Live tasks
Motif Search in DNA/Protein Sequences
The following livetask is designed to identify specific motifs within a set of DNA or Protein sequences provided in a FASTA format file.
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UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
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PyDESeq2 for differential expression analysis
This livetask utilizes the PyDESeq2 library for differential expression analysis of gene expression data. It takes as input a count table and metadata file
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Convert gene names to gene IDs
This livetask streamlines the process of converting gene names to gene IDs by leveraging the MyGeneInfo API and pandas library in Python. It takes a list of gene names stored in a csv format as input.
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Convert gene IDs to gene names
This livetask streamlines the process of converting gene IDs to gene names. It takes a list of gene IDs in a csv format as input.
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Imputing missing values with iterative method
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Imputation for completing missing values using k-Nearest Neighbors
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Plot a heatmap with dendogram
This live task shows you how to quickly plot a heatmap combined with a dendogram in Constellab. Heatmaps are used when we have a lot of data because it is easier to interpret and distinguish raw value...
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Univariate imputer for completing missing values with simple strategies
This live tasks shows you how to quickly replace missing values using a descriptive statistic (e.g. mean, median, or most frequent) along each column, or using a constant value. The various stra...
Version 2
Plot a parallel coordinates plot
This live tasks shows you how to quickly plot an interactive parallel coordinates plot in Constellab. In a parallel coordinates plot with px.parallel_coordinates, each row of the DataFrame is represen...
Version 1