{ "id": 351038, "title": "Papers, videos, notebooks, other materials related to the competition and research topics around ", "url": "/competitions/open-problems-multimodal/discussion/351038", "author_name": "", "post_date": "2022-09-08T09:24:16.002682200Z", "votes": 15, "comment_count": 1, "views": 0, "content": "

Let us collect info which might be related to the competition (and more widely research around - more precisely about multimodal single cell data, ATAC-seq, CITE-seq etc. )

\n\n

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02595-6
\nhttps://www.pnas.org/doi/10.1073/pnas.2023070118
\nhttps://www.nature.com/articles/s41467-019-12630-7
\nhttps://www.nature.com/articles/s41592-022-01562-8
\nhttps://www.nature.com/articles/s42256-022-00469-5

\n

To be continued

", "messages": [ { "id": "1930868", "postDate": "09/08/2022 09:24:16", "content": "

Let us collect info which might be related to the competition (and more widely research around - more precisely about multimodal single cell data, ATAC-seq, CITE-seq etc. )

\n\n

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02595-6
\nhttps://www.pnas.org/doi/10.1073/pnas.2023070118
\nhttps://www.nature.com/articles/s41467-019-12630-7
\nhttps://www.nature.com/articles/s41592-022-01562-8
\nhttps://www.nature.com/articles/s42256-022-00469-5

\n

To be continued

", "rawMarkdown": "Let us collect info which might be related to the competition (and more widely research around - more precisely about multimodal single cell data, ATAC-seq, CITE-seq etc. )\n\n- Summary paper from the last year competition: Multimodal single cell data integration challenge: Results and lessons learned ( https://proceedings.mlr.press/v176/lance22a.html ) \n\n- A deep generative model for multi-view profiling of single-cell RNA-seq and ATAC-seq data ( Genome Biology 2022) \nhttps://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02595-6#Sec10\n\n- SCMER - package to work with https://scmer.readthedocs.io/en/latest/cite-seq-bmnc-donor2-validation.html\n\n- SCANPY tutorial https://scanpy-tutorials.readthedocs.io/en/latest/paga-paul15.html is quite related to the present data.\n\n- Winners' solutions of the last year (topic here): https://www.kaggle.com/competitions/open-problems-multimodal/discussion/348792 \n\n- Models and Notebooks About Single-Cell Data on Kaggle (topic here): https://www.kaggle.com/competitions/open-problems-multimodal/discussion/344824\n\n- Research Papers on Multimodal Single-Cell Integration (topic here): https://www.kaggle.com/competitions/open-problems-multimodal/discussion/344686\n\n- Weighted-nearest neighbor analysis - Multimodal Single-Cell Integration (topic here): https://www.kaggle.com/competitions/open-problems-multimodal/discussion/344688 \n\n- Codes | Diagonal integration of multimodal single-cell data (topic here): \nhttps://www.kaggle.com/competitions/open-problems-multimodal/discussion/344687\nPaper : https://www.nature.com/articles/s41467-022-31104-x#code-availability\nGithub : https://github.com/rpmccordlab/cross-domain-simulation\n\n- CITE-seq: https://youtu.be/IUT6qwtmGzY\nPreprocessing and models (mainly for scRNA-seq data): https://scanpy.readthedocs.io/en/stable/\nhttps://yoseflab.github.io/software/scvi-tools/\nhttps://paperswithcode.com/paper/sisua-semi-supervised-generative-autoencoder\n\n- Related dataset (topic here): https://www.kaggle.com/competitions/open-problems-multimodal/discussion/349582\n\n- Playlist of related webinars: https://www.youtube.com/watch?v=bZ_oFxujyxo&list=PL89L8UQK3ys81d0NeH4e8Ff4XLAoNJ_eM\n\n- Single-cell roadmap of human gonadal development https://www.nature.com/articles/s41586-022-04918-4\nWe used several single-cell genomics methods: (1) single-cell RNA sequencing (scRNA-seq); (2) single-cell accessible chromatin sequencing (scATAC-seq) and (3) combined single-nucleus RNA and ATAC sequencing (snRNA-seq/scATAC-seq) to profile 347,709, 96,174 and 40,742 cells, respectively (Fig. 1b and Supplementary Tables 1–3). We also generated single-cell transcriptomes of corresponding mouse tissue around the time of sex determination, that is, at embryonic days (E) 10.5, 11.5 and 12.5 (63,929 cells), and integrated them with a previously published dataset covering later gestational stages (E11.5 to postnatal day (P) 5)5 (Supplementary Table 1).\n\n- Related Hi-C data: High Order Chromatin Structure Regulates Gene Expression in Hematopoietic Stem Cell Self-Renewal and Erythroid Differentiation https://www.sciencedirect.com/science/article/pii/S0006497119310341 Large DNA Methylation Nadirs Anchor Chromatin Loops Maintaining Hematopoietic Stem Cell Identity https://www.sciencedirect.com/science/article/pii/S1097276520302604?via%3Dihub Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C https://www.nature.com/articles/ng.3286\n \n- MOFA analysis of the Chromium Single Cell Multiome ATAC + Gene Expression assay https://raw.githack.com/bioFAM/MOFA2_tutorials/master/R_tutorials/10x_scRNA_scATAC.html\n\n- The other similar topics on Kaggle: \nhttps://www.kaggle.com/competitions/open-problems-multimodal/discussion/344686#1941193\nhttps://www.kaggle.com/code/digitalbro/multimodal-sc-integration-meta-resources\n\nhttps://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02595-6\nhttps://www.pnas.org/doi/10.1073/pnas.2023070118\nhttps://www.nature.com/articles/s41467-019-12630-7\nhttps://www.nature.com/articles/s41592-022-01562-8\nhttps://www.nature.com/articles/s42256-022-00469-5\n\n\nTo be continued", "votes": null }, { "id": "1953657", "postDate": "09/24/2022 16:24:30", "content": "

Dimensional reduction plots by orgs:
\nhttps://twitter.com/DBBurkhardt/status/1559304632438079495?s=20&t=ch2m23EzqSMGDiCfeqdp2A

", "rawMarkdown": "Dimensional reduction plots by orgs:\nhttps://twitter.com/DBBurkhardt/status/1559304632438079495?s=20&t=ch2m23EzqSMGDiCfeqdp2A", "votes": null } ], "comments": [ { "id": 1953657, "author_name": "alexandervc", "author_url": "", "post_date": "09/24/2022 16:24:30", "content": "

Dimensional reduction plots by orgs:
\nhttps://twitter.com/DBBurkhardt/status/1559304632438079495?s=20&t=ch2m23EzqSMGDiCfeqdp2A

", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "1930868": "Let us collect info which might be related to the competition (and more widely research around - more precisely about multimodal single cell data, ATAC-seq, CITE-seq etc. )\n\n- Summary paper from the last year competition: Multimodal single cell data integration challenge: Results and lessons learned ( https://proceedings.mlr.press/v176/lance22a.html ) \n\n- A deep generative model for multi-view profiling of single-cell RNA-seq and ATAC-seq data ( Genome Biology 2022) \nhttps://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02595-6#Sec10\n\n- SCMER - package to work with https://scmer.readthedocs.io/en/latest/cite-seq-bmnc-donor2-validation.html\n\n- SCANPY tutorial https://scanpy-tutorials.readthedocs.io/en/latest/paga-paul15.html is quite related to the present data.\n\n- Winners' solutions of the last year (topic here): https://www.kaggle.com/competitions/open-problems-multimodal/discussion/348792 \n\n- Models and Notebooks About Single-Cell Data on Kaggle (topic here): https://www.kaggle.com/competitions/open-problems-multimodal/discussion/344824\n\n- Research Papers on Multimodal Single-Cell Integration (topic here): https://www.kaggle.com/competitions/open-problems-multimodal/discussion/344686\n\n- Weighted-nearest neighbor analysis - Multimodal Single-Cell Integration (topic here): https://www.kaggle.com/competitions/open-problems-multimodal/discussion/344688 \n\n- Codes | Diagonal integration of multimodal single-cell data (topic here): \nhttps://www.kaggle.com/competitions/open-problems-multimodal/discussion/344687\nPaper : https://www.nature.com/articles/s41467-022-31104-x#code-availability\nGithub : https://github.com/rpmccordlab/cross-domain-simulation\n\n- CITE-seq: https://youtu.be/IUT6qwtmGzY\nPreprocessing and models (mainly for scRNA-seq data): https://scanpy.readthedocs.io/en/stable/\nhttps://yoseflab.github.io/software/scvi-tools/\nhttps://paperswithcode.com/paper/sisua-semi-supervised-generative-autoencoder\n\n- Related dataset (topic here): https://www.kaggle.com/competitions/open-problems-multimodal/discussion/349582\n\n- Playlist of related webinars: https://www.youtube.com/watch?v=bZ_oFxujyxo&list=PL89L8UQK3ys81d0NeH4e8Ff4XLAoNJ_eM\n\n- Single-cell roadmap of human gonadal development https://www.nature.com/articles/s41586-022-04918-4\nWe used several single-cell genomics methods: (1) single-cell RNA sequencing (scRNA-seq); (2) single-cell accessible chromatin sequencing (scATAC-seq) and (3) combined single-nucleus RNA and ATAC sequencing (snRNA-seq/scATAC-seq) to profile 347,709, 96,174 and 40,742 cells, respectively (Fig. 1b and Supplementary Tables 1–3). We also generated single-cell transcriptomes of corresponding mouse tissue around the time of sex determination, that is, at embryonic days (E) 10.5, 11.5 and 12.5 (63,929 cells), and integrated them with a previously published dataset covering later gestational stages (E11.5 to postnatal day (P) 5)5 (Supplementary Table 1).\n\n- Related Hi-C data: High Order Chromatin Structure Regulates Gene Expression in Hematopoietic Stem Cell Self-Renewal and Erythroid Differentiation https://www.sciencedirect.com/science/article/pii/S0006497119310341 Large DNA Methylation Nadirs Anchor Chromatin Loops Maintaining Hematopoietic Stem Cell Identity https://www.sciencedirect.com/science/article/pii/S1097276520302604?via%3Dihub Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C https://www.nature.com/articles/ng.3286\n \n- MOFA analysis of the Chromium Single Cell Multiome ATAC + Gene Expression assay https://raw.githack.com/bioFAM/MOFA2_tutorials/master/R_tutorials/10x_scRNA_scATAC.html\n\n- The other similar topics on Kaggle: \nhttps://www.kaggle.com/competitions/open-problems-multimodal/discussion/344686#1941193\nhttps://www.kaggle.com/code/digitalbro/multimodal-sc-integration-meta-resources\n\nhttps://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02595-6\nhttps://www.pnas.org/doi/10.1073/pnas.2023070118\nhttps://www.nature.com/articles/s41467-019-12630-7\nhttps://www.nature.com/articles/s41592-022-01562-8\nhttps://www.nature.com/articles/s42256-022-00469-5\n\n\nTo be continued", "1953657": "Dimensional reduction plots by orgs:\nhttps://twitter.com/DBBurkhardt/status/1559304632438079495?s=20&t=ch2m23EzqSMGDiCfeqdp2A" }, "source": "meta" }