User: Riba Michela

gravatar for Riba Michela
Riba Michela80
Reputation:
80
Status:
Trusted
Location:
Last seen:
2 years, 7 months ago
Joined:
5 years, 1 month ago
Email:
r***********@gmail.com

Posts by Riba Michela

<prev • 10 results • page 1 of 1 • next >
0
votes
3
answers
942
views
3
answers
Answer: A: leading edge analysis clusterProfiler DOSE custom GSEA
... Hi, I found this stating from the page you mention Leading edge analysis and core enriched genes Leading edge analysis reports Tags to indicate the percentage of genes contributing to the enrichment score, List to indicate where in the list the enrichment score is attained and Signal for enrichmen ...
written 2.6 years ago by Riba Michela80
0
votes
3
answers
942
views
3
answers
Answer: A: leading edge analysis clusterProfiler DOSE custom GSEA
... Oh sure, I have tried and as I told everything ok, consider the question is   how could I perform leading edge analysis using clusterprofiler? I tried the internal function just because I found the example gseDO in DOSE package, here: http://guangchuangyu.github.io/2016/05/news-of-my-bioc-packa ...
written 2.6 years ago by Riba Michela80
2
votes
3
answers
942
views
3
answers
leading edge analysis clusterProfiler DOSE custom GSEA
... Hi,   I’m writing about your very useful and complete packages for functional analysis. In particular I often use DOSE and clusterProfiler and ChipSeeker.   I’m writing about the possibility to perform leading edge analysis in GSEA. I found on your github page you have already developed this  ...
0
votes
1
answer
888
views
1
answers
Comment: C: Fwd: limma modeling, paired samples
... Thanks a lot for explanations I'm pleased to go into more detail following the mail and studying! Thanks a lot so much Michela ...
written 5.0 years ago by Riba Michela80 • updated 4.1 years ago by Gordon Smyth37k
0
votes
1
answer
888
views
1
answers
Comment: C: Fwd: limma modeling, paired samples
... Hi, thanks for your quick answer, I get the point, and basically I actually arrived to the conclusion of being absorbed in the Intercept, for this reason I went on and put 0+ in the model, in any case sure I'm not a statistician, and I cannot move on from this. I'm not at the moment convinced abo ...
written 5.0 years ago by Riba Michela80 • updated 4.1 years ago by Gordon Smyth37k
1
vote
1
answer
888
views
1
answer
limma modeling, paired samples: first disease type disappears from design matrix
... Hi, I'm writing again dealing with a paired sample design: the experimental setting involves 9 patients, 3 disease stages and microarray expression data according to the included target file target<- readTargets("targetPT.txt") head(target) Genotype <- factor(target$Genotype) Disease<- fa ...
limma limma design matrix written 5.0 years ago by Riba Michela80 • updated 4.1 years ago by Gordon Smyth37k
0
votes
2
answers
1.3k
views
2
answers
Comment: C: limma modeling, paired samples and continuous variable
... Hi Professor Gordon, thanks for you answer. I just want to add some observations: -about the factor I actually declared as a factor, but afterwards I used another : >> r<-target$Condition #this should be numeric where actually I returned back to the target file and extracted the column o ...
written 5.1 years ago by Riba Michela80
0
votes
2
answers
1.3k
views
2
answers
Comment: C: limma modeling, paired samples and continuous variable
... Hi, thanks a lot for your answer and I'm forwarding the covariate matrix of our design. target<- readTargets("targetPTpGSp.txt") head(target) Genotype <- factor(target$Genotype) Disease<- factor(target$Disease, levels=c("stageA", "stageB", "stageC")) # Condition <-factor(target$Con ...
written 5.1 years ago by Riba Michela80
0
votes
2
answers
1.3k
views
2
answers
Comment: C: limma modeling, paired samples and continuous variable
... Hi, thanks a lot for your kind answer. I have to specify an additional observation: the "r"parameter is indeed a numeric variable and also in this situation the result is the same. Would be reasonable to try and model the design as: design<- <- model.matrix(~0+r) #where "r"is a numeric variab ...
written 5.1 years ago by Riba Michela80
0
votes
0
answers
833
views
0
answers
CellMix package use with own data matrix
... Hi, I'd like to start using CellMix package. I have my own data matrix from expression profiling using microarrays. Is it possible to use them instead of GEO datasets to make calculation? Is it sufficient to convert the matrix into an expressionSet object? And how could it be converted into an Expr ...
convert written 5.2 years ago by Riba Michela80

Latest awards to Riba Michela

No awards yet. Soon to come :-)

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 16.09
Traffic: 402 users visited in the last hour