.

@@bioinfotips thanks!! This helps. Got what I wanted and glad to see my hypothesis is working. Have a great day ahead!

Hi :) what do you mean by non constant?

The ratio of two drugs is non constan

How so? Can you leave a print screen or send it to bioinfotips@gmail.com?

You welcome 😁

When you do the analysis it automatically plots a graph for you in the graphs section. Check it and let me know if you found it.

I didn't check it but I believe you can do it in the analysis menu and crosstabs statistics.

Hi Rob 😁 check this video from the channel: czcams.com/video/hyLGYO7XV_w/video.html Let me know if that helps.

You welcome. Thank you for your question. However, I don't see a scenario where that happens... Can you send a print screen?

Glad I could helpt! That means a lot to me 😁

Hi :). In that case, I would recommend you to separate analysis just for girls, using maybe a ANOVA, depending on if you want to count the number of girls who have mint as the favorite flavor or if you ask to rank the flavours

You can get it here imagej.net/software/fiji/downloads

Sorry for taking so long to reply. In GraphPad Prism, IC50 determination involves fitting a dose-response curve to your experimental data to determine the concentration of a compound that inhibits a particular biological process by 50%. The number of parameters used in the IC50 determination depends on the model you choose to fit your data. Three-parameter model: This model assumes a sigmoidal dose-response curve with three parameters: the bottom plateau (representing the response at infinite inhibitor concentration), the top plateau (representing the response at zero inhibitor concentration), and the IC50 value (the concentration at which the response is halfway between the top and bottom plateaus). This model is simpler and more commonly used when you have limited data points or when the curve doesn't exhibit significant asymmetry. Four-parameter model: This model includes an additional parameter, the slope factor (Hill slope), which allows for asymmetry in the dose-response curve. The slope factor represents the steepness of the curve around the IC50 value. This model is more flexible and suitable for data that show significant asymmetry or curvature. When to use each model: Three-parameter model: Use this model when your data follow a standard sigmoidal dose-response curve without significant asymmetry or curvature. This model is simpler and requires fewer data points for reliable fitting. It's a good choice for initial analysis or when the additional complexity of the four-parameter model isn't justified by the data. Four-parameter model: Choose this model when your data exhibit significant asymmetry, curvature, or when you need a more flexible model to accurately capture the dose-response relationship. The four-parameter model provides a more accurate estimation of the IC50 value when the dose-response curve deviates from a simple sigmoidal shape. In summary, start with the three-parameter model for simplicity and use the four-parameter model when your data require a more flexible and accurate fitting approach.

Hi. The best option for you is to create a spreadsheet by columns with the a,b and c groups. Then perform a ANOVA with multiple comparisons (compare the mean of each group with the mean of every group), if it's normally distributed, or kruskall-walls if it's not normally distributed. And finally plot it as in this video. But search on channel. There is a video about that.

@@bioinfotips thank you so much!!!! it really helped me a lot!!!

Glad I could help you 😁

Thank you for your comment Sebastian. I'll keep that in mind for the next videos 😁

Hi :) if you want, I have a fiverr profile, contact me there and maybe we can schedule a zoom meeting. www.fiverr.com/joaomaia7?up_rollout=true

Hi and thank you for your comment. Let me check if I can find it.

Thank you and anticipating your response@@bioinfotips

may it help ibtjbs.ilmauniversity.edu.pk/journal/jbs/14.1/9.pdf

@@bioinfotips hello, did you have any reference please?

Hi, I'll leave the 2 papers from where I learned it from: www.jstor.org/stable/2984418 www.jstor.org/stable/2348250

Glad it was useful :)

After minute czcams.com/video/H5cj2wBT59A/video.html, it measures the number of particles (in this case). However, In the spheroid case, you are only interested in the area of the main "particle" which is the spheroid itself. Alternatively just copy the total area in the summary of results window.

Glad it was helpful to you nick!

Try to add a threshold adjustment step the particle measurement.

thanks!

Yes. I believe they have the instructions in the website. If you want you can mention them in the acknowledgments or something like that

@@bioinfotips Thank you for your kind response!

No problem

Muito obrigado Humberto!

Hi Nerea, let me check and I'll let you know

Just made this video about it czcams.com/video/TUnu3wNxQmc/video.html

Setting the scale you mean? You need to take a picture of your cells with a scale bar on it.

Hi Bianca. Thank you for your question. Let me check and I'll let you know.

What is the value on that row before the transformation? If there are zero or negative values, these can cause issues during the transformation, resulting in missing values.

The value is positive, same as yours. If you look at your example, the one in the video, you'll see that in row 9, you don't have a number after you did the transformation. I was thinking that maybe it has something to do with the fact that is the highest value of all, but I don't get why the program "deletes" that value.

Oh my bad. I though you were talking about your data. Let me check and I'll let you know.

@@bioinfotips i am curious about this too

Hi. What do you mean?

Cut off value can be calculated bythe highest Youden's index= sensitivity + specificity - 1

Thank you for your request. I'll take a look into it and make a video.

Thank you so much! It means a lot. It really depends on the scale you are using but it should be micrometers

Should I set the scale before doing the analysis? Or can I accept it directly as a micrometer?@@bioinfotips

Yes set the scale before doing the analysis.

Thank you so much!@@bioinfotips

Hi. Depending on the degree of skewness, I would say square root transformation (for moderate skewness) or log10 transformation (for higher degree of skewness). Let me know if it helped.

I already tried the sqrt and log method ...but still not getting the normality in the data

In that case, why don't you use non parametric analysis?

Hi and thank you for your comment. I'll try to make the next video about it.

Hi jennifer. What do you mean by "leave test"?

Thank you for your comment. Glad I could help 😃

In that scenario I would recommend other type of normalization according to the type of skewness you have.

Thank you, is there a guide you might recommend that suggests the type of transformation to make?

Thank you for your feedback. I'll take that into account on the next videos.

Thank you! I will do a video showing how to do it.

@bioinfotips will be waiting for that. In Graphpad, please.

Don't worry i'll be doing it on Graphpad

There you go czcams.com/video/MjK3BQdHNak/video.html