fig:qc-plot-pancreas
fig:qc-plot-pancreas-better
fig:discardplot416b
fig:discardplotpbmc
fig:zeisel-demo-snap25
fig:cellbench-lognorm-fail
fig:cellbench-lognorm-downsample
fig:trend-plot-seger-noweight
fig:cv2-pbmc
fig:elbow
fig:cluster-pc-choice
fig:zeisel-parallel-pc-choice
fig:corral-sort
fig:snifter-scater
fig:snifter-embedding
fig:densne
fig:pbmc-silhouette
fig:pbmc-box-purities
fig:rmsd-pbmc
fig:rmsd-pbmc-lib
fig:cluster-mod
fig:cluster-graph
fig:walktrap-v-louvain-prop
fig:walktrap-v-louvain-jaccard
fig:pbmc-graph-linked
fig:walktrap-res-clustree
fig:pbmc-rand-breakdown
fig:bootstrap-matrix
fig:graph-parameter-sweep
fig:simulated-outliers-auc-cohen
fig:simulated-cap-auc-cohen
fig:viol-gcg-lawlor
fig:pval-dist
fig:rankplot
fig:ambientpvalhist
fig:qc-mito-pbmc
fig:ambient-removal-igkc
fig:ambient-removal-lyz
fig:barcode-rank-mix-genes
fig:barcode-rank-mix-hto
fig:hto-total-comp
fig:hto-1to2-hist
fig:hto-ambient
fig:hto-ambient2
fig:hto-mix-tsne
fig:mammary-swapped-barcode-rank
fig:mammary-swapped-barcode-rank-after
fig:heatclust
fig:markerexprs
fig:denstsne
fig:densclust
fig:scdblfinder-tsne
fig:hash-barcode-rank
fig:hto-2to3-hash
fig:tsne-hash
fig:doublet-prop-hash-dist
fig:heat-cyclin
fig:heat-cyclin-grun
fig:dist-lef1
fig:phaseplot416b
fig:cell-cycle-regression
fig:cell-cycle-regression2
fig:cell-cycle-regression3
fig:leng-nocycle
fig:discard-416b
fig:cell-cycle-contrastive
fig:tscan-nest-tsne
fig:tscan-nest-pseudo
fig:tscan-nest-omega
fig:tscan-nest-mnn
fig:traj-princurve-tsne-nest
fig:traj-princurve-clustered-nest
fig:traj-princurve-omag-nest
fig:nest-1-simple-down
fig:nest-1-simple-up
fig:nest-1-simple-up-heat
fig:nest-pseudo-reordered
fig:nest-3-versus
fig:entropy-nest
fig:tsne-hermann-velocity
fig:tscan-sperm-velocity
fig:tcell-pseudotime
fig:nuclei-qc
fig:nuclei-tsne
fig:nuclei-tsne-merged
fig:nuclei-contamination
fig:top-prop-adt-dist
fig:cite-detected-ab-hist
fig:cite-total-con-hist
fig:pbmc-adt-ambient-profile
fig:comp-bias-norm
fig:control-bias-norm
fig:tsne-tags
fig:heat-tags
fig:subcluster-stats
fig:gzmh-cd8-t
fig:subcluster-tag-dist
fig:rescaled-tsne-adt
fig:combined-umap
fig:correlation-cd127-cluster
fig:correlation-pd1-blocked
fig:iSEE-default
fig:iSEE-landing
fig:iSEE-qc
fig:iSEE-anno
fig:iSEE-hvg
fig:iSEE-rowcol
fig:iSEE-tour
quality-control-redux
overview
the-isoutlier-function
outlier-assumptions
qc-batch
qc-discard-cell-types
more-norm
overview-1
scaling-and-the-pseudo-count
downsampling-instead-of-scaling
comments-on-other-transformations
normalization-versus-batch-correction
more-hvgs
overview-2
fine-tuning-the-fitted-trend
handling-covariates-with-linear-models
using-the-coefficient-of-variation
more-hvg-selection-strategies
feature-selection-positive
based-on-significance
apriori-hvgs
dimensionality-reduction-redux
overview-3
more-choices-for-the-number-of-pcs
using-the-elbow-point
using-the-technical-noise
based-on-population-structure
using-random-matrix-theory
count-based-dimensionality-reduction
more-visualization-methods
fast-interpolation-based-t-sne
density-preserving-t-sne-and-umap
clustering-redux
motivation
quantifying-clustering-behavior
motivation-1
silhouette-width
cluster-purity
within-cluster-sum-of-squares
using-graph-modularity
comparing-different-clusterings
motivation-2
identifying-corresponding-clusters
visualizing-differences
adjusted-rand-index
cluster-bootstrapping
clustering-parameter-sweeps
agglomerating-graph-communities
marker-detection-redux
motivation-3
properties-of-each-effect-size
using-custom-de-methods
p-value-invalidity
from-data-snooping
false-replicates
further-comments
droplet-processing
motivation-4
qc-droplets
background
testing-for-empty-droplets
relationship-with-other-qc-metrics
removing-ambient-contamination
cell-hashing
background-1
cell-calling-options
demultiplexing-on-hto-abundance
further-comments-1
removing-swapped-molecules
doublet-detection
overview-4
doublet-detection-with-clusters
doublet-simulation
computing-doublet-densities
doublet-classification
further-comments-2
doublet-detection-in-multiplexed-experiments
background-2
identifying-inter-sample-doublets
guilt-by-association-for-unmarked-doublets
further-comments-3
cell-cycle-assignment
motivation-5
using-the-cyclins
using-reference-profiles
using-the-cyclone-classifier
removing-cell-cycle-effects
comments
with-linear-regression-and-friends
removing-cell-cycle-related-genes
using-contrastive-pca
trajectory-analysis
overview-5
obtaining-pseudotime-orderings
overview-6
cluster-based-minimum-spanning-tree
basic-steps
tweaking-the-mst
further-comments-4
principal-curves
characterizing-trajectories
overview-7
changes-along-a-trajectory
changes-between-paths
further-comments-5
finding-the-root
overview-8
entropy-based-methods
rna-velocity
real-timepoints
single-nuclei-rna-seq-processing
introduction
quality-control-for-stripped-nuclei
comments-on-downstream-analyses
nuclei-ambient-tricks
integrating-with-protein-abundance
motivation-6
setting-up-the-data
quality-control
issues-with-rna-based-metrics
applying-custom-qc-filters
other-comments
normalization
overview-9
library-size-normalization
cite-seq-median-norm
control-based-normalization
computing-log-normalized-values
comments-on-downstream-analyses-1
feature-selection
clustering-and-interpretation
integration-with-gene-expression-data
by-subclustering
by-intersecting-clusters
with-rescaled-expression-matrices
with-multi-metric-umap
finding-correlations-between-features
interactive-sharing
motivation-7
interactive-quickstart
isee-examples
quality-control-1
annotation-of-cell-populations
querying-features-of-interest
reproducible-visualizations
dissemination
additional-resources
dealing-with-big-data
motivation-8
fast-approximations
nearest-neighbor-searching
big-data-svd
parallelization
out-of-memory-representations