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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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1answer
47 views

Investigate the effect of street-light regime on insects

I need advice on a suitable analysis of a dataset that has an awkward design - because we investigate a real-world situation -we have two sites (A,B) where we can conduct the research. The hypothesis ...
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47 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 ...
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2answers
83 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 ...
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94 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 ...
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2answers
205 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 ...
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1answer
207 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 ...
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1answer
62 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: ...
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1answer
730 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 ...
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1answer
128 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 ...
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1answer
174 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 ...
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1answer
42 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: <...
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1answer
165 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) ...
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2answers
373 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 ...
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2answers
241 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 ...
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1answer
242 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 ...
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1answer
2k 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 ...
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371 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 ...