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Carlo Sidore

dblp:53/11141 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics
genome analysis
0.312017
fastMitoCalc: an ultra-fast program to estimate mitochondrial DNA copy number from whole-genome sequences · Bioinform. 2017
Bioinformatics and computational biology › statistical genetics
genetic association study
0.112017
fastMitoCalc: an ultra-fast program to estimate mitochondrial DNA copy number from whole-genome sequences · Bioinform. 2017
Bioinformatics and computational biology › statistical genetics › association analysis
quantitative trait association
0.112017
fastMitoCalc: an ultra-fast program to estimate mitochondrial DNA copy number from whole-genome sequences · Bioinform. 2017

Methods — techniques the papers use, named apart from their topics

sequencing coverage estimation · 0.3
YearPublicationVenuePosition
2017 fastMitoCalc: an ultra-fast program to estimate mitochondrial DNA copy number from whole-genome sequences
abstract
Abstract Mitochondrial DNA (mtDNA) copy number is tightly regulated in tissues, and is both a critical determinant of mitochondrial function and a potential biomarker for disease. We and other groups have shown that the mtDNA copy number per cell can be directly estimated from whole-genome sequencing. The computation is based on the rationale that sequencing coverage should be proportional to the underlying DNA copy number for autosomal and mitochondrial DNA, and most computing time is spent calculating the average autosomal DNA coverage across ∼3 billion bases. That makes analyzing tens of thousands of available samples very slow. Here we present fastMitoCalc, which takes advantage of the indexing of sequencing alignment files and uses a randomly selected small subset (0.1%) of the nuclear genome to estimate autosomal DNA coverage accurately. It is more than 100 times faster than current programs. fastMitoCalc also provides an option to estimate copy number using a single autosomal chromosome, which could also achieve high accuracy but is slower. Using fastMitoCalc, it becomes much more feasible now to conduct analyses on large-scale consortium data to test for association of mtDNA copy number with quantitative traits or nuclear variants. Availability and Implementation fastMitoCalc is available at https://lgsun.irp.nia.nih.gov/hsgu/software/mitoAnalyzer/index.html Supplementary information Supplementary data are available at Bioinformatics online.
Yong Qian, Thomas J. Butler, Krista Opsahl-Ong, Nicholas S. Giroux, Carlo Sidore, Ramaiah Nagaraja, Francesco Cucca, Luigi Ferrucci, Gonçalo R. Abecasis, David Schlessinger
Bioinform.5