TCGA Biomarkers Identification using Machine Learning | Complete Walkthrough

[@Muuip]

Great presentation! Much appreciated!👍

[@rk956]

Thanks again for previous help! One question I'm having issue with. I used legacy data, so the GDCprepare function did not work for my query. I was able to design a workaround where I created a count matrix manually, with the metadata in a separate table. How would I go about assigning training labels to data that's not in SummarizedExperiment format? I.e. how would I replicated the below code by using two separate data frames - one for expression data and another for metadata: train_label % as.numeric () train_label

[@rk956]

please let me know if you have any guidance!

[@mangalahegde3805]

Hi, Thank you so much. This is really helpful

[@salma-amlas]

great video

[@md.ishtiakrashid1523]

I was wondering if this could be used in case of 16S amplicon sequencing data. Could you please enlighten me?

[@LiquidBrain]

Yeap, it can, but how useful the outcome is, it going to be strongly dependent on your interpretation

[@user-vn9gp9le1x]

Hi I'm having a hard time understanding about finding goi. Can you tell me about the theory of finding good nodes (gene of interst) by summing total weight and bias?

[@LiquidBrain]

It's not really a great example how it can be used, but a higher Weight and bias signifies the gene expression is being considered as part of the data for the classification process. Even a lowly expressed gene can get a high activation value if they are being multiplied with a big number

[@anthonyimhenkuomon1293]

Hi, This is absolutely a great video!! Please, I did not understand your explanation in code line 70: about removing "Metastatic". I am doing similar ML project with "TCGA-BLCA" i.e Bladder cancer but not with ANN. my sample group is "Primary Tumor ,Solid Tissue Normal". I was thinking of how to implement code line 70, but, I actually don't get it. could you brief me in line with my Project? regards,

[@GajulaShivaChaitanyaCS16M016]

because you might not have "Metastatic" in your data, so check for unique values and eliminate which is not necessary. unique(sedf@colData@listData$sample_type) will give you unique values in the sample, instead of Metastatic, you could remove which ever type you wish to remove.

[@LINAMEZIANE-dr6dd]

can you share with me your github for this project?

[@Muuip]

Time series on binomial outcomes!? Ex.: gene expression comparison by death versus survival over 30 days!? 🤔

[@RanjeetSingh-xw7lr]

Hi there! Awesome video - super cool stuff! I ran the code dge

[@rutchristine6554]

hi I tried your code especially for PCA visualization but my graph would not show. It says table of extent 0>. How do I solve this? I am totally new in r. Thank you

[@LiquidBrain]

Hmm, can you show me what's the code that you run when you get the error? And is your input matrix containing all numbers (no alphabet)?

[@ishas.7508]

I am facing the same issue....what can be done?

[@ishas.7508]

! Problem while converting geom to grob. ℹ Error occurred in the 1st layer. this is the error for PCA

[@MadihaHameedAwan]

you did not tel me how to select project id because manifest file downloading is tricky you firs need to tel that