External data

In scTHI: Indentification of significantly activated ligand-receptor interactions across clusters of cells from single-cell RNA sequencing data

knitr::opts_chunk$set(echo = TRUE)

Interaction table

The object interaction_table contains a list of 2,548 pairs of ligand and receptors. Data has been collected curating publicly available resources from:

• Ramilowski JA, Goldberg T, Harshbarger J, Kloppmann E, Lizio M, Satagopam VP, et al. A draft network of ligand-receptor-mediated multicellular signalling in human. Nat Commun. 2015;6:7866. doi:10.1038/ncomms8866.

• Vento-Tormo R, Efremova M, Botting RA, Turco MY, Vento-Tormo M, Meyer KB, et al. Single-cell reconstruction of the early maternal-fetal interface in humans. Nature. 2018;563:347–53. doi:10.1038/s41586-018-0698-6.

The curated list is composed of known and novel literature-supported interactions and includes both heteromeric and monomeric ligands/receptors mainly related to chemokine, cytokine, growth factors, integrin, TGF and TNF family members, semaphorins, ephrins, Wnt and Notch signalings..

Signatures

The object signatures contains a list of 295 cell-type specific signatures, including the Immune and Central Nervous Systems. Data has been collected integrating a cureted collection of marker genes and a set of signatures available from public databases and published studies, as:

• a compendium of 64 human cell types signatures including lymphoid, myeloid, stromal, tissue-specific and stem cells, collected from FANTOM5, ENCODE, Blueprint and Gene Expression Omnibus (GEO) data portals;

• a set of markers for 30 immune cell types, including myeloid and lymphoid subpopulations identified from Peripheral Blood Mononuclear Cells (PBMCs) [1];

• a set of Central Nervous System cell signatures including astrocytes, neuron, oligodendrocytes, microglia, and endothelial cells [2];

• a set of 53 signatures corresponding to 26 different cell types [3-6]

• two gene expression programs related to microglia and bone marrow-derived macrophages in gliomas [7].

The object signaturesColors is a data.frame including a list of colors for signatures.

References

[1] Butler A, Hoffman P, Smibert P, Papalexi E, Satija R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat Biotechnol. 2018;36:411–20. doi:10.1038/nbt.4096.

[2] Zhang Y, Chen K, Sloan SA, Bennett ML, Scholze AR, O’Keeffe S, et al. An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J Neurosci. 2014;34:11929–47. doi:10.1523/JNEUROSCI.1860-14.2014.

[3] Bindea G, Mlecnik B, Tosolini M, Kirilovsky A, Waldner M, Obenauf AC, et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity. 2013;39:782–95. doi:10.1016/j.immuni.2013.10.003.

[4] Charoentong P, Finotello F, Angelova M, Mayer C, Efremova M, Rieder D, et al. Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade. Cell Rep. 2017;18:248–62. doi:10.1016/j.celrep.2016.12.019.

[5] Rooney MS, Shukla SA, Wu CJ, Getz G, Hacohen N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell. 2015;160:48–61. doi:10.1016/j.cell.2014.12.033.

[6] Tirosh I, Izar B, Prakadan SM, Wadsworth MH, Treacy D, Trombetta JJ, et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science. 2016;352:189–96. doi:10.1126/science.aad0501.

[7] Venteicher AS, Tirosh I, Hebert C, Yizhak K, Neftel C, Filbin MG, et al. Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq. Science. 2017;355. doi:10.1126/science.aai8478.

scTHI documentation built on Nov. 8, 2020, 7:37 p.m.