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Questions tagged [pca]

Principal Components Analysis. A statistical method used to reduce the dimensionality of a dataset while keeping as much variance in the first principal components as possible. It can be used to visualise samples with many variables in 2-D or 3-D, thus allowing for a visual non-supervised grouping of points.

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What does PCA mean on GWAS

I understand what GWAS is and I'm able to perform certain tests with the p-values, etc. But what I am having a hard time wrapping my head around is what PCA on GWAS means. So let's say I have 100,000 ...
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How are Principal Component analyses and Admixture analyses from a genetic alignment different?

How are Principal Component analyses and Admixture analyses from a genetic alignment different? My understanding is that a PCA will take raw genetic differences across the entire alignment and plot ...
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How to interpret PCA output statistically and biologically?

How can I interpret the PCA results statistically for biological data? I have used FactoMineR and factoextra libraries for PCA Scripts used: library(FactoMineR) ...
Dendrobium's user avatar
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1 answer
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Should PCA be standardized for gene expression?

This is a theory/good practice question more than a technical one. If samples are being plotted on a PCA projection of gene expression data, I'm wondering whether it is standard (and if so, why) to ...
Felipe Flores's user avatar
4 votes
2 answers
543 views

PCA on genotype matrix with multiple alleles

Consider an m x n genotype matrix of m haploid samples and n SNPs where each value is an allele encoded by an integer (0,1,2,3). Is there a good/standard way to encode the alleles in order to ...
cmdoret's user avatar
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Understanding PCHeatmap outputs

I am currently trying to understand the purpose of these PCHeatmaps - part of the seurat package in R: All the online documentation I have searched for has only ...
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Question about umap using different numbers of pca components as initialization

I am new to the scRNA-seq field and I have been doing some experiments of visualization of UMAP using different numbers of PCA components for initialization. The process involves projecting scRNA-seq ...
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PCA plot shows big difference but not many differentially expressed genes are found

I got a PCA plot of bulk RNA-seq experiment that looks the following way: It was generated by the following code: ...
Nikita Vlasenko's user avatar
3 votes
1 answer
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3D PCA group labelling

I would like to make a 3D PCA but not sure how to label group wise which i can do for 2D PCA ...
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Should be RT-qPCR values standardized before PCA analysis?

I come from this question of gene exression analysis: Should PCA be standardized for gene expression? My experiment is based in 151 x 51 (individuals/samples x genes), in which, patients are subjected ...
Javier Hernando's user avatar
2 votes
2 answers
66 views

WCGNA - Relate modules with Y features when the % of variance explained of each eigengen is low

I'm doing a WCGNA analysis (signed network) on microbiome 16S data. I have transformed counts to centeres log-ratio transformed data (CLR) to address the compositional characteristics of the data and ...
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How to perform PCA on proteomic data set

I'm trying to perform Principal Component Analysis using R on a proteomics dataset. As the dataset contains a lot missing values I tried different approaches. I ran PCA using ...
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Using Multi-Dimensional Scaling (MDS) to produce a vector in order to account for patient bias when constructing DGE lists from RNA-seq datasets in R?

I am currently working on my PhD and as part of my thesis, I intend to analyse gene expression within multiple sclerosis (MS) lesions by looking at RNA-seq datasets on Gene Expression Omnibus (https://...
R_Cres_01's user avatar
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PCA of methylation-values normalized by coverage

I have started analyzing methylation (EM-seq) data for the first time ~0.8M positions. In this data set I have 27 samples of 20 patients. I want to perform a PCA of the dataset to check for possible ...
llrs's user avatar
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483 views

Filter out PCA outliers automatically

I am new to bioinformatics and PCA. What I am trying to do is to remove bad cells from a dataset that was obtained with scRNA-seq for ...
Nikita Vlasenko's user avatar
1 vote
3 answers
390 views

Performing PCA for the samples and for the genes

I have 10 samples from a RNAseq experiment (5 control, 5 disease), I have performed a cluster analysis for the samples and for the genes (4000 genes aprox) to see how they cluster (to see which ...
Mee's user avatar
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2 answers
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PCA plot in R coloured by sample type

I'm a biologist, not a programmer so please be gentle. So I have a dataset that looks like ...
Athon's user avatar
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3 answers
771 views

Explanation for RNA-seq samples not clustering in PCA as expected

A colleague is analysing RNA-seq data - the study design is 2 treatments, 3 replicates, 3 tissues. In their PCA plot the samples clustered neatly by tissue. Except for two samples - two tissue samples ...
user260878's user avatar
1 vote
1 answer
795 views

What is a sensible number of gene/observations to explain PCA variance?

I am working with a set of RNASeq dataset. I have about 4000 observations (genes) on 20 samples and plotting a PCA I found the clustering doesn't vary much when I use different number of genes, but ...
Ecg's user avatar
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1 answer
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Using external list of PCs for clustering

I am going to use principal components (PCs) comes from calcPCA function in URD program for clustering my cells in Seurat; So ...
Zizogolu's user avatar
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1 vote
2 answers
60 views

Predict population based on PC coordinates

Utilizing a reference panel, I want to assign most likely population label to each individual in the study. Following are the files I have: Reference panel population labels: ...
user2998764's user avatar
1 vote
1 answer
54 views

Test for differences between groups of samples

Sorry if the answer to this should be obvious. I have RNA-expression results from 24 samples which can be divided into 6 groups, (wildtype and two different mutants at two different ages) with a total ...
Sethzard's user avatar
1 vote
3 answers
2k views

RNAseq biological replicates not clustering in PCA plots

I have RNAseq data from 4 samples with 3 biological replicates per sample. I am currently trying to do the differential expression analysis with DESeq2 but the biological replicates will not cluster ...
nmp116's user avatar
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1 vote
1 answer
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Error in annotating row names as data points in a PCA plot

I made a PCA plot and was trying to plot the eigenvenctors in R so that each data point is actually the sample name. All the samples are in column 1. The following are the R commands I am using: <...
user2887's user avatar
1 vote
1 answer
765 views

Hierarchial PCA Clustering with duplicated row names

I have a matrix object in R of 1500 rows and 20 columns. Based on my own algorithm of analysis, I know there are roughly 7 clusters. In my matrix object, each row is one data point, and is labeled to ...
rishi's user avatar
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1 answer
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PCA analysis of samples in a phylogenetic tree

I have a phylogenetic tree. Each branch ends have samples (s1, s2, ~ s16). What I want to do is, I want to make PCA analysis plot for each sample. First I thought each sample has each lineage (...
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1 answer
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Biology behind PCA analysis based on SNP

What is the biology behind SNP based PCA analysis to study population structure? I am reading some articles where they used PCA analysis to compare isolates of drosophila that is collected from a ...
Ashar's user avatar
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1 vote
1 answer
194 views

data visualization RNAseq : scaling data for PCA and cluster dendogram

I have count data from a RNAseq experiment (2 samples are from normal cells and 3 samples are cells with a disease), and the data is already standardized by trimmed mean of M values (TMM). I want to ...
Mee's user avatar
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1 vote
1 answer
108 views

How to identify latent variables in single-cell RNA-Seq data

I have a single-cell RNASeq sample, in which I'd like to identify latent variables (e.g. response to stress) that I think might be affecting the clustering. The approach I was planning to use is to ...
gc5's user avatar
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1 vote
3 answers
146 views

K means clustering, would PCA be a better option?

I have the data below. I need to use a clustering method to classify them and into categories of "Heterozygotote, Allele 1, Allele 2 and No Call. The values in RFU1 and RFU2 are used to determine the ...
Jordan Browne's user avatar
1 vote
1 answer
1k views

Illustrate a 3D visualisation of the three main PCs using plot3d() package in R?

I have a dataset (view/download) here. I need to run PCA on this data set and need to illustrate a 3D visualisation of the three main PCs using plot3d() package. I have looked for more information ...
stackdon's user avatar
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0 answers
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Project PLINK eigenvector from one group on top of another group

I have 1 .bcf file called with individuals from two groups, one which is my samples, another which is a reference panel. Due to my samples having a limited amount ...
RAHenriksen's user avatar
1 vote
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46 views

What is the best approach to do a PCA analysis to distinguish between two groups?

I have two samples A and B and I do have an RNAseq for both of them. Inside each file (for A and B) I do have a set of FPKMs that give me a fold change for each gene (sample vs control). It looks ...
Lara's user avatar
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1 vote
0 answers
151 views

Clustering individuals by gene presence/absence

I have a binary matrix with individuals as row names, and gene name as column name. So, if the gene is present in an individual, we have 1, otherwise 0. I would like to cluster individuals based on ...
Marco's user avatar
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101 views

PCA analysis and nucleotide diversity pi

I have 25 individuals' whole-genome sequence (collected from 5 different locations) and after doing a variant calling analysis, I found 2734 SNP+INDELS marker (SNPs + INDELS = 2734 ). Then I plotted ...
Ashar's user avatar
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1 vote
0 answers
206 views

PCA on large sparse matrix of single cell RNA-seq

I received a large sc-RNA-seq data matrix, as of the nature of sc-RNA-seq compared to bulk-RNA-seq the data matrix is very sparse. Moreover, due to the fact that this is single cell data the cell ...
David's user avatar
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0 votes
2 answers
679 views

Interpreting this PCA plot for RNA-seq

I have RNA-seq from two sequencing batches; Lab technician says that he has run the RNA expression quantification two times in bathes 1 and 2 for example ...
Zizogolu's user avatar
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0 votes
2 answers
433 views

Pre-filtering genes for Principal Component Analysis

I have a raw counts data-set of 20,502 genes and 137 samples. I want to find out Principal Components which best explain variation between samples in different stages of tumor. I am new to Machine ...
Pawan Verma's user avatar
0 votes
1 answer
101 views

Is this RNA seq data good based on the MDS plot

I am analyzing some RNA sequencing data from a collaborator where the effect of some ligands on the transcriptome is being looked at. I am using DESeq2 for my analysis. I am looking to compare each of ...
siddhartha das's user avatar
0 votes
2 answers
328 views

Help with performing PCA analysis on data from 3 different datasets of normalized counts data for RNA-seq experiment

So, I have limited knowledge of R but I need to do a PCA analysis of 3 different datasets of gene expression as a result of combined growth or mono-culture growth. The 3 different datasets I performed ...
Justin1609's user avatar
0 votes
1 answer
3k views

Perplexity is too large

I am trying to run {Rtsne}. On pca dataset prepared by using dudi.pca from {ade4}. For pca calculation I selected 40 components ...
Nikita Vlasenko's user avatar
0 votes
1 answer
87 views

the variation between treatments is less than the variation between replicates in RNA-seq data

I have a set of RNA-seq samples from targeting different proteins in a complex with siRNAs. However, the ...
Reza Rezaei's user avatar
0 votes
0 answers
9 views

Done miRNA sequencing from animal tissue & have 1 control sample in duplicates 1 treatment group as test. In PCA plot clustering is not there

I have done miRNA sequencing from animal tissue and have control sample in duplicates . Like wise one treatment group as test. In PCA plot clustering is not there. There is very randomness. Is it ...
M Javed's user avatar
0 votes
1 answer
94 views

scRNA: What are good dimensionality reduction/clustering parameters to get biologically plausible groupings?

I've got a moderately large set of PBMCs, over 1M cells. That means I can't easily do a grid search of dimensionality reduction/clustering parameters/methods. Some examples results I'm getting with ...
Henry Gong's user avatar
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0 answers
39 views

Is SNPRelate the goto package for PCA of SNP data in R?

I'm trying to evaluate a method that I'm not familiar with. They used SNPRelate. I'm wondering if this is the best / only choice... what other tools would you recommend? Many thanks,
Dan Bolser's user avatar
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0 answers
25 views

about rescaled data (median) [duplicate]

When we have a rescaled data with median (divided by median value)(e.g.,metabolome) and perform natural log transformation, do we need to use autoscaling again to perform PCA or to compute euclidian ...
user224050's user avatar
0 votes
0 answers
245 views

Selecting genes with more contribution from PCA

I have RNA-seq data in response to treatment vs non response; By machine learning I selected three principle components likely can predict the response based on the gene expression. Now I have ...
Zizogolu's user avatar
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