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Questions tagged [normalization]

The tricky art of scaling quantitative data across libraries, typically to account for differences in sequencing depth. This can also be about scaling for read source length, like transcript or gene length, in order to enable comparisons across genes.

2
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3answers
107 views

How to quantile normalization on RNA seq counts

I have a read count data (RNAseq) and want to perform quantile normalization. Could you please help me how to do it. I tried some scripts in R but it didn't work. I want the result output in matrix ...
1
vote
1answer
44 views

Calculating Z-score from logCPM values using edgeR

I have the raw counts for RNA-Seq data. I converted counts data to logCPM using edgeR package. Lets say I have a dataframe A with 15000 genes as rows and 100 ...
5
votes
1answer
69 views

How to normalise scRNASeq data for differential expression analysis

I wish to perform differential expression analysis for cluster-specific gene expression in single-cell data (with a tool such as MAST or SCDE). I have data for 3 biological replicates. I performed ...
3
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0answers
37 views

Why are TPMs per 10k or 100k in many scRNA-seq studies?

I noticed that many scRNA-seq papers normalize TPMs to 10k or 100k as opposed to 1M (as the abbreviation defines them). It doesn't really matter since you are just moving the decimal point, so why ...
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1answer
47 views

Convert TPM-normalized matrices back to UMI in python

I want to process a plenty of scRNAseq datasets in python, and I want to run TMM ...
2
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2answers
166 views

Input normalization in ChIP-seq

If I subtract input counts from ChIP counts (for every gene, since I have one peak per gene) I get negative values for most genes. This makes sense to me, because (as can be seen in the figure) input ...
2
votes
1answer
459 views

Normalize ATAC-seq/Dnase-seq sequencing reads coverage signals over estimated background

I'm trying to normalize the coverage signals of ATAC-seq reads against its own background using normal distribution, described in this paper It says: Finally, all open chromatin coverage ...
5
votes
1answer
227 views

Drawbacks of upper quartile normalization for scRNA-seq data

I would like to use Upper Quartile normalization for scRNA-seq data defined as: The upperquartile (UQ) was proposed by (Bullard et al. 2010). Here each column is divided by the 75% quantile of the ...
4
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1answer
216 views

Order of batch effects removal, data imputation and library size normalization in scRNA-seq data

I am preprocessing scRNA-seq data. What is the best practice in use to run both ComBat for batch effects removal, data imputation (to mitigate dropout) and library size normalization? I thought that ...
3
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1answer
176 views

Large dataset normalization for PCA

I need to normalize a large (400Mb) dataset for doing PCA analysis. I want to use scran for doing that: ...
5
votes
1answer
468 views

Normalizing RNAseq for PCA and CCA

Usually the expression data is transformed to log space using either RPKM, FPKM or CPM, this is required when looking for differential expression because the data is tested against the normal ...
4
votes
2answers
234 views

Normalizing microarray data for clustering heat map

I wanted to generate a clustering heat map for the microarray data. This is the first time I'm working on Microarray data. I read some tutorials but have few doubts. I'm using microarray (Affymetrix ...
6
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1answer
1k views

How to apply upperquartile normalization on RSEM expected counts?

I see that TCGA RNASeq V2 RSEM data is normalized with upper-quartile normalization. After doing Quantification with RSEM with the samples I have, I got "genes.results" as output which has gene id, ...
5
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0answers
278 views

Voom function from limma package and Normalization on counts data

I know that Voom function from limma package converts raw counts into log-CPM values and then Normalization is applied on that, with normalize.method argument. But I would like to know clearly how ...
4
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1answer
51 views

Analyzing Illumina Counts

I'm pretty new to all of this--forgive me if this is a simple question. When I download illumina counts from GEO (like the supplementary file in GSE89225). Can I do comparisons directly on that file?...
4
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2answers
1k views

RNAseq: Z score, Intensity, and Resources

I'm very new to bioinformatics in general, and I'm trying to understand some basic concepts. I have RNAseq data, and bioinformatics people tell me that intensities cannot be compared across patients. ...
3
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0answers
79 views

Minfi returning incorrect beta values

UPDATE: I found the solution. I was using normalized values and GEO was using raw beta values. I'm trying to link GEOquery and minfi. Specifically I want to obtain beta values from the idat files ...
3
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1answer
220 views

qPCR: Why is fold change and standard deviation calculated after transformation?

I am analyzing data from a quantitative polymerase chain reaction (qPCR) using R. After cleaning the raw data, it looks something like this: ...
11
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1answer
403 views

How to read and interpret a gene expression quantification file?

I have a gene expression quantification file from TCGA that contains the following lines: ...
5
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1answer
208 views

What are some good practices to follow during EPIC DNA methylation data analysis?

I recently got some EPIC DNA methylation data and I was wondering what are some good practices to follow? I am interested in knowing about normalization and differential analysis. Thank you.
13
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2answers
867 views

How can I extract normalized read count values from DESeq2 results?

The results obtained by running the results command from DESeq2 contain a "baseMean" column, which I assume is the mean across samples of the normalized counts for ...
15
votes
2answers
188 views

Confirm success or failure RNA-Seq normalization

I am working with a set of (bulk) RNA-Seq data collected across multiple runs, run at different times of the year. I have normalized my data using library size / quantile / RUV normalization, and ...
13
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2answers
1k views

Normalization methods with RNA-Seq ERCC spike in?

ERCC spike-in is a set of synthetic controls developed for RNA-Seq. I'm interested in using it to normalize my RNA-Seq samples. In particular, I'd like to use the spike-ins to remove technical bias ...