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<!DOCTYPE HTML>
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<title>Common Bioinformatics Software</title>
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<h1>Some Commonly Used Bioinformatics Software</h1>
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<p>Here are some of the bioinformatics software I have used and my experience at using that. The page is
still in construction, and I will add more information about them.</p>
<p><b><a href="https://github.com/BayraktarLab/cell2location">Cell2loc</a></b></p>
<p>Cell2loc is used to deconvolution the spatial transcriptomics data. It enables us to investigate the
cell proportion in a spatially resolved manner</p>
<p><b><a href="https://github.com/broadinstitute/Tangram">Tangram</a></b></p>
<p>Tangram is also a great tool for the spatial deconvolution.</p>
<p><b><a href="https://satijalab.org/seurat/">Seurat</a></b></p>
<p>A commonly used tool for the single-cell analysis. Basically doing anything. Many tools also based on
that. <del>It seems that Seurat is better known than Georges Pierre Seurat</del></p>
<p><b><a href="https://scanpy-tutorials.readthedocs.io/en/latest/">Scanpy</a></b></p>
<p>Like Seurat. Also commonly used in single cell analysis. Many tools like Tangram are based on it.</p>
<p><b><a href="https://github.com/dpeerlab/Palantir">Palantir</a></b></p>
For aligning cells in trajectories.
<p><b><a href="https://github.com/tabdelaal/SpaGE">SpaGE</a></b></p>
<p>Predict the gene expression level (imputation) in spatial transcriptomics data.</p>
<p><b><a href="https://bioconductor.org/packages/release/bioc/html/DESeq2.html">DESeq2</a></b></p>
<p>Bioconductor package for differential gene analysis for bulk RNA-seq data. </p>
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