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6 votes

Is it possible to do this in R?

R supports logistic regression, which would seem to be the most efficient method for tackling this question. Assuming the "Chemo" variable is the type of chemo the code would be something like: <...
42-'s user avatar
  • 161
5 votes

Extracting p-values using corrr package in R

I would suggest looking at some of the documentation. As far as I can tell, the intention of the package is to visualize and organize correlation coefficient estimates. It does not seem that the ...
Maximilian Press's user avatar
4 votes
Accepted

Extracting genes from corrplot and adding labels based on high and low corelation

Here is a solution using the pheatmap library to cluster and visualise the correlation matrix, then extract the groups from the cluster dendrograms: ...
user3479780's user avatar
4 votes
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Spearman correlation between two genes

Since Spearman is a rank-based test, it relies on you being able to accurately decide on the ranking of your observations by some metric (usually the magnitude of the numbers). If two observations ...
sjcockell's user avatar
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4 votes

RNA-Seq data transformation prior to sample correlation analysis

You don't absolutely need to perform any further steps before calculating the correlation. However you would likely benefit from the following sort of workflow: Transform your data with vst() or ...
Devon Ryan's user avatar
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3 votes
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Power law distribution alpha values

It means the distribution is heavily skewed and has a 'long-tail', thus the variance is much greater than the mean. In other words most values are around zero, with a small number of values having ...
M__'s user avatar
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3 votes
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How to specifically select cluster on Featurescatter on Seurat?

You can use the cells argument to only display the data for a specific subset of cells. For example to extract the values for a cluster 2: ...
PPK's user avatar
  • 886
3 votes

Error in formation of correlation matrix-(corrupt matrix -- dims not not match length)

You can't compute a correlation matrix when you have more than ~46000 rows, since a standard R matrix can have a maximum of 2^31-1 values. Have a look at packages like bigcor. Alternatively, consider ...
Devon Ryan's user avatar
  • 19.6k
3 votes

Is it possible to do this in R?

The general approach would be to loop through every column starting at column 2. You can use numeric indexes to do that. For each column, check its type. If it is a factor, use your ...
Ram RS's user avatar
  • 2,425
2 votes

Why are my Chi-squared test results different from those in a published table?

Your calculations seem right, perhaps there was an error on their side. I also looked at the number of samples reported, but they use the same amount of samples in each case. Because they are ...
llrs's user avatar
  • 4,713
2 votes

Is it possible to do this in R?

You have category-based variables as well as variables based on continuous data. The best-option could be linear Mixed- effects model for your research purpose. Chi-square test and t-test may be used ...
Subhash C. Davar's user avatar
2 votes
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Different results of spearman correlation between TPM and FPKM

This shouldn't be surprising that you see different correlations between gene expression data when expressed in different units. To see why, let's look at how these units are defined. Let's denote the ...
James Hawley's user avatar
  • 1,384
2 votes

correlation coefficient versus DEGs analysis: what's the best approach for low expressed genes?

First of all, RNASeq is extremely sensitive to batch effects. Are these matched controls processed at the same time as the tumors? IF they are not, lots of your differences will be caused by batch ...
swbarnes2's user avatar
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2 votes
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How to get separate histograms plots on the basis of the column value?How to detect which plot has most deviation?

You could use the groupby() pandas function to group the dataframe by gene name. And then just loop through each group to plot the histogram of correlation values. I think you can use the mean of the ...
Steve's user avatar
  • 3,109
2 votes
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correlation between imputed genotype and true genotype

This is done by downsampling. Take the 1000 genomes, set some genotypes as missing ./., impute them using GLIMPSE, then measure correlation between the genotype ...
user438383's user avatar
  • 1,689
2 votes
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How to prove correlation between gene expression and functions using omics data in bioinformatics?

In general terms data mining is needed, then supervised learning and finally ODE, because you are performing DE against enzyme kinetics and thats doable, but you'll need a lot of biochemical knowledge....
M__'s user avatar
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1 vote

I am trying to find correlation between two ChIP-seq datasets but the Pearson and Spearman test results do not correspond with the peak overlap

Correlations like this between ChIP-seq datasets is common. If you're calculating the correlation between BAM files across the entire genome, those are largely going to be the same (hence the need for ...
James Hawley's user avatar
  • 1,384
1 vote

Generate a single column from two different columns in the same format

I think this should be fairly straightforward: ...
user324810's user avatar
  • 1,125
1 vote

Extracting p-values using corrr package in R

Here is a suggested workaround: Generate a p-value table using one of these tools: RcmdrMisc::rcorr.adjust() psych::corr.test()...
Tripartio's user avatar
  • 111
1 vote
Accepted

gene-gene correlation from two different Tissues

You can use mapply(). ta and tb being transposed data frames of your ...
haci's user avatar
  • 4,162
1 vote

How to calculate module-trait relationship when trait data is in binary format?

Answer from @m, converted from comment: Personally I'd build a tree. Whats your question patients or the relationship between RNAseq 'signatures'? Its not the definitive analysis, but its good mining. ...
1 vote
Accepted

How to remove zero value of gene on FeatureScatter plot using Seurat?

It will not improve your correlation most likely, unless the zeros are not missing at random: ...
StupidWolf's user avatar
  • 1,688
1 vote

How to analyze co-occurrence of multiple SNPs?

I found the LDheatmap package in R very helpful at calculating linkage disequilibrium. You can make plots such as this:
CephBirk's user avatar
  • 151
1 vote

Identifying mutually **exclusive** gene sets

"Mutually exclusive" is not a precise statistical term because it could be seen as independence. Anyway if truly mutually exclusive AND their behaviour follows periodicity, i.e. sine waves, which it ...
M__'s user avatar
  • 12.6k
1 vote

How to exclude the repetition of gene-gene correlation calculation in python?

Actually I found an easy and efficient way. ...
Elyas Mohammadi's user avatar
1 vote

How to exclude the repetition of gene-gene correlation calculation in python?

You don't need g2 to go from 0 to din.index, just from 0 ...
Ram RS's user avatar
  • 2,425
1 vote
Accepted

correlation between transposon and gene

Ok I think I roughly get what you want to get. Below I simulate something that's like your data because you provided two identical matrices. ...
StupidWolf's user avatar
  • 1,688
1 vote

Metagenomic shotgun data with internal control

The problem with correlations in relative scale is know on the literature, it has been suggested to change to other metrics. So I wouldn't use it for internal control. As you can see on figure 3 of ...
llrs's user avatar
  • 4,713
1 vote
Accepted

Correlate DEGs from DESeq2, EdgeR and Limma results

I would use the p-value/FDR which each method returns to rank the gene list for that method in order from 'most likely to be DE' to least likely. You would then have three ranked lists of genes - you ...
Jay Moore's user avatar
  • 1,012
1 vote

Multiple correlation with R

Like haci mentioned, you can use the apply family of functions to loop over all your columns. ...
Ashley Xavier's user avatar

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