1. Datacamp
2. Hemberg's Lab course
3. OCW MIT Computational Biology
4. Computational Biology: Genomes, Networks, Evolution*
5. MIT's 6.047/6.878 Machine Learning in Genomics*
6. Deep Learning for Single Cell Biology
7. Seurat - Guided Clustering Tutorial*
8. STAT 555: Statistical Analysis of Genomics Data*

1. hemberg-lab
2. SingleCellThoughts, SingleCellThoughts
3. Single-cell exploratory data analysis for RNA-Seq
4. Single-cell RNA sequencing (Cell Ranger)
5. Nikolay Oskolkov
6. Awesome Single Cell
7. scScope
8. Dendrosplit
9. Clustering cells from single cell RNA seq assays

1. Gilad's Lab
2. Kellis Lab at MIT*
3. Broad Institute
4. Marioni group*
5. Valentine Svensson

1. SIB ExPASy Bioformatics Resources Portal

1. scRNAseq: The scRNAseq package provides convenient access to several publicly available data sets in the form of SingleCellExperiment objects. The focus of this package is to capture datasets that are not easily read into R with a one-liner from, e.g., read.csv().
2. scater
3. scran
4. seurat
5. MAST
6. NMF
7. ggfortify
8. scran

1. Biopython
2. Scanpy
3. Scedar

1. scGEAToolbox

1. StatQuest: A gentle introduction to RNA-seq
2. MIT CompBio Lecture 21 - Single-Cell Genomics, Fall 2018
3. MIT CompBio Lecture 21 - Single-Cell Genomics, Fall 2019

1. Deconstructing Olfactory Stem Cell Trajectories at Single Cell Resolution*
2. DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning*
3. Deciphering epigenomic code for cell differentiation using deep learning*
4. Current best practices in single-cell RNA-seq analysis: a tutorial*
5. Revealing the vectors of cellular identity with single-cell genomics*
6. Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments
7. Single-cell RNA-seq denoising using a deep count autoencoder*
8. 12 Grand Challenges in Single-Cell Data Science*
9. An interpretable framework for clustering single-cell RNA-Seq datasets
10. Transcriptomic characterization of 20 organs and tissues from mouse at single cell resolution creates a Tabula Muris
11. Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications*+

1. Reinthinking Single-Cell RNA-Seq Analysis*

1. Single Cell Portal - Broad Institute
2. Tung dataset (2017)
3. Treutlein dataset(2014)

^{*web.archive.org version backup available.}

• Rahul Bhadani ( rahulbhadani@email.arizona.edu)