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13 votes
Accepted

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 ...
Devon Ryan's user avatar
  • 19.6k
6 votes
Accepted

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): ...
Devon Ryan's user avatar
  • 19.6k
6 votes
Accepted

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" ...
olga's user avatar
  • 481
6 votes
Accepted

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" ...
M__'s user avatar
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5 votes
Accepted

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 ...
Devon Ryan's user avatar
  • 19.6k
5 votes
Accepted

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 ...
sjcockell's user avatar
  • 861
5 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... ...
user172818's user avatar
  • 6,535
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 ...
LinuxBlanket's user avatar
4 votes

How to analyse Orthofinder results

I think they simply calculate the percentage of proteins in each species that belongs to an orthogroup conserved in the five species. There should be a tab separated text file called Orthogroups....
CorteZero's user avatar
  • 109
4 votes
Accepted

split fastq file containing a sequence block at different locations

You can try seqkit locate with say start or end of CDS sequence. This will give you a tabulated output with locations of your CDS query in each read. Since you expect that the CDS sequence should be ...
darked89's user avatar
  • 358
3 votes
Accepted

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 ...
Kohl Kinning's user avatar
  • 1,149
3 votes
Accepted

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 ...
olga's user avatar
  • 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 ...
Alec's user avatar
  • 31
3 votes
Accepted

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 ...
Nikita Vlasenko's user avatar
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 ...
holmrenser's user avatar
3 votes
Accepted

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 ...
Devon Ryan's user avatar
  • 19.6k
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
GIM's user avatar
  • 31
3 votes
Accepted

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 ...
llrs's user avatar
  • 4,713
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 ...
Devon Ryan's user avatar
  • 19.6k
3 votes
Accepted

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 ...
haci's user avatar
  • 4,142
3 votes

hierarchical clustering of kmers and their counts

I think you need some way to convert the k-mer strings into a numerical representation so that they can be clustered. There's a few ways to do this. For example, you could one-hot (or two-bit) encode ...
Steve's user avatar
  • 3,109
3 votes

Mapping single cell data with annotation

It seems like you can annotate all your cells as endothelial cells, problem solved ;) But seriously, not clear what your expected cell types are (subtypes of endothelial cells perhaps) or the tissue ...
Chris_Rands's user avatar
  • 3,948
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 ...
Devon Ryan's user avatar
  • 19.6k
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:...
Ümit Akköse's user avatar
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 ...
biomiha's user avatar
  • 121
2 votes
Accepted

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 ...
Kohl Kinning's user avatar
  • 1,149
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 ...
Aedin's user avatar
  • 156
2 votes
Accepted

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 ...
Peter Langfelder's user avatar
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/...
Mack123456's user avatar
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 ...
Devon Ryan's user avatar
  • 19.6k

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