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Pedigree based DNA sequencing pipeline for germline genomes of cancer families

Overview of attention for article published in Hereditary Cancer in Clinical Practice, August 2016
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  • High Attention Score compared to outputs of the same age and source (80th percentile)

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9 X users

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Title
Pedigree based DNA sequencing pipeline for germline genomes of cancer families
Published in
Hereditary Cancer in Clinical Practice, August 2016
DOI 10.1186/s13053-016-0058-1
Pubmed ID
Authors

Asta Försti, Abhishek Kumar, Nagarajan Paramasivam, Matthias Schlesner, Calogerina Catalano, Dagmara Dymerska, Jan Lubinski, Roland Eils, Kari Hemminki

Abstract

In the course of our whole-genome sequencing efforts, we have developed a pipeline for analyzing germline genomes from Mendelian types of cancer pedigrees (familial cancer variant prioritization pipeline, FCVPP). The variant calling step distinguishes two types of genomic variants: single nucleotide variants (SNVs) and indels, which undergo technical quality control. Mendelian types of variants are assumed to be rare and variants with frequencies higher that 0.1 % are screened out using human 1000 Genomes (Phase 3) and non-TCGA ExAC population data. Segregation in the pedigree allows variants to be present in affected family members and not in old, unaffected ones. The effectiveness of variant segregation depends on the number and relatedness of the family members: if over 5 third-degree (or more distant) relatives are available, the experience has shown that the number of likely variants is reduced from many hundreds to a few tens. These are then subjected to bioinformatics analysis, starting with the combined annotation dependent depletion (CADD) tool, which predicts the likelihood of the variant being deleterious. Different sets of individual tools are used for further evaluation of the deleteriousness of coding variants, 5' and 3' untranslated regions (UTRs), and intergenic variants. The likelihood of success of the present genomic pipeline in finding novel high- or medium-penetrant genes depends on many steps but first and foremost, the pedigree needs to be reasonably large and the assignments and diagnoses among the members need to be correct.

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The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 37%
Student > Ph. D. Student 6 15%
Student > Bachelor 5 12%
Student > Doctoral Student 3 7%
Student > Master 2 5%
Other 2 5%
Unknown 8 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 22%
Unspecified 6 15%
Agricultural and Biological Sciences 6 15%
Medicine and Dentistry 2 5%
Psychology 2 5%
Other 6 15%
Unknown 10 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 August 2016.
All research outputs
#7,205,554
of 25,374,917 outputs
Outputs from Hereditary Cancer in Clinical Practice
#55
of 260 outputs
Outputs of similar age
#113,930
of 376,055 outputs
Outputs of similar age from Hereditary Cancer in Clinical Practice
#1
of 5 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 260 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 78% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 376,055 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them