Read in depth¶
2020-09-14¶
We read CHISEL paper for single-cell copy number variation calling [zaccaria2020characterizing] in detail today.
2020-10-11¶
We read variational auto-encoder paper [kingma2013auto] in detail today, with brief disucssion on its single cell application scVI [lopez2018deep].
2021-05-17¶
We read three papers: RPCI [liu2021robust], Cell-ID: [cortal2021gene], scPred [alquicira2019scpred], all about linear projection of single-cell transcriptome to lower dimensional space with singular value decomposition (SVD), the implementation technique for Principal component analysis (PCA).
We also referred more details on PCA and SVD by reading the following book chapters:
SVD quick reading: chapter 2.7-2.8 (4 pages): https://www.deeplearningbook.org/contents/linear_algebra.html
SVD Longer reading: chapter 4.5: https://mml-book.github.io/book/mml-book.pdf
PCA quick reading: chapter 12.1 https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf
2022-01-13¶
We read the Chapter 8 OptimiZation, PML book 1. https://probml.github.io/pml-book/book1.html
Rongting lead the reading of the foundation part, Mingze lead the discussion of the specific methods (SGD and the rest), and Chen C introduce the EM details.
2022-02-16¶
We read the Chapter 13-14 deep nueral networks(Introduction), PML book 1. https://probml.github.io/pml-book/book1.html
Xianjie, Qiaochen and Ruiyan lead the reading.
2022-03-02¶
We read the Chapter 14 VAE, PML book 1. https://probml.github.io/pml-book/book1.html
Fangxin and weizhong lead the reading.
References¶
Simone Zaccaria and Benjamin J Raphael. Characterizing allele-and haplotype-specific copy numbers in single cells with chisel. Nature biotechnology, pages 1–8, 2020. URL: https://www.nature.com/articles/s41587-020-0661-6.
Diederik P Kingma and Max Welling. Auto-encoding variational bayes. arXiv, 2013. URL: https://arxiv.org/abs/1312.6114.
Romain Lopez, Jeffrey Regier, Michael B Cole, Michael I Jordan, and Nir Yosef. Deep generative modeling for single-cell transcriptomics. Nature methods, 15(12):1053–1058, 2018. URL: https://www.nature.com/articles/s41592-018-0229-2.
Yang Liu, Tao Wang, Bin Zhou, and Deyou Zheng. Robust integration of multiple single-cell RNA sequencing datasets using a single reference space. Nature biotechnology, pages 1–8, 2021. URL: https://www.nature.com/articles/s41587-021-00859-x.
Akira Cortal, Loredana Martignetti, Emmanuelle Six, and Antonio Rausell. Gene signature extraction and cell identity recognition at the single-cell level with Cell-ID. Nature Biotechnology, pages 1–8, 2021. URL: https://www.nature.com/articles/s41587-021-00896-6.
Jose Alquicira-Hernandez, Anuja Sathe, Hanlee P Ji, Quan Nguyen, and Joseph E Powell. scPred: accurate supervised method for cell-type classification from single-cell RNA-seq data. Genome biology, 20(1):1–17, 2019. URL: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1862-5.