Evidence map›Paper›PMID 22011106›Full record

ArticleBMC bioinformatics2011

Mitochondrial genome sequence analysis: a custom bioinformatics pipeline substantially improves Affymetrix MitoChip v2.0 call rate and accuracy.

Hongbo M Xie, Juan C Perin, Theodore G Schurr, Matthew C Dulik, Sergey I Zhadanov, Joseph A Baur, Michael P King, Emily Place, Colleen Clarke, Michael Grauer and 8 more

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
0.5field-weighted citation impact, top 34% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 24 citations in OpenAlex.

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  13. Mitochondrial DNA Haplogroups and Neurocognitive Impairment During HIV Infection.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2015
    Observational
  14. Contribution of non-reference alleles in mtDNA of Alzheimer's disease patients.Annals of clinical and translational neurology · 2014
    Article
  15. Review
  16. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors at 4 institutions in 2 countries.

Hongbo M XieCenter for Biomedical Informatics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
Juan C Perin
Theodore G Schurr
Matthew C Dulik
Sergey I Zhadanov
Joseph A Baur
Michael P King
Emily Place
Colleen Clarke
Michael Grauer
Jonathan Schug
Avni Santani
Anthony Albano
Cecilia Kim
Vincent Procaccio
Hakon Hakonarson
Xiaowu Gai
Marni J Falk
Children's Hospital of Philadelphia · USUniversity of Pennsylvania · USThomas Jefferson University · USUniversité d'Angers · FR

Funding

Pharmacologic treatment of mitochondrial complex I dysfunction in C. elegansR01HD065858 · NICHD · CHILDREN'S HOSP OF PHILADELPHIA · PI FALK, MARNI J · 2010 to 2014
$2.0M
Transcriptional Profiling of Metabolic Pathways in Mitochondrial DiseaseR03DK082521 · NIDDK · CHILDREN'S HOSP OF PHILADELPHIA · PI FALK, MARNI J · 2009 to 2010
$157k
NICHD NIH HHS R01 HD065858NIDDK NIH HHS R03 DK082521NIDDK NIH HHS R03-DK082521
6 · The paper itself

Abstract

backgroundMitochondrial genome sequence analysis is critical to the diagnostic evaluation of mitochondrial disease. Existing methodologies differ widely in throughput, complexity, cost efficiency, and sensitivity of heteroplasmy detection. Affymetrix MitoChip v2.0, which uses a sequencing-by-genotyping technology, allows potentially accurate and high-throughput sequencing of the entire human mitochondrial genome to be completed in a cost-effective fashion. However, the relatively low call rate achieved using existing software tools has limited the wide adoption of this platform for either clinical or research applications. Here, we report the design and development of a custom bioinformatics software pipeline that achieves a much improved call rate and accuracy for the Affymetrix MitoChip v2.0 platform. We used this custom pipeline to analyze MitoChip v2.0 data from 24 DNA samples representing a broad range of tissue types (18 whole blood, 3 skeletal muscle, 3 cell lines), mutations (a 5.8 kilobase pair deletion and 6 known heteroplasmic mutations), and haplogroup origins. All results were compared to those obtained by at least one other mitochondrial DNA sequence analysis method, including Sanger sequencing, denaturing HPLC-based heteroduplex analysis, and/or the Illumina Genome Analyzer II next generation sequencing platform.

resultsAn average call rate of 99.75% was achieved across all samples with our custom pipeline. Comparison of calls for 15 samples characterized previously by Sanger sequencing revealed a total of 29 discordant calls, which translates to an estimated 0.012% for the base call error rate. We successfully identified 4 known heteroplasmic mutations and 24 other potential heteroplasmic mutations across 20 samples that passed quality control.

conclusionsAffymetrix MitoChip v2.0 analysis using our optimized MitoChip Filtering Protocol (MFP) bioinformatics pipeline now offers the high sensitivity and accuracy needed for reliable, high-throughput and cost-efficient whole mitochondrial genome sequencing. This approach provides a viable alternative of potential utility for both clinical diagnostic and research applications to traditional Sanger and other emerging sequencing technologies for whole mitochondrial genome analysis.

Indexed as

Genome, MitochondrialComputational BiologyGenome, HumanHumansMitochondriaMutationSequence Analysis, DNA

Identifiers

PMID22011106
PMCPMC3234255
OpenAlexW2070682107

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.