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. Author manuscript; available in PMC: 2021 Sep 1.
Published in final edited form as: Cell Rep. 2021 Aug 24;36(8):109575. doi: 10.1016/j.celrep.2021.109575

KEY RESOURCES TABLE

REAGENT or RESOURCE SOURCE IDENTIFIER
Antibodies
Rabbit polyclonal anti-H3 acetyl-K27 Active Motif Cat# 39133; RRID:AB_2561016
Chemicals, peptides, and recombinant proteins
Recombinant Protein G Agarose Invitrogen Cat# 15920-010
Proteinase K Invitrogen Cat# 25530-049
RNase A Roche Cat# 10109169001
γ-Secretase Inhibitor XXI (compound E) Calbiochem Cat# 565790
RPMI 1640 Corning Cat# 10-040-CM
HyClone Fetal bovine serum Thermo Fisher Scientific Cat# SH30070.03
L-glutamine Corning Cat# 25-005-CI
Penicillin-Streptomycin Corning Cat# 30-002-CI
MEM Non-Essential Amino Acids GIBCO Cat# 11140-050
Sodium Pyruvate GIBCO Cat# 11360-070
Glycine Invitrogen Cat# 15527-013
Pierce 16% Formaldehyde Thermo Fisher Scientific Cat# 28908
Trizma Hydrochloride Solution, pH 7.4 Sigma-Aldrich Cat# T2194-100ml
Sodium Chloride Solution, 5M Sigma-Aldrich Cat# 59222C-500ml
Magnesium Chloride Solution, 1M Sigma-Aldrich Cat# M1028-100ml
Nonidet P40 Substitute Sigma-Aldrich Cat# 74385-5l
MACS BSA Stock Solution Miltenyi Biotec Cat# 130-091-376
Flowmi Cell Strainer, 40 mm Bel-Art Cat# H13680-0040
Digitonin Thermo Fisher Scientific Cat# BN2006
Dulbecco’s Phosphate-Buffered Salt Solution 1X Corning Cat# 21031CV
Critical commercial assays
KAPA Library Quant Kit Roche Cat# KK4824
D1000 ScreenTape Agilent Cat# 5067-5582
D1000 Reagents Agilent Cat# 5067-5583
High Sensitivity D1000 ScreenTape Agilent Cat# 5067-5584
High Sensitivity D1000 Reagents Agilent Cat# 5067-5585
QIAquick PCR Purification Kit QIAGEN Cat# 28106
NEBNext Ultra II DNA Library Prep Kit NEB Cat# E7645S
Chromium Single Cell ATAC Library & Gel Bead Kit, 4 rxns 10X GENOMICS Cat# PN-1000111
Chromium i7 Multiplex Kit N, Set A 10X GENOMICS Cat# PN-1000084
Chromium Chip E Single Cell ATAC Kit, 48 rxns 10X GENOMICS Cat# PN-1000082
NextSeq® 500/550 High Output Kit v2 (75 cycles) Illumina Cat# FC-404-2005
NextSeq® 500/550 High Output Kit v2 (150 cycles) Illumina Cat# FC-404-2002
Deposited data
Raw and analyzed scATAC-seq data This paper GEO: GSE155916
Raw and analyzed ChIP-seq data This paper GEO: GSE171098
Bulk ATAC-seq of purified progenitor and differentiated hematopoietic cells Yoshida et al., 2019; https://doi.org/10.1016/j.cell.2018.12.036 GEO: GSE100738
10x Genomics scATAC-seq of CD34\textsuperscript{+} hematopoietic progenitor cells Satpathy et al., 2019; https://doi.org/10.1038/s41587-019-0206-z GEO: GSE129785
Fluidigm C1 scATAC-seq of CD34\textsuperscript{+} hematopoietic progenitor cells Buenrostro et al., 2018; https://doi.org/10.1016/j.cell.2018.03.074 GEO: GSE96769
sciATAC-seq of murine marrow and spleen cells Cusanovich et al., 2018; https://doi.org/10.1016/j.cell.2018.06.052 GEO: GSE111586
scRNA-seq of GSI-resistant DND-41 cells Schwartz et al., 2020; https://doi.org/10.1038/s41592-020-0748-5 GEO: GSE138892
Experimental models: Cell lines
DND-41 DSMZ ACC 525
Software and algorithms
APEC v1.2.2 Li et al., 2020; https://doi.org/10.1186/s13059-020-02034-y https://github.com/QuKunLab/APEC
Cicero v1.9.1 Pliner et al., 2018; https://doi.org/10.1016/j.molcel.2018.06.044 https://github.com/cole-trapnell-lab/cicero-release
CisTopic v0.3.0 Bravo González-Blas et al., 2019; https://doi.org/10.1038/s41592-019-0367-1 https://github.com/aertslab/cisTopic
Cusanovich2018 Cusanovich et al., 2018; https://doi.org/10.1016/j.cell.2018.06.052 This paper https://github.com/faryabib/CellReports_TooManyPeaks_analysis
EpiScanpy v0.3.0 Danese et al., 2019; https://doi.org/10.1101/648097 https://github.com/colomemaria/epiScanpy
Seurat v3.2.3 Butler et al., 2018; https://doi.org/10.1038/nbt.4096 https://github.com/satijalab/seurat
Signac v1.1.0 Stuart et al., 2020; https://doi.org/10.1101/2020.11.09.373613 https://github.com/timoast/signac
SnapATAC v1.0.0 Fang et al., 2021; https://doi.org/10.1038/s41467-021-21583-9 https://github.com/r3fang/SnapATAC
tsne v0.1.3 van der Maaten and Hinton, 2008 https://github.com/jdonaldson/rtsne/
TooManyPeaks v2.2.0.0 This paper https://doi.org/10.5281/zenodo.5130671 https://github.com/faryabib/too-many-cells#too-many-peaks
TooManyPeaks analysis code This paper https://doi.org/10.5281/zenodo.5130655 https://github.com/faryabib/CellReports_TooManyPeaks_analysis
R wrapper for TooManyCells v0.1.1.0 Schwartz et al., 2020; https://doi.org/10.1038/s41592-020-0748-5 https://github.com/GregorySchwartz/tooManyCellsR
umap-learn v0.4.6 McInnes et al., 2018; https://doi.org/10.21105/joss.00861 https://github.com/lmcinnes/
HOMER v4.9 Heinz et al., 2010; https://doi.org/10.1016/j.molcel.2010.05.004 http://homer.ucsd.edu/homer
bedtools v2.30.0 Quinlan and Hall, 2010; https://doi.org/10.1093/bioinformatics/btq033 http://bedtools.readthedocs.io/en/stable
BWAv0.7.13 Li and Durbin, 2009; https://doi.org/10.1093/bioinformatics/btp324 http://bio-bwa.sourceforge.net
Cell Ranger ATAC v1.2.0 Satpathy et al., 2019; https://doi.org/10.1038/s41587-019-0206-z https://support.10xgenomics.com/single-cell-atac/software/pipelines/latest/what-is-cell-ranger-atac
Picard v2.1.0 Broad Institute https://github.com/broadinstitute/picard
Trim Galore v0.4.1 Babraham Bioinformatics https://www.bioinformatics.babraham.ac.uk/projects/trim_galore
UCSC tools v404 Kent et al., 2010; https://doi.org/10.1093/bioinformatics/btq351 https://github.com/ucscGenomeBrowser/kent