Closed zrf492174 closed 1 year ago
Hi @zrf492174, thank you for reporting this.
Looking at the essential tasks in Human-GEM, it appears to be about:
ID | DESCRIPTION | SHOULD FAIL | IN | IN LB | IN UB | OUT | OUT LB |
---|---|---|---|---|---|---|---|
IC | Glyceraldehyde 3-phosphate de novo synthesis | O2[e];glucose[e];Pi[e] | D-glyceraldehyde 3-phosphate[c] | 1 |
I couldn't find any metabolite changes in the recent versions that could cause issues, so then I wondered if there have been any changes to the tasks themselves. And bingo 🎯 there has been a change in the latest Human-GEM 1.16 from which Mouse-GEM 1.6 is derived:
@haowang-bioinfo, what would be the best fix? and how can this be avoided in the future?
@haowang-bioinfo, what would be the best fix? and how can this be avoided in the future?
before fixing, good to know what are the code and dependencies used? @zrf492174
Hi @zrf492174, thank you for reporting this.
Looking at the essential tasks in Human-GEM, it appears to be about:
ID DESCRIPTION SHOULD FAIL IN IN LB IN UB OUT OUT LB IC Glyceraldehyde 3-phosphate de novo synthesis O2[e];glucose[e];Pi[e] D-glyceraldehyde 3-phosphate[c] 1 I couldn't find any metabolite changes in the recent versions that could cause issues, so then I wondered if there have been any changes to the tasks themselves. And bingo 🎯 there has been a change in the latest Human-GEM 1.16 from which Mouse-GEM 1.6 is derived:
@haowang-bioinfo, what would be the best fix? and how can this be avoided in the future?
Thank you very much, I used the newest metabolicTasks_Essential file and it works. My results and function are as followed:
[metricsM, modelEssentialM] = evalGeneEssentialityPred(mouseGEM, expdataM, task)
expdataM is from the origin paper, mouseGEM and task are the newest version. metrics results are sensitivity: 0, specificity: 1, accuracy: 0.4872, F1: 0, MCC: NaN, p_hyper: 1 I think the reason may be the fun just detect 3 essential gene:'Dtymk', 'Guk1' and 'Tpk1', I wonder what did i do wrong
@haowang-bioinfo, what would be the best fix? and how can this be avoided in the future?
before fixing, good to know what are the code and dependencies used? @zrf492174
Thanks for your reply, the code and dependencies' version are as followed: raven toolbox version is 2.80 task file and evalGeneEssentialityPred code are from human-GEM repositories which version is 1.14 mouseGEM 1.16 gurobi solver 9.52
@zrf492174 thanks for providing the code and dependencies
then what's the error message when running evalGeneEssentialityPred
? or you just got NaN
for MCC value?
@zrf492174 thanks for providing the code and dependencies
then what's the error message when running
evalGeneEssentialityPred
? or you just gotNaN
for MCC value?
Before I used the newest task file, I got an error that 'Model failed task(s) before gene deletion!'. After using the latest one, the error disappeared and got NaN for MCC value. Is this normal?
I think it's normal to get NaN for MCC in your case.
if sensitivity = 0, specificity = 1, then TP = FP = 0. In other words TP + FP = 0, this would lead to infinity MCC, or Not a Number (NaN), given the formula below:
I think it's normal to get NaN for MCC in your case.
if sensitivity = 0, specificity = 1, then TP = FP = 0. In other words TP + FP = 0, this would lead to infinity MCC, or Not a Number (NaN), given the formula below:
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Thanks a lot, HaoWANG and Mihail. I think I understand the meaning of MCC and it runs well if using metabolic tasks after version 1.16 and GEM after version 1.6.
very good!
Hello, I am using the newest version of mouseGEM(1.16) to test if my steps is right,when calculate the Matthews correlation coefficient (MCC). I used the metabolicTasks_Essential and gene essentiality data set which the paper provided as inputs tothe funcation evalGeneEssentialityPred's, but I received an error-Could not find all outputs in "[IC] Glyceraldehyde 3-phosphate de novo synthesis". Do you know what is the problem?
Thanks in advance.
Runfeng