[{"innerBlocks":[],"name":"core\/freeform","postId":1403,"blockType":{"name":"core\/freeform","keywords":[],"attributes":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"providesContext":[],"usesContext":[],"selectors":[],"supports":{"className":false,"customClassName":false,"reusable":false},"styles":[],"variations":[],"apiVersion":3,"title":"Classic","description":"Use the classic WordPress editor.","category":"text"},"originalContent":"A computational technique used to block unwanted files and messages as a form of access or spam control has proven to be a novel method for streamlining the identification of genetic drivers of disease.

The approach, called blacklisting, has been leveraged by researchers at the Icahn School of Medicine at Mount Sinai and The Rockefeller University as a filter to single out genetic variations in patient genomes and exomes that do not cause illness.

\u201cUntil now, there has been no viable published method for filtering out non-pathogenic variants that are common in human genomes and absent from current genomic databases,\u201d said Yuval Itan, assistant professor of genetics and genomic sciences at the Icahn School of Medicine. \u201cUsing the blacklist, researchers will now be able to remove genetic \u2018noise\u2019 and focus on true disease-causing mutations.\u201d

Also See<\/b>: Geisinger to make DNA sequencing a part of routine clinical care<\/a>

Itan and his colleagues co-authored a paper<\/a> describing the technique in the December issue of Proceedings of the National Academy of Science of the United States of America<\/i>.

\u201cComputational analyses of human patient exomes aim to filter out as many nonpathogenic genetic variants as possible, without removing the true disease-causing mutations,\u201d according to the authors. \u201cThis involves comparing the patient\u2019s exome with public databases to remove reported variants inconsistent with disease prevalence, mode of inheritance, or clinical penetrance.\u201d

However, they contend that their work using the blacklisting computational technique \u201cdemonstrates the power of extracting variant blacklists from private databases as a specific in-house but broadly applicable tool for optimizing exome analysis.\u201d

Researchers have developed a program, called ReFiNE, as well as an associated web server that others can use to automate the creation of their own blacklists.

Ultimately, Itan hopes that the tool will help clinicians to conduct more accurate and rapid genetic analyses than the traditional cumbersome process of sifting through large amounts of data, thereby accelerating the pace of genomic medicine.
","saveContent":"A computational technique used to block unwanted files and messages as a form of access or spam control has proven to be a novel method for streamlining the identification of genetic drivers of disease.

The approach, called blacklisting, has been leveraged by researchers at the Icahn School of Medicine at Mount Sinai and The Rockefeller University as a filter to single out genetic variations in patient genomes and exomes that do not cause illness.

\u201cUntil now, there has been no viable published method for filtering out non-pathogenic variants that are common in human genomes and absent from current genomic databases,\u201d said Yuval Itan, assistant professor of genetics and genomic sciences at the Icahn School of Medicine. \u201cUsing the blacklist, researchers will now be able to remove genetic \u2018noise\u2019 and focus on true disease-causing mutations.\u201d

Also See<\/b>: Geisinger to make DNA sequencing a part of routine clinical care<\/a>

Itan and his colleagues co-authored a paper<\/a> describing the technique in the December issue of Proceedings of the National Academy of Science of the United States of America<\/i>.

\u201cComputational analyses of human patient exomes aim to filter out as many nonpathogenic genetic variants as possible, without removing the true disease-causing mutations,\u201d according to the authors. \u201cThis involves comparing the patient\u2019s exome with public databases to remove reported variants inconsistent with disease prevalence, mode of inheritance, or clinical penetrance.\u201d

However, they contend that their work using the blacklisting computational technique \u201cdemonstrates the power of extracting variant blacklists from private databases as a specific in-house but broadly applicable tool for optimizing exome analysis.\u201d

Researchers have developed a program, called ReFiNE, as well as an associated web server that others can use to automate the creation of their own blacklists.

Ultimately, Itan hopes that the tool will help clinicians to conduct more accurate and rapid genetic analyses than the traditional cumbersome process of sifting through large amounts of data, thereby accelerating the pace of genomic medicine.
","order":0,"get_parent":{},"attributes":[],"attributesType":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"dynamicContent":""}]

Blacklisting computing proves valuable for genetic analysis

More for you