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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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1 answer
99 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 ...
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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 ...
3 votes
1 answer
137 views

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 ...
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: ...
2 votes
0 answers
303 views

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 ...
4 votes
2 answers
240 views

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 ...
5 votes
2 answers
2k views

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 ...
1 vote
0 answers
44 views

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 ...
1 vote
1 answer
56 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 ...
1 vote
0 answers
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 ...
2 votes
0 answers
47 views

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://...
2 votes
0 answers
49 views

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 ...
1 vote
3 answers
780 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 ...
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 ...
1 vote
0 answers
154 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 ...
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 ...
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 ...
1 vote
1 answer
172 views

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 (...
0 votes
1 answer
102 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 ...
1 vote
0 answers
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 ...
1 vote
2 answers
3k views

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 ...
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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,
1 vote
1 answer
239 views

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 ...
1 vote
1 answer
814 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 ...
1 vote
3 answers
395 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 ...
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 ...
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 ...
0 votes
2 answers
434 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 ...
0 votes
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 ...
3 votes
1 answer
763 views

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: ...
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 ...
1 vote
3 answers
147 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 ...
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 ...
0 votes
0 answers
246 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 ...
0 votes
2 answers
680 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 ...
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 ...
4 votes
1 answer
2k views

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 ...
3 votes
1 answer
3k views

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 ...
1 vote
1 answer
738 views

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 ...
5 votes
1 answer
791 views

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 ...
1 vote
1 answer
77 views

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: <...
5 votes
1 answer
491 views

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) ...
5 votes
2 answers
1k views

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 ...
4 votes
2 answers
544 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 ...
1 vote
1 answer
766 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 ...
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 ...
2 votes
0 answers
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 ...