单细胞数据分析概要
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分析可视化
https://github.com/klarman-cell-observatory/scPlot 这个项目是专门针对单细胞的图表
The plots provided include scatter plots, feature plots, dot plots and violin plots and can scale to millions of cells by plotting cells on a 2D grid. scPlot uses HoloViews (http://holoviews. org/), thus allowing generation of interactive plots with Bokeh for a Jupyter notebook.
https://pauliacomi.com/2020/06/07/plotly-v-bokeh.html
Plotly vs. Bokeh: Interactive Python Visualisation Pros and Cons -
https://sci-hub.st/10.1093/nar/gkx949
单细胞数据库的整合问题 -
https://terra.bio/speed-up-your-machine-learning-work-with-gpus/
GPU 支持 例子也用的是pegasus
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https://rnabioco.github.io/cellar/
Single-cell RNA-seq Workshop -
数据集
https://cellxgene.cziscience.com/
https://www.covid19cellatlas.org/index.patient.htmlhttps://www.biorxiv.org/content/10.1101/2021.07.19.452956v1
The Tabula Sapiens: a single cell transcriptomic atlas of multiple organs from individual human donors -
单细胞类型注释：
https://www.cellkb.com/
https://www.biostars.org/p/433235/
scCATCH(https://github.com/ZJUFanLab/scCATCH)
SCSA (https://github.com/bioinfo-ibms-pumc/SCSA).
https://www.frontiersin.org/articles/10.3389/fgene.2020.00490/full
SCSA: A Cell Type Annotation Tool for Single-Cell RNA-seq Data
单细胞待解决的问题：
https://openproblems.bio/ -
scapy 培训视频
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https://scanpy.discourse.group/t/highly-variable-genes-best-practice/29/5
scanpy hvgs
You can find our current best-practices in the recent publication here 98. Typically the pre-processing steps in an analysis workflow would be:Cell & Gene QC
Normalization
Batch correction (or data integration)
HVG selection
Dimensionality reduction (including visualization) -
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https://www.singlecellcourse.org/
sanger的单细胞教程 -
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https://squidpy.readthedocs.io/en/latest/
squidpy 空间转录组分析 -