TITLE:  Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) inference based on single cell copy number profile
AUTHORS: Fang Wang, Qihan Wang, Vakul Mohanty, Shaoheng Liang, Jinzhuang Dou, Jincheng Han, Darlan Conterno Minussi, Ruli Gao, Li Ding, Nicholas Navin, Ken Chen

[DESCRIPTION]
<div class = "text-blocks"><div class = "text-block"><div class = "justify" style = "text-align:justify">This protocol describes two innovative algorithms:</div><style>
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							</style></div><div class = "text-block"><div class = "justify" style = "text-align:justify">1) A minimal event distance aneuploidy lineage tree (MEDALT) inference algorithm allows implementing genetically meaningful distances and is scalable to current single-cell datasets containing thousands of cells, and</div><style>
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							</style></div><div class = "text-block"><div class = "justify" style = "text-align:justify">2) A statistical routine, Lineage Speciation Analysis (LSA), enables prioritization of CNAs and genes that are non-randomly associated with the observed lineage expansion and thereby are potentially functionally important.</div><style>
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[STEPS]
?. Install Python 2.7 and R 3.5Download MEDALT tool from https://github.com/KChen-lab/MEDALT.gitExtract input dataset
?. Decompress gzipped files (MEDALT-1.0.tar.gz)
?. Run the example data generated based on single cell DNA sequencing technology
R packages (igraph, HelloRanges and DescTools) are loaded.
Three text files are expected:(1) CNV.tree.txt which is an rooted directed tree including three columns: parent node, child node and distance.(2) segmental.LSA.txt which includes broad CNAs significantly associated with lineage expansion.(3) gene.LSA.txt which includes focal (gene) CNAs significantly associated with lineage expansion.Two figures are also expected:(1) singlecell.tree.pdf which is a visualization of MEDALT by igraph. You also can input CNV.tree.txt into Cytoscape to generate preferred visualization. (2) LSA.tree.pdf which is a visualization of identified CNAs by igraph.
We run the example data only through permuting copy number profile instead of reconstructing tree based on permuted copy number profile. The seting can be changed via -R T.
?. Run the example data inferred using inferCNV based on single cell RNA sequencing technology
Three text files are expected:(1) CNV.tree.txt which is an rooted directed tree including three columns: parent node, child node and distance.(2) segmental.LSA.txt which includes broad CNAs significantly associated with lineage expansion.(3) gene.LSA.txt which includes focal (gene) CNAs significantly associated with lineage expansion.Two figures are also expected:(1) singlecell.tree.pdf which is a visualization of MEDALT by igraph. (2) LSA.tree.pdf which is a visualization of identified CNAs by igraph.