jcao89757 / tessa Goto Github PK

Hi @jcao89757 , thanks for the great package and all your efforts in maintaining it!

I ran the relined code： “python3 Tessa_main.py -tcr ./example_data/example_TCRmeta.csv -model ./BriseisEncoder/TrainedEncoder.h5 -embeding_vectors ./BriseisEncoder/Atchley_factors.csv -output_TCR test.csv -output_VJ testVJ.csv -output_log test.log -exp ./example_data/example_exp.csv -output_tessa /path/to/tessa_results/ -within_sample_networks FALSE”

and the error was as follows: “ERROR: please input valid TCRs/embedding.”

This code generates the embedded TCRs file （test.csv）, but the running results are inconsistent with your example results, as follows:

Thanks,
Ze Zhang

Hi Ze，

   The code can change the CDR3 sequences to a 30-d numerical vector. I want to know how to find each or some numerical vector corresponding amino acid sequence like Extended Data Fig.1 a decoder.

Thanks a lot
Ren

The gene expression value was scaled,log-transformed? How to obtain the suitable expression value for TESSA from UMI count?

Hi, Dear TESSA developers,it is a good idea for clusering single cell by joint TCR and RNA profile,,but Tessa takes too long to run，My guess is that this is caused by 1000 iterations of MCMC，So I would like to ask how the number of iterations affects the final result. Can I customize it?How much do you recommend?Thank you and I am looking forward to your reply.

The printout of TESSA is "cluster rate" and "b acceptance rate", but if I would like to get the cluster purity that you've mentioned in your paper, how can I get it? Thanks.

Hi Ze，

 Different lengths of CDR3 sequence can be solved by Tessa, a wonderful tool.  I have an Error when I used my data running TCR network construction. The error is as followd:

Initialization
[1] 123
Error in t[, !duplicated(cdr3), drop = F] :
(subscript) logical subscript too long
Calls: Tessa -> initialize
Execution halted

embeding.csv have accomplished, but I cannot find out where is the error from. Could you give me some advice? I can run to completion the example, but the version is not completely the same as you. I dont know whether this mistake is caused by version.

Thanks a lot.
Ren

what does node size represent in the figure generated from plot_Tessa_clusters? How to understand the figure?

Greetings, brilliant tool and really excited to implement this. I was wondering if there was any documentation on the Rdata output? Specifically, I am assuming that the tessa_results$dt contains the TCR distances for each network, but I am unclear on the structure of it.

For example, I would like to calculate the unexplained variance for some of my networks, which I think I can derive from this Rdata output, but I am just not sure how to get there without any explanation of the output structure.

Thanks so much for your time!

Greetings again! I have successfully run this analysis on ~30k T-cells without any problem. Now, I am attempting to run this analysis on a dataset of ~100k T-cells and I am receiving the following error:

Error in hclust(dist(t(t0))) : size cannot be NA nor exceed 65536
Calls: Tessa ... initialize -> initialize_cluster -> cutree -> nrow -> hclust
Execution halted

I did some testing and if I subset my data down to 100 cells this error does not arise. I then looked into the hclust function and it seems that it will not accept a distance matrix that has more than 65536 observations? Is my interpretation of this error correct? If it is correct, then I suppose that I will need to implement a different clustering function during this step?

Thanks for your help!

I want to train my data using the autoencoder ,In the script "encodeTCR_CNN.py", in the step: convert to 3D array it called:
cannot reshape array of size 11109250 into shape (120,5,1),
Could you please tell me why this error occurred?

Dear all,

I tried the Tessa tool and found in the post-analysis step, library ggplot2 is missed in function plot_tessaClsuters. This gives an error for R plotting. What's more, the error message 'ERROR: please input valid TCRs/embedding.' is confusing.

Best!

what does node size represent in the figure generated from plot_Tessa_clusters?

Hi, I'm fresh in sc-TCR related analysis, glad to see this new tool.
As I know, to decide a clonotype of one T cell, one ’TCRα + TCRβ pair‘ profile should be necessarily provided. But some sc-TCR analysis based on 10x genomics vdj technology which has much lower rate to detect TCRα have to use TCRβ only. I'm not sure about how many false-positives it may bring in. e.g. x50 copies of one TCRβ type are detected in two different tissues, could say these two tissues both have this kind of T cell, but if add TCRα result, might find that no 'α+β pair' are overlapped between them.
My question is that: have you thought about this issue, and would 'using TCRβ only' affect tessa method like correlation of TCR type x Tcell expression or sth. else ?