13 votes
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Using the t-SNE algorithm on microarray data + an error bonus

Converting your data.frame to a matrix (and then removing the data.frame) will often free up ...
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6 votes
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How to obtain clusters of hierarchical heatmap when using Python?

Clustering like this is typically done with scipy. Here's the code we use in deepTools (original context here): ...
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  • 19.2k
6 votes
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validating identified sub-populations of cells in scRNA-seq

A SC3, single-cell consensus clustering, approach could be helpful here. It aims at achieving "high accuracy and robustness by combining multiple clustering solutions through a consensus approach" ...
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  • 481
5 votes
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Is removing samples based on clustering for downstream analysis a right choice?

I would be very hesitant to blindly exclude those samples based on the clustering. Check to see if the clusters actually denote some sort of batch effect, since it's not like all of the TCGA datasets ...
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  • 19.2k
5 votes
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How to scale the size of heat map and row names font size?

heatmap.2 is very configurable, and has options to adjust the things you want to fix: cexRow: changes the size of the row label ...
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  • 861
5 votes
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Are phylogenetic tree construction algorithms any different than general clustering algorithms?

The goal of a phylogeny is to estimate the "expected" number of mutations between all taxa in the analysis and their hypothetical common ancestors. A cluster-analysis will only identify the "observed" ...
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  • 7,284
4 votes

Are phylogenetic tree construction algorithms any different than general clustering algorithms?

A great question, though a little ambiguous. I don't know what "general clustering algorithms" refer to. For biological sequences, building a tree can be thought as a way of clustering. Anyway... ...
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  • 5,735
4 votes

Getting hierarchy of cell populations with Drop-seq data

This article uses the freely available R package dropbead for filtering and then Seurat to perform a principal component analysis that groups together affine transcriptomes. It could be what you are ...
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3 votes
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Using external list of PCs for clustering

There is a way to do this, and even better--there is documentation for how to do it! No surprise coming from the Satija Lab. In the vignette they perform multidimensional scaling, but the idea is the ...
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  • 1,119
3 votes
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Should the cell sorting marker genes be excluded during clustering?

I do not think there is a simple "yes" or "no" answer here. A good starting point would be, as you suggest, use all the genes and assess the results in the light of the marker genes and expected ...
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  • 481
3 votes

validating identified sub-populations of cells in scRNA-seq

While better methods of evaluating your clusters would be to use an external dataset or a dataset with known truth, there are a variety of internal validation metrics that can be used to compare ...
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  • 31
3 votes
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factoextra: Error in if (xlab == "x") xlab <- "x value" : argument is of length zero

I actually found an answer just accidentally. It is very unfortunate that factoextra documentation does not explicitly say that ...
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3 votes

Find Patterns in Cluster

Based on your description I think you should have a look at a technique called 'biclustering'. The example on this page defines the goal of this technique as 'Finding subgroups of rows and columns ...
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3 votes
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RNA-Seq: clustering/treatment of genes with low expression

rlog(normalized counts) is going to be more robust than log2(TPM), so use it instead. Do it afterward, keeping the low counts ...
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3 votes

Omics data: How to interpret heatmap and dendrogram output?

You may be interested in reading up on heatmaps. For a history perspective (pre the biological introduction by Eisen et al. ) read The History of the Cluster Heat Map by Wilkinson and Friendly
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  • 31
3 votes
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Omics data: How to interpret heatmap and dendrogram output?

The dendrogram summarize the information of a group of values and sort them according to the similarity they have. It can be applied to both, samples and features. The dendrogram allows to visualize ...
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  • 4,602
3 votes

How to scale the size of heat map and row names font size?

Make the image itself bigger (e.g., png("S7.png", width=1000, height=1000)). Having said that, rethink the utility of having the labels there. Are you really going ...
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3 votes
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Cluster is split in 2-3 locations on tsne plot - Suerat

Your cluster labels come from graph clustering implemented in the FindClusters() function. The resulting clusters are then visualised with a 2D tSNE plot (via ...
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  • 3,432
2 votes

What could be the reason for the samples not clustering?

Samples will only cluster by experimental group if the experimental effect is large enough that it's the primary source of variance between your samples. If that's not the case then you'll get results ...
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2 votes

Evaluate clusters of individuals by using their sequence data

You can calculate allele frequencies for each cluster you have to further verify if they belong to similar population, however if size of your dataset is rather small this may not work for you. https:...
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2 votes

Seurat for clustering bulk RNA-seq?

I'm not sure Seurat is the best tool for this as it was developed for single cell RNA seq data and there are a few intricacies of that type of data that are very different from bulk RNA seq. For bulk ...
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  • 121
2 votes
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Can I get the graph generated by cellranger

Cell Ranger You can't download the tSNE coordinates for cells directly from the Analysis tab of the fancy, polished .html document that Cell Ranger produces. If you have access to the machine on ...
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  • 1,119
2 votes

Using multidimensional scaling to visualize protein sequences by functionality

Some of the first MSA analysis, eg of codon usage of bacteria were performed using matrix factorization (see old papers from Des Higgins). His group also published discriminative methods for finding ...
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  • 156
2 votes
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Hierarchical clustering for outlier detection - single cell RNASeq & WGCNA

For outlier identification I suggest using the sample network approach developed by Oldham et al. It basically amounts to constructing a inter-sample connectivity (assuming ...
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2 votes

Clustering using cellranger

The direct answer is yes. If you have never worked with hdf5 you can start here. But, cellranger outputs several hdf5 files. You can extract the count matrix from the "/outs/...
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2 votes

about the normalization of RNAseq data for calculating distance for unsupervised learning

Typically some sort of variance stabilizing transform is used before clustering. Popular options are regularized log transformation or a vst transform, which are available in DESeq2. Note that these ...
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2 votes

Changing active.ident in Seurat

M <- SetIdent(M, value = "status") or more explicitly M <- SetIdent(M, value = M@meta.data$status) You can also ...
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  • 3,432
2 votes
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Calculating average mito.percentage for each cluster (seurat)

You can extract the necessary values and add them directly the plot as a second layer using plot + geom_text(). This is very similar to the inner workings of the <...
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  • 768
2 votes

How do I install hammock?

Download a release (Hammock_v_1.2.0.7z) from https://github.com/krejciadam/hammock/releases Unzip To run the first example: ...
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  • 56
2 votes
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How do I plot clusters based on DNA sequence alignment?

I think one of the reasons you struggle is that clustering DNA sequences is not a clearly defined task. In general intention of clustering is to reconstruct, or approximate the relatidness of the DNA ...
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