MIT CompBio Lecture 21 - Single-Cell Genomics

MIT Computational Biology: Genomes, Networks, Evolution, Health
Prof. Manolis Kellis
compbio.mit.edu/6.047/
Fall 2018
Lecture 21 - Single-cell Genomics
1. Single-cell profiling technologies
- Traditional single-cell analyses
- Single-cell RNA-seq
- Dealing with noise in scRNA-seq data
- Single-cell epigenomics (scATAC-Seq)
2. Extracting biological insights from single-cell data
- Clustering similar cells
- Clustering similar genes
- Dimensionality reduction
- Distinguishing different cell types
- Trajectories through cell space
- Dataset completion and missing data imputation
3. Single-cell RNA-seq in disease: Focus on Brain Disorders
- Why Brain: Cell type and function diversity
- Initial maps of brain diversity across regions, development, organoids
- Brain variation at the single-cell level in Alzheimer’s disease
- Somatic mosaicism and clonality from scDNA-seq and scRNA-seq
- Deconvolution of bulk data into single-cell profiles vs. phenotype vs. genotype
- Deconvolution of eQTL effects at single-cell level and mediation analysis
Slides for Lecture 21:
stellar.mit.edu/S/course/6/fa...

Thank you so much Dr. Manolis Kellis. Greetings from Bimac Research Group at Universidad del Cauca, Colombia.

[@qsc9546]

PCA to construct network, with network molecularity reduction usually has up to 0.8 clustering accuracy with low noise field dataset.

[@laylachae]

Thank you very much. It helped me a lot.

[@timazebardast1096]

Thank you, I really enjoyed this lecture, comprehensive, nice speech, good voice and video quality. 💜

[@lhsilhs1512]

Dr. Kellis, Thank you. Is this the entire lecture that you offered for scRNA-seq methods or are there more lectures that we can learn.

[@lvest79]

Great lecture!

[@chaks94]

Very clearly explained! Thank you so much.

[@qsc9546]

What's the overall performance of Seurat, Scanpy, SingleR, and ScPred ? Really depends on data sets.

[@educationk]

Awesome lecture...is there way to find codes for all the plots generated here?

[@anjalimaru823]

Is it also applicable for mitochondrial and chloroplast genomics ????

[@OmegaPsiPhi0]

Human Cell Atlas 📚

[@helenaklarajambor2914]

Super great for preparing my own lectures, thank you very much Manolis! Did anyone catch the Barcoding: I think he said with 10 nucleotides there are 2^10 possibilities, does that mean for barcodes only 2 nucleotides are used? Else i'd be 4^10 possibilities?

[@ManolisKellis1]

Yes indeed. 4^10. Thanks

[@olgaantonova5939]

nice intro, but every 10 seconds, he says "you know".

[@ManolisKellis1]

Thanks for your feedback Olga, i'll be more careful in the future

[@Singularitarian]

@@ManolisKellis1 Saying "you know" is fine, I didn't even notice. Not a bad thing.