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.

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What is the difference between Normalized Expression in EdgeR vs DESeq2?

I am trying to access the normalized expression in both edgeR and DESeq2, yet the results are different. Does anyone know why? How to get normalized expression using edgeR: ...
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Normalization methods to combine scRNA-seq experiments with different sequencing depths

I am training a classifier to identify a cell type in a particular state of activity using scRNA-seq. There is a large variation in the sequencing depth (reads average per cell) of the testing data (...
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A question on Homer normalization

When using annotatePeaks.pl script from Homer software to create histograms, the output is normalized per bp per peak (on top of normalization to 10 million tags). What does it mean to normalize per ...
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What is the correct order of flooring-normalization-batch correction for microarrays?

This question was also asked on Biostars I am trying to learn and understand the correct order of data processing steps for microarrays. I have data which already was analyzed by a researcher using ...
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Normalization methods for single cell RNA sequencing that take read count into account

I have two RNA-seq datasets. One was sequenced at an average read count of 1.5 million per cell the other at 43K average reads per cell. For the first I also have the meta data from reads alligned ...
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What statistics can I use on qPCR data composed of several runs if all normality tests fail on the dataset?

I have >100 qPCR experiments that I'd like to analyze together, each containing the same set of genes (10 genes of interest and 2 reference genes). I have four different samples (untreated & 3 ...
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CITEseq different sequencing depth normalization -- Seurat

New technician ruined his first 10X CITEseq experiment on cells counting level and the ratio between replicates is 14k:2.2k:0.8k ncells. How should I now normalize protein data (ADT) from experiment ...
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How to perform a meta-analysis using data consisting of paired-end and single-end reads generated from Illumina and Ion Torrent?

So basically I have RNA-seq reads that were generated from Illumina and Ion Torrent platforms for yeast species. I have seen an article where they compared liver cells of a rat that were sequenced ...
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Calculating most abundant transcript from RNA-Seq data

vcf2maf uses VEP to annotate variants, and I believe selects the default Ensembl transcript to use for annotation. Sometimes the ...
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Problems about value log2(IP/Input) less than zero in ChIP-seq?

I have a question about the normalization for ChIP-seq. I used CPM to normalize my bam files of each IP and Input. Then I calculate the coverage of gene bodies for all genes on the genome. I have WT ...
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Normalize RNA seq data from multiple runs for expression analysis

I have RNA samples sequenced with TruSeq Stranded Total RNA kit protocol in Illumina HiSeq (2x125bp) and NovaSeq platforms (2x150bp) - almost 100 samples altogether. I have to use the samples data for ...
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Doubt about using TPM for statistics

We designed an experiment to explore the potential role of carbon dioxide on algae physiology using RNA-Seq. We analyse the differential gene expression using DESeq2 but now we are interested into ...
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Bulk RNA-Seq Read Length Normalization across different samples

I have 20 samples out of which 14 are 100 bp in length and 6 are 150 bp. Is there a way to normalize the read length for cross-sample differential expression comparison? What would be the best way to ...
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Differential expression analysis for a subset of transcripts

I want to check the differential expression of a specific class of transcripts (say, long non-coding RNAs) using DESeq2. Now, I know that the normalization step takes into account the total number of ...
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Why is there a minus in the 2ˆ(–delta delta CT) method (qPCR)

Question: Why is there a minus in the 2ˆ(–delta delta CT) formula? My line of thoughs: Consider Ct values of some pPCR ...
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GWAS phenotype data format and preprocessing

I have a set of different phenotypes which I want to use for a GWAS analysis (general linear model). I have a couple of questions and uncertainty about the phenotype data input. I have control and ...
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if I know the number of sequencing circles can I give this information to DESeq2?

I am trying to understand library normalization in DESeq2. I would like to ask the following: I know that some samples have been run 15 cycles and some others 20, can I give this information to DESeq2,...
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median normalization for proteomics

I am using the data from a proteomics study were the data was log2 transformed and then a median normalization was applied. The data was normalized by groups of conditions (normal, mutant), not for ...
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What is a good rule of thumb for the threshold of noise versus signal for RPK in RNA seq?

I have RPK values (RNA seq) and I'm wondering what is a good rule of thumb for what is considered to be noise versus what is considered to be signal? I.e what should I choose as a threshold value for ...
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scRNA-Seq: Account for sequencing depth and gene length?

Task: Normalize a single-cell RNA-Seq dataset to account for sequencing depth and gene-length. For UMI-count based protocols (like 10x) that don't suffer from gene-length biases, there are various ...
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How to create a list of differentially expressed (DE) genes after normalization with RUVSeq?

I am using edgeR to perform differential expression (DE) analysis on a set of RNA-seq data samples (2 controls; 8 treatments). To correct for batch effects, I am using RUVSeq. I am able to get a list ...
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What is a good RNA seq normalization method that allows for across sample comparisons and between transcripts

What is a good RNA seq normalization method that allows for across sample comparisons, and allows between transcripts comparisons as well? I read that TMM for example allows across sample comparisons ...
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Regarding RNA seq data analysis and building coexpression network

I have some questions regarding RNA seq analysis if you can suggest anything it will help me a lot. I am currently normalizing RNA seq data for comparing genes expression within and between samples. ...
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What unit (TPM, FPKM/RPKM, or other) to use when working across samples

I have raw gene read counts and would like to perform an analysis across multiple samples. I've found conflicting info online on how this should be done. One commonality however is that FPKM/RPKM ...
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apply TMM on counts imported from salmon using Tximeta

I used Tximeta to import a summarisedExperiment from the salmon output (used with genocide transcriptome v34). I need to produce 4 matrix of counts: - tx counts in TPM - gene counts in TPM - tx counts ...
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How are these definitions related to differential expression?

I have two groups of patients; for each patient I have an output file (RNA-seq) contains this information ...
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RNASeq: Normalization, stabilization, gene length and rlog

I was thinking about the best method for normalization, which takes gene length into account (in order to compare genes)... Do you think I can do that? : - taking raw counts and dividing each gene by ...
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Normal score transformation

This question is related to a normal score transformation which is performed in the paper by RUAN, Quansong, et al. Local similarity analysis reveals unique associations among marine bacterioplankton ...
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Should I use log2-CPM values (voom-limma) as input for my model?

We have created a model to integrate several OMICs data, but we realized that the maximum TPM values of RNA-Seq data were so big that had unexpected effects on our results. We hypothesized that this ...
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1 answer
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Is re-normalization of RNAseq data recommended for analysis of gene subsets?

I downloaded an RNAseq dataset from TCGA database in 3 formats: 1) HTSeq counts; 2) FPKM; 3) FPQM-upper quartile normalized. The complete dataset contains ~60,000 genes. All of my analysis will focus ...
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2 votes
1 answer
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RPGC normalisation creates artefacts at centromere

I am studying ChIP-Seq data in HeLa cells and I've started using the RPGC normalisation of deepTool's bamCoverage. MACS2 also uses this normalisation for its peak calling. I am seeing a large number ...
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Is it okay to use deeptools bamCompare (SES normalization) for comparisons across different ATAC-Seq datasets?

We are trying to use deeptools for analysis of ATAC Seq datasets. We have datasets with different sequencing depths and are wondering if bamCompare's SES based normalization is appropriate for ...
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In-sample and across samples normalized expression

I want to get the expression data that is in-sample normalized like FPKM and also across samples normalized as obtained using DESeq2 or else. What I am currently doing is that I first normalize the ...
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1 answer
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RNA-seq: How to get new expression count after normalization

I've RNA seq, Human, Paired-end data, Sample size is <40. These are aligned using STAR, RSEM processed. With RSEM I've TPM and expected counts, that is two files columns as individual IDs and row ...
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1 vote
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277 views

Normalization of single cell RNASeq data with ERCC spike-ins

I wish to normalize a scRNASeq dataset with respect to ERCC spike-ins, where "for some of the samples, ERCC spike-in RNA was added to the lysis buffer" and was wondering how to do so? I have seen ...
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Cluster is split in 2-3 locations on tsne plot - Suerat

I am running a single cell dataset (count data - exon) through Seurat. After running tsne I see a cluster (13) split in 3 different locations on the plot. Here are the commands I am running: ...
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What is the formula for Mg values in TMM normalization for RNA Seq data?

I am reading through the paper "A scaling normalization method for differential expression analysis of RNA-seq data" by Mark D Robinson, Alicia Oshlack, available here. In this paper they introduce a ...
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1 vote
1 answer
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Normalization of data with RPkM

I'm having difficulty normalizing my data. I was searching for transposable elements in my genome, and after this step, I made counts of reads in some transcripts. I produced something like this: <...
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How I normalize these two sets of data

I have average log fold change for a cluster of cells versus another cluster of cells by Seurat like below ...
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1 vote
1 answer
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Discordance in gene signature behavior between bulk and single-cell RNASeq

The objective of the following analysis is to identify an activation signature of a specific phenotype on bulk RNASeq and to apply it to single-cell RNA-Seq, in order to identify the population of ...
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3 votes
3 answers
323 views

Normalization for two bulk RNA-Seq samples to enable reliable fold-change estimation between genes

I have two bulk RNA-Seq samples, already tpm-normalized. I would like to know what is a reasonable normalization procedure to enable downstream log fold-change estimation. The distribution of the ...
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1 vote
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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 ...
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1 answer
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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 ...
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5 votes
1 answer
868 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 ...
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6 votes
2 answers
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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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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 ...
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3 votes
2 answers
1k 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 ...
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1 answer
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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 ...
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6 votes
1 answer
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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 ...
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6 votes
1 answer
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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 ...
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