Life Science Alliance,
Год журнала:
2022,
Номер
6(1), С. e202201701 - e202201701
Опубликована: Дек. 16, 2022
Spatial
transcriptomics
extends
single-cell
RNA
sequencing
(scRNA-seq)
by
providing
spatial
context
for
cell
type
identification
and
analysis.
Imaging-based
technologies
such
as
multiplexed
error-robust
fluorescence
in
situ
hybridization
(MERFISH)
can
achieve
resolution,
directly
mapping
identities
to
positions.
MERFISH
produces
a
different
data
than
scRNA-seq,
technical
comparison
between
the
two
modalities
is
necessary
ascertain
how
best
integrate
them.
We
performed
on
mouse
liver
kidney
compared
resulting
bulk
statistics
with
those
from
Tabula
Muris
Senis
atlas
Visium
datasets.
quantitatively
reproduced
RNA-seq
scRNA-seq
results
improvements
overall
dropout
rates
sensitivity.
Finally,
we
found
that
independently
resolved
distinct
types
structure
both
kidney.
Computational
integration
did
not
enhance
these
results.
conclude
provides
comparable
method
gene
expression
identify
without
need
computational
atlases.
Cell,
Год журнала:
2023,
Номер
186(26), С. 5876 - 5891.e20
Опубликована: Дек. 1, 2023
Harmonizing
cell
types
across
the
single-cell
community
and
assembling
them
into
a
common
framework
is
central
to
building
standardized
Human
Cell
Atlas.
Here,
we
present
CellHint,
predictive
clustering
tree-based
tool
resolve
cell-type
differences
in
annotation
resolution
technical
biases
datasets.
CellHint
accurately
quantifies
cell-cell
transcriptomic
similarities
places
relationship
graph
that
hierarchically
defines
shared
unique
subtypes.
Application
multiple
immune
datasets
recapitulates
expert-curated
annotations.
also
reveals
underexplored
relationships
between
healthy
diseased
lung
states
eight
diseases.
Furthermore,
workflow
for
fast
cross-dataset
integration
guided
by
harmonized
hierarchy,
which
uncovers
underappreciated
adult
human
hippocampus.
Finally,
apply
12
tissues
from
38
datasets,
providing
deeply
curated
cross-tissue
database
with
∼3.7
million
cells
various
machine
learning
models
automatic
tissues.
Nature Cell Biology,
Год журнала:
2023,
Номер
unknown
Опубликована: Фев. 2, 2023
Abstract
The
increasing
availability
of
large-scale
single-cell
atlases
has
enabled
the
detailed
description
cell
states.
In
parallel,
advances
in
deep
learning
allow
rapid
analysis
newly
generated
query
datasets
by
mapping
them
into
reference
atlases.
However,
existing
data
transformations
learned
to
map
are
not
easily
explainable
using
biologically
known
concepts
such
as
genes
or
pathways.
Here
we
propose
expiMap,
a
informed
deep-learning
architecture
that
enables
mapping.
ExpiMap
learns
cells
understandable
components
representing
‘gene
programs’.
activity
each
for
gene
program
is
while
simultaneously
refining
and
de
novo
programs.
We
show
expiMap
compares
favourably
methods
bringing
an
additional
layer
interpretability
integrative
analysis.
Furthermore,
demonstrate
its
applicability
analyse
perturbation
responses
different
tissues
species
resolve
patients
who
have
coronavirus
disease
2019
treatments
across
types.
Immunity,
Год журнала:
2024,
Номер
57(2), С. 379 - 399.e18
Опубликована: Янв. 31, 2024
Palatine
tonsils
are
secondary
lymphoid
organs
(SLOs)
representing
the
first
line
of
immunological
defense
against
inhaled
or
ingested
pathogens.
We
generated
an
atlas
human
tonsil
composed
>556,000
cells
profiled
across
five
different
data
modalities,
including
single-cell
transcriptome,
epigenome,
proteome,
and
immune
repertoire
sequencing,
as
well
spatial
transcriptomics.
This
census
identified
121
cell
types
states,
defined
developmental
trajectories,
enabled
understanding
functional
units
tonsil.
Exemplarily,
we
stratified
myeloid
slan-like
subtypes,
established
a
BCL6
enhancer
locally
active
in
follicle-associated
T
B
cells,
SIX5
putative
transcriptional
regulator
plasma
maturation.
Analyses
validation
cohort
confirmed
presence,
annotation,
markers
tonsillar
provided
evidence
age-related
compositional
shifts.
demonstrate
value
this
resource
by
annotating
from
cell-derived
mantle
lymphomas,
linking
heterogeneity
to
normal
differentiation
states
Cell,
Год журнала:
2024,
Номер
187(10), С. 2343 - 2358
Опубликована: Май 1, 2024
As
the
number
of
single-cell
datasets
continues
to
grow
rapidly,
workflows
that
map
new
data
well-curated
reference
atlases
offer
enormous
promise
for
biological
community.
In
this
perspective,
we
discuss
key
computational
challenges
and
opportunities
reference-mapping
algorithms.
We
how
mapping
algorithms
will
enable
integration
diverse
across
disease
states,
molecular
modalities,
genetic
perturbations,
species
eventually
replace
manual
laborious
unsupervised
clustering
pipelines.
Cell Genomics,
Год журнала:
2024,
Номер
4(2), С. 100473 - 100473
Опубликована: Янв. 3, 2024
CD4+
T
cells
are
key
mediators
of
various
autoimmune
diseases;
however,
their
role
in
disease
progression
remains
unclear
due
to
cellular
heterogeneity.
Here,
we
evaluated
cell
subpopulations
using
decomposition-based
transcriptome
characterization
and
canonical
clustering
strategies.
This
approach
identified
12
independent
gene
programs
governing
whole
heterogeneity,
which
can
explain
the
ambiguity
clustering.
In
addition,
performed
a
meta-analysis
public
single-cell
datasets
over
1.8
million
peripheral
from
953
individuals
by
projecting
onto
reference
cataloging
frequency
qualitative
alterations
populations
20
diseases.
The
analyses
revealed
that
transcriptional
were
useful
characterizing
each
predicting
its
clinical
status.
Moreover,
genetic
variants
associated
with
diseases
showed
disease-specific
enrichment
within
programs.
results
collectively
provide
landscape
transcriptomes
involved
disease.
