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Clustering 3K PBMCs with Scanpy

Contributors

AvatarMehmet Tekman

Questions

Objectives

last_modification Last modification: Apr 16, 2021

Single Cell RNA Pre-processing

fig01

Speaker Notes

  1. Barcode Extraction
  2. Mapping
  3. Gene Annotation
  4. Batch count matrices

Single Cell RNA Downstream Analysis

fig10

Speaker Notes

  1. Filtering
  2. Normalising
    • Confounder Removal
  3. Dimension Reduction
  4. Clustering
    • Annotation

Barcoding Cells

fig1


Filtering: Cell and Gene

fig2


Normalisation: Technical Variation

fig3


Normalisation: Biological Variation

fig4


Dimension Reduction: Relatedness of Cells

fig5

Speaker Notes Build a KNN graph from distance matrix:


Dimension Reduction: Projection

fig6

Speaker Notes


Community Clustering: Louvain

Aim: Maximise internal links and minimise external links

fig7


Community Clustering: Louvain

Pick a cell, place in neighbour, and accept if internal:external increases

fig8


Cell Type: Identifying Cluster Types

.left-column50[.image-100[fig9]] .left-column50[.image-100[fig10]]


Clustering: Hard vs Soft

.pull-left[


.image-100[fig11]

Hard

]

.pull-right[ .image-100[fig12]

Soft

]

Speaker Notes Why? Why would there be clusters so close to one another?


Continuous Phenotypes:

.image-100[fig13]

Speaker Notes


Interactive Environments: live.usegalaxy.eu


Speaker Notes What is Differential Expression in scRNA-seq?


CellxGene Local Test


Key Points

Thank you!

This material is the result of a collaborative work. Thanks to the Galaxy Training Network and all the contributors! Galaxy Training Network This material is licensed under the Creative Commons Attribution 4.0 International License.