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authoredMay 9, 2024··
add index require in readme
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‎README.md

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In a nutshell, **gcap** provides an end-to-end workflow for predicting
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circular amplicon (also known as ecDNA, extra-chromosomal DNA ) in gene level with machine learning approach,
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then classifying cancer samples into different focal amplification (fCNA) types,
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based on input from WES (tumor-normal paired BAM) data,
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based on input from WES (tumor-normal paired BAM, with corresponding `.bai` index files) data,
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allele specific copy number data (e.g., results from [ASCAT](https://github.com/VanLoo-lab/ascat) or [Sequenza](https://cran.r-project.org/package=sequenza)), or even
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absolute integer copy number data (e.g., results from [ABSOLUTE](https://software.broadinstitute.org/cancer/cga/absolute)). The former two data
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sources are preferred as input of **gcap** .

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