KrishnaswamyLab / CSHL_ComputationalGenomics2023

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Cold Spring Harbor Course on Computational Genomics

November 29 - December 6 2023

https://github.com/KrishnaswamyLab/CSHL_ComputationalGenomics2023

Link to CSHL Course Website
Link to Slack channel help

To see the course slides and colab notebooks from 2022, see last year's repository.

Precourse Recommendations:
The course workshops will use Python, and some practice beforehand is strongly recommended. For those without Python experience at this point, I would recommend purchasing and going through the Codecademy Python 3 Tutorial (focus on Sections 1-6) and the Data Analysis with Pandas Tutorial. These two courses will provide a sufficient background for the course.

I also suggest you get some exposure to some of the mathematical concepts we will teach during the workshop. A great place to start is this review article from our lab on manifold-based methods: Manifold learning-based methods for analyzing single-cell RNA-sequencing data or this review on multiscale manifold-based methods: Multiscale geometric and topological analyses for characterizing and predicting immune responses from single cell data.

Course data and Colabs:
In this course, we will be using several publicly available and simulated single-cell datasets. All our code will be available on Google Colab. The full drive with data and Colab coding notebooks is accessible here, and the hyperlinks in the schedule below correspond to the slides and code for each lecture. If you are interested in using Google Colab more generally for your work, see guides in the introduction notebook and FAQ.

Single-cell preprocessing:
The data we will be working with is already pre-processed. To learn how to preprocess scRNA-seq data from publicly available data, see this Google Colab. To learn how to preprocess your scRNA data, see this Google Colab.


Sunday-- 3 December 2023

10:00 [Slides] Single-cell Analysis I-- PHATE/Multiscale PHATE/MELD
11:00 [Colab] [Answers] Workshop Single-cell analysis I
14:30 [Slides] Single-cell Analysis II-- MAGIC/Pseudotime/TrajectoryNet
15:30 [Colab] [Answers] Workshop Single-cell analysis II

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