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CSV中的人类基因组注释

CSV中的人类基因组注释

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Biology,Healthcare Classification

数据结构 ? 478.09M

    Data Structure ?

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    README.md

    Introduction The human genome contains about 30 billion base pairs, and annotations are created to help scientists to understand and use the genome more effectively. Put it in a simplistic way, the genome could be considered a couple of dozens (chromosomes) of long strings, and we would like to understand the functionality of different regions of it. For example, one kind of annotation could be from position X to position Y in chromosome Z is a gene D. Of course, the reality is much more complicated than this, e.g. one region could be annotated at multiple levels as it could be an exon, which is part of a transcript, which is part of a gene. Genome annotations are usually stored in a GTF (aka. GFF2) or GFT3 format. Those formats are very close to a tabular format (e.g. CSV), but less accessible to people who aren't familiar with it. Here, I transformed one of the latest human genome annotations (GRCh38.92) to a plain CSV, to encourage data scientists who are interested in genomics to explore the structure within the annotations. The transformation is relatively straightforward, and can be found in the [gtf2csv repo](https://github.com/zyxue/gtf2csv), besides a brief description provided , more technical details can found provided at [gtf2csv.py](https://github.com/zyxue/gtf2csv/blob/master/gtf2csv/gtf2csv.py). Acknowledgements The annotation in GTF is downloaded from ftp://ftp.ensembl.org/pub/release-92/gtf/homo_sapiens/Homo_sapiens.GRCh38.92.gtf.gz. Inspiration The human genome annotation is very rich in information, and visualization is one of the keys to understand it. Although several genome browsers (e.g. the [UCSC genome browser](http://genome.ucsc.edu//cgi-bin/hgTracks?db=hg38&position=lastDbPos) and the [Ensembl genome browser](https://uswest.ensembl.org/Homo_sapiens/Gene/Summary?db=core;g=ENSG00000012048;r=17:43044295-43170245)) exists, I thought by providing such information in an easily accessible format to every data scientist in the world, more innovative visualizations and analysis methods would be created and shared, which would benefit everyone.
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