6 votes

Why did expression based subtypng of breast cancer gain much more acceptance than others

In two words: incidence and funding I'm not an expert on this topic, but I assume it has something to do with the incidence of breast cancer itself: Breast cancer is the most common cancer in ...
5 votes
Accepted

How to deal with duplicate genes having different expression values?

I assume you're familiar with the various issues surrounding FPKMs, so I'll not expound upon them. As a general rule, you should be using gene IDs rather than gene names, since the former are unique ...
  • 19.3k
4 votes

How to convert featureCounts to FPKM?

I have seen many posts regarding counts to RPKM and TPM. There’s your answer then: FPKM = RPKM. It’s simply a more accurate name. Speaking of RPKM for paired-end data is discouraged because the ...
4 votes
Accepted

How to quantile normalization on RNA seq counts

On google there are many tutorials about quantile normalzation, for example here. In that tutorial they made a function to calculate quantile normalization. Here an example with that function on your ...
  • 3,551
4 votes

Why the t-test for a specific gene shows different value compared to differential analysis?

There is no reason your t-test should reproduce edgeR. In fact, edgeR exists because t-test is inappropriate. edgeR does the tests by pooling information from all genes, because with the low number ...
  • 2,649
4 votes
Accepted

Inflated p-values in quantitative trait analysis

Permutation as suggested by @StupidWolf's comment is essential to understand what's going on. If permutation makes this pattern go away, then you have a problem with your model specification, there's ...
4 votes
Accepted

The biological meaning of the random variables and the responses in Seurat analysis

In the linked article the authors formalize microarray analysis as the study of the joint distributions of $\overrightarrow{X}_i$ and $Y_i$, where $\overrightarrow{X}_i$ is a vector of random ...
  • 3,221
3 votes

How to quantile normalization on RNA seq counts

Ma be CQN from Bioconductor will be useful, though it doesn't perform just quantile normalisation.
  • 321
3 votes
Accepted

Why the t-test for a specific gene shows different value compared to differential analysis?

The $log(CPM)$ of any low-moderately expressed gene will be negative. There is nothing unexpected there. Your statistics are inappropriate for a variety of reasons. Firstly, a CPM is not a robust ...
  • 19.3k
3 votes

How to deal with duplicate genes having different expression values?

The best way to deal with this is to use unique gene IDs, for example ensembl accession numbers. So use the ensemble gtf annotation when quantifying the read counts and not the gene symbols. Just to ...
  • 3,551
3 votes
Accepted

Where to download baseline/average gene expression level of all human coding genes?

There is not going to be a public database with this data. Apart from anything else, generating data for early human development is difficult and ethically tricky. Also, most people who care about ...
  • 3,221
3 votes
Accepted

Get Gene Expression Matrix from GEOquery

The answer to this really depends on the type of data you're retrieving from GEO. Microarray data sets should have a normalised matrix of expression values uploaded as part of the entry. ...
  • 861
3 votes
Accepted

Doing plot with this data

In general, survival analysis can be said to be composed of two steps; Cox regression, with which you calculate the "hazard ratio" based on your variables, and a "Kaplan-Meier (KM) estimate", which is ...
  • 3,477
3 votes
Accepted

Available phenotype data from GTEx

If helpful for anyone else, I found that all and much more are available. See below 2 links. https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/dataset.cgi?study_id=phs000424.v8.p2&phv=169091&...
3 votes
Accepted

How to downsample some of the samples in RNA-seq data?

You have a few options: Downsample the fastq files and rerun the entire analysis. You can do this with seqtk sample. Downsample the BAM files, which you can do ...
  • 19.3k
3 votes
Accepted

WGCNA co-expression network analysis with less than 20 samples

It's hard to say without knowing how different the subtypes are. If you do a common WGCNA, you may find modules related to the differences between A and B as well as to drivers of expression variation ...
3 votes

FPKM, FPKM-UQ, TPM or counts: How do I know which kind of unit should I use?

Type of data you need depends on the downstream applications and since you would like to carry out DEA with DESeq2, you would need raw counts (non-normalized). ...
  • 3,477
3 votes
Accepted

How to check if a given gene is expressed in a group of microarray samples if I do not have control group to compare with?

You ask about which "genes are expressed" and then you mention "if a gene is up or down regulated". These are different, and given your application I think what you actually want ...
3 votes

what are the nodes and edges values in gene regulatory networks?

This is an incomplete answer since it's not my field of expertise, but it sounds like Weighted correlation network analysis is what you are referring to. There is a paper which describes how it can be ...
  • 1,265
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 ...
  • 4,622
2 votes

How to convert featureCounts to FPKM?

You can use countToFPKM package. This package provides an easy to use function to convert the read count matrix into FPKM matrix; following the equation in The ...
2 votes

How can I interpret gene expression data from Bioconductor packages?

Processed microarray data is commonly represented as log_2(expression). This data transformation is used because the data more closely fit a normal distribution in log space. With such a ...
  • 11.9k
2 votes

residual Squared Coefficient of Variation (rCV²) vs Distance to Median (DM)

There has been a lot of work done on this problem already, particularly these two papers: https://www.biorxiv.org/content/10.1101/576827v2 https://www.biorxiv.org/content/10.1101/574574v1
  • 674
2 votes

Clustering of gene co-expression network by igraph R package

For the first part, do you mean that the file is too large to be run on your computer? For the second, if I understood correctly, you can use igraph or ...
  • 806
2 votes

How to extract gene expression tables from this GEO dataset?

Assuming that you have downloaded processed file, according to your link, it is either plain text (compressed) or GTF. If you would have plain text you probably would have posted a snapshot or sample ...
  • 203
2 votes

How to cluster the human genes by pathways/system-biology/metabolic properties?

To measure if two genes are functional similar I developed the BioCor package. It calculates a similarity score between genes by the measuring the amount of pathways shared. However, it doesn't take ...
  • 4,622
2 votes
Accepted

Any way to quantify the variation of genes that expressed in Affymetrix expression data?

You can use the following code to calculate the coefficient of variation: ...
  • 4,622
2 votes
Accepted

Why models of stochastic gene expression predict that intrinsic noise should increase as the amount of transcript decrease

Reading Kaufmann and van Oudenaarden (2007), it seems to validate the first alternative (using results from the Central Limit Theorem): Although biochemical fluctuations influence all stages of ...
  • 1,733

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