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{
"copyright_text": null,
"description": "PAR-CLIP, a CLIP-seq protocol, derives a transcriptome wide set of binding sites for RNA-binding proteins. Even though the protocol uses stringent washing to remove experimental noise, some of it remains. A recent study measured three sets of non-specific RNA backgrounds which are present in several PAR-CLIP datasets. However, a tool to identify the presence of common background in PAR-CLIP datasets is not yet available. In this talk I will introduce a tool that uses this score to identify the amount of common backgrounds present in a PAR-CLIP dataset, and we provide the user the option to use or remove it. My team used the proposed strategy in 30 PAR-CLIP datasets from nine proteins. It is possible to identify the presence of common backgrounds in a dataset and identify differences in datasets for the same protein. This method is the first step in the process of completely removing such backgrounds.",
"duration": 1858,
"language": "spa",
"recorded": "2019-10-10",
"related_urls": [
{
"label": "Conference schedule",
"url": "https://conf.scipyla.org/en/program/schedule/"
}
],
"speakers": [
"Carlos Sierra"
],
"tags": [],
"thumbnail_url": "https://i.ytimg.com/vi/pi3ekjEwJHg/maxresdefault.jpg",
"title": "BackCLIP: a tool to identify common background presence in PAR-CLIP datasets",
"videos": [
{
"type": "youtube",
"url": "https://www.youtube.com/watch?v=pi3ekjEwJHg"
}
]
}
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