Evidence map›Paper›PMID 25823460›Full record

ArticleGenome research2015

Accurate typing of short tandem repeats from genome-wide sequencing data and its applications.

Arkarachai Fungtammasan, Guruprasad Ananda, Suzanne E Hile, Marcia Shu-Wei Su, Chen Sun, Robert Harris, Paul Medvedev, Kristin Eckert, Kateryna D Makova

Open access · bronzeAbstract read
In one paragraph

Article in Genome research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed
–field-weighted citation impact
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

60 citing papers in PubMed, 109 citations in OpenAlex.

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  9. Tracking Somatic Mutations for Lineage Reconstruction.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  10. Microsatellites explorer: A database of short tandem repeats across genomes.Computational and structural biotechnology journal · 2024
    Article
  11. Article
  12. Heterodisomy in theFrontiers in endocrinology · 2024
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  14. Review
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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

9 authors at 1 institution in 1 country.

Arkarachai FungtammasanIntegrative Biosciences, Bioinformatics and Genomics Option, Pennsylvania State University, University Park, Pennsylvania 16802, USA; Department of Biology, Pennsylvania State University, University Park, Pennsylvania 16802, USA; Center for Medical Genomics, Pennsylvania State University, University Park, Pennsylvania 16802, USA; The Genome Science Institute at the Huck Institutes of Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA;
Guruprasad AnandaIntegrative Biosciences, Bioinformatics and Genomics Option, Pennsylvania State University, University Park, Pennsylvania 16802, USA; Center for Medical Genomics, Pennsylvania State University, University Park, Pennsylvania 16802, USA; The Genome Science Institute at the Huck Institutes of Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA; Department of Biochemistry and Molecular Biology, Pennsylvania State University, Pennsylvania 16802, USA;
Suzanne E HileCenter for Medical Genomics, Pennsylvania State University, University Park, Pennsylvania 16802, USA; Department of Pathology, The Jake Gittlen Laboratories for Cancer Research, Pennsylvania State University College of Medicine, Hershey, Pennsylvania 17033, USA;
Marcia Shu-Wei SuDepartment of Biology, Pennsylvania State University, University Park, Pennsylvania 16802, USA; Center for Medical Genomics, Pennsylvania State University, University Park, Pennsylvania 16802, USA;
Chen SunDepartment of Computer Science and Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, USA.
Robert HarrisDepartment of Biology, Pennsylvania State University, University Park, Pennsylvania 16802, USA;
Paul MedvedevCenter for Medical Genomics, Pennsylvania State University, University Park, Pennsylvania 16802, USA; The Genome Science Institute at the Huck Institutes of Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA; Department of Biochemistry and Molecular Biology, Pennsylvania State University, Pennsylvania 16802, USA; Department of Computer Science and Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, USA.
Kristin EckertCenter for Medical Genomics, Pennsylvania State University, University Park, Pennsylvania 16802, USA; Department of Pathology, The Jake Gittlen Laboratories for Cancer Research, Pennsylvania State University College of Medicine, Hershey, Pennsylvania 17033, USA;
Kateryna D MakovaDepartment of Biology, Pennsylvania State University, University Park, Pennsylvania 16802, USA; Center for Medical Genomics, Pennsylvania State University, University Park, Pennsylvania 16802, USA; The Genome Science Institute at the Huck Institutes of Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA;
Pennsylvania State University · US

Funding

Computational and Biochemical Analysis of Microsatellite Life CycleR01GM087472 · NIGMS · PENNSYLVANIA STATE UNIVERSITY, THE · PI ECKERT, KRISTIN A, MAKOVA, KATERYNA · 2009 to 2012
$1.4M
NIGMS NIH HHS R01 GM087472NIGMS NIH HHS R01-GM087472
6 · The paper itself

Abstract

Short tandem repeats (STRs) are implicated in dozens of human genetic diseases and contribute significantly to genome variation and instability. Yet profiling STRs from short-read sequencing data is challenging because of their high sequencing error rates. Here, we developed STR-FM, short tandem repeat profiling using flank-based mapping, a computational pipeline that can detect the full spectrum of STR alleles from short-read data, can adapt to emerging read-mapping algorithms, and can be applied to heterogeneous genetic samples (e.g., tumors, viruses, and genomes of organelles). We used STR-FM to study STR error rates and patterns in publicly available human and in-house generated ultradeep plasmid sequencing data sets. We discovered that STRs sequenced with a PCR-free protocol have up to ninefold fewer errors than those sequenced with a PCR-containing protocol. We constructed an error correction model for genotyping STRs that can distinguish heterozygous alleles containing STRs with consecutive repeat numbers. Applying our model and pipeline to Illumina sequencing data with 100-bp reads, we could confidently genotype several disease-related long trinucleotide STRs. Utilizing this pipeline, for the first time we determined the genome-wide STR germline mutation rate from a deeply sequenced human pedigree. Additionally, we built a tool that recommends minimal sequencing depth for accurate STR genotyping, depending on repeat length and sequencing read length. The required read depth increases with STR length and is lower for a PCR-free protocol. This suite of tools addresses the pressing challenges surrounding STR genotyping, and thus is of wide interest to researchers investigating disease-related STRs and STR evolution.

Indexed as

AlgorithmsGenome, HumanMicrosatellite RepeatsBase SequenceGenotyping TechniquesHumansMolecular Sequence DataSensitivity and SpecificitySequence Analysis, DNA

Identifiers

PMID25823460
PMCPMC4417121
OpenAlexW2121427560

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.