1nature research | reporting summary
October 2018Corresponding author(s): Rani E. GeorgeLast updated by author(s):Jun 13, 2019Reporting Summary
Nature Research wishes to improve the reproducibility of the work that we publish. This form provides structure for consistency and transparency
in reporting. For further information on Nature Research policies, see Authors & Referees and the Editorial Policy Checklist.Statistics
For all statistical analyses, confirm that the following items are present in the figure legend, table legend, main text, or Methods section.n/a Confirmed
The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurementA statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedlyThe statistical test(s) used AND whether they are one- or two-sided
Only common tests should be described solely by name; describe more complex techniques in the Methods section.A description of all covariates testedA description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisonsA full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient)
AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals)For null hypothesis testing, the test statistic (e.g. F, t, r) with confidence intervals, effect sizes, degrees of freedom and P value noted
Give P values as exact values whenever suitable.For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settingsFor hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomesEstimates of effect sizes (e.g. Cohen's d, Pearson's r), indicating how they were calculatedOur web collection on statistics for biologists contains articles on many of the points above.Software and code
Policy information about availability of computer codeData collection Data collection was done with BD CellQuest Pro software (BD Biosciences) for the flow cytometry experiment.
The Cell Ranger Single Cell Software Suite (v1.3) was used to perform sample de-multiplexing, barcode and UMI processing, and singlecell
3 ʹ gene counting for the single cell RNA-sequencing experiment.Data analysis R (v3.1.3), affy (v1.44.0), limma (v3.22.7), Fastqc (v0.11.5), STAR (v2.5.1b_modified), Samtools (v1.3.1), MarkDuplicates (v2.1.1),
deepTools (v2.2.4), MACS2 (v2.1.1), bedGraphToBigWig (v4), R (v3.5.1), Rstudio (v1.1.463), data.table (v1.12.2), trimmomatic (v0.36),
HiC-Pro (v2.10.0), hichipper (v0.7.3), diffloop (v1.10.0), ROSE (v1), HOMER (v2) (http://homer.ucsd.edu/homer/motif/), Biostrings
(v2.50.1),Cell Ranger (v1.3), Scater (v1.10.0), Seurat (v2.3.4), Circlize (v0.4.5), IGV (v2.3.74), FlowJo (v10.0.5) and GraphPad Prism (v7.02).
Custom code is available upon reasonable request.
For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors/reviewers.
We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.Data
Policy information about availability of data
All manuscripts must include a data availability statement. This statement should provide the following information, where applicable:- Accession codes, unique identifiers, or web links for publicly available datasets
- A list of figures that have associated raw data
- A description of any restrictions on data availability
The microarray, ChIP-seq, HiChIP and scRNA-seq datasets generated and analyzed during the current study are available in the Gene Expression Omnibus repository
under accession number GSE103084. The authors declare that all other data supporting the findings of this study are available within the paper and its
Supplementary Information files.