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Noteworthy Single-cell RNA-seq Datasets on Inflammatory Diseases

Single-cell datasets are not easy to come by. This data needs to be mined from various publications and multiple repositories like SCP, HCA, GEO, etc. And this is just the beginning. The researcher then has to spend a huge chunk of time extracting and preprocessing this data because it will be present in different file formats, which may not be easily accessible or compatible with all data analysis tools.

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Noteworthy Single-cell RNA-seq Datasets on Inflammatory Diseases

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  1. Noteworthy Single-cell RNA-seq Datasets on Inflammatory Diseases

  2. Single-cell datasets are not easy to come by. This data needs to be mined from various publications and multiple repositories like SCP, HCA, GEO, etc. And this is just the beginning. The researcher then has to spend a huge chunk of time extracting and preprocessing this data because it will be present in different file formats, which may not be easily accessible or compatible with all data analysis tools. Here’s a glimpse of the single-cell datasets on Elucidata’s data harmonization platform- Polly. Polly harmonizes unstructured single-cell data with a configurable, transparent, and granular curation process as per your inclusion/ exclusion criteria to accelerate downstream analysis. Another challenge is incomplete or poorly described metadata (cell types, experimental conditions, sample information, etc.), making it challenging to interpret the results.

  3. t-SNE plot showing the different cell types 01 Comprehensive Profiling of Cancer Cells and Their Microenvironment in Advanced NSCLC Dataset ID: GSE148071_GPL20795 Year of Publication: 2021 No of cells: 58 396 Organism:Homo sapiens Source: GEO Reference link: Single-cell profiling of tumor heterogeneity and the microenvironment in advanced non-small cell lung cancer

  4. UMAP shows immune cells in different developmental stages 02 Mapping the Developing Human Immune System Across Organs Year of Publication: 2022 No of cells: 589 390 Source: Publication Polly ID: HSC_immune_cells_all_hematopoietic-derived_cells Organism:Homo sapiens Reference link: Mapping the developing human immune system across organs

  5. UMAP shows the distribution of different cells in the human cell landscape 03 Construction of a Human Cell Landscape at the Single-Cell Level Year of Publication: 2020 Organism:Homo sapiens No of cells: 599 926 Polly ID: Construction_of_a_human_cell_landscape_at_single-cell_level Source: Publication Reference link: Construction of a human cell landscape at single-cell level

  6. UMAP shows the distribution of immune cells 04 Defining T Cell States Associated with Response to Checkpoint Immunotherapy in Melanoma Year of Publication: 2018 Organism:Homo sapiens No of cells: 14 151 Source: GEO Dataset ID: GSE120575_GPL18573 Reference link: Defining T Cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

  7. UMAP shows the distribution of cardiac cells 05 Spatial Multi-Omic Map of Human Myocardial Infarction Year of Publication: 2022 Organism:Homo sapiens No of cells: 191 795 Source: Publication Polly ID: All-snRNA-Spatial_multi-omic_map_of_human_myocardial_infarction Reference link: Spatial multi-omic map of human myocardial infarction

  8. Thank You. ‍Connect with us to accelerate your journey of finding relevant biomedical datasets, creating cohorts, and visualizing & analyzing the data, to derive actionable insights and probable targets.

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