Hello, Bioinformatics lovers,

This is Tommy. Usually, you should receive my weekly newsletter on Saturday morning.

I was away last week most of the time at Iowa State University https://idgp-biosci-symposium.sites.iastate.edu/2024-speaker-information for a symposium. I loved interacting with the students and seeing the awesome science they were doing.

However, biology has become a data-intensive field. Lacking computational skills hinders their ability to analyze their data. Most of the talks by the students have some components of data analysis (image analysis, bulk-RNAseq, etc).

I gave a talk on how to learn computational biology the right way. Please find the slides at.2024-04-04_learn_compbio_from_scratch_Iowa_state_U.pdf​

Other resources:

1. ​Master Bioinformatics RNAseq Analysis from Scratch: A Beginner's Guide
2. Accelerating Drug Development Using Spatial Multi-omics https://aacrjournals.org/cancerdiscovery/article/14/4/620/741974/Accelerating-Drug-Development-Using-Spatial-Multi​
3. Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments https://www.nature.com/articles/s41592-023-01785-3​
4. Obtain metadata for public datasets in GEO https://divingintogeneticsandgenomics.com/post/obtain-metadata-for-public-datasets-in-geo/​
5. customize FeaturePlot in Seurat for multi-condition comparisons using patchwork https://divingintogeneticsandgenomics.com/post/customize-featureplot-in-seurat-for-multi-condition-comparisons-using-patchwork/​
6. Statistical method scDEED for detecting dubious 2D single-cell embeddings and optimizing t-SNE and UMAP hyperparameters https://www.nature.com/articles/s41467-024-45891-y​
7. Principled and interpretable alignability testing and integration of single-cell data https://www.pnas.org/doi/10.1073/pnas.2313719121​
8. BANKSY unifies cell typing and tissue domain segmentation for scalable spatial omics data analysis https://www.nature.com/articles/s41588-024-01664-3​
9. Pan-cancer proteogenomics characterization of tumor immunity https://www.cell.com/cell/fulltext/S0092-8674(24)00064-3​

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Happy Learning!

Tommy

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DNA confesses Data speak

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