Evidence map›Paper›PMID 30602090›Full record

ArticleGenomics & informatics2018

A Universal Analysis Pipeline of Hybrid Capture-Based Targeted Sequencing Data with Unique Molecular Indexes (UMIs).

Min-Jung Kim, Si-Cho Kim, Young-Joon Kim

Abstract read
In one paragraph

Article in Genomics & informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. 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

3 authors.

Min-Jung KimDepartment of Integrated Omics and Biomedical Science, Yonsei University, Seoul 03722, Korea.
Si-Cho KimDepartment of Biochemistry, Yonsei University 03722, Seoul, Korea.
Young-Joon KimDepartment of Integrated Omics and Biomedical Science, Yonsei University, Seoul 03722, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hybrid capture-based targeted sequencing is increasingly used for genomic variants profiling in tumor patients. Unique molecular index (UMI) technology has recently been developed and helps to increase the accuracy of variant calling by minimizing PCR biases and sequencing errors. However, UMI-adopted targeted sequencing data analysis is slightly different from the methods for other types of omics data, and its pipeline for variant calling is still being optimized in various studying groups for their own purpose. Due to this provincial usage range of tools, our group built an analysis pipeline for global application to many studies of targeted sequencing generated with different methods. First, we generated hybrid capture-based data using genomic DNA extracted from tumor tissues of colorectal cancer patients. Sequencing libraries were prepared, pooled together and an 8-plexed capture library was processed to the enrichment step before 150bp paired-end (PE) sequencing with Illumina Hiseq series. For the analysis, we evaluated several different tools published. We mainly focused on the compatibility of input and output of each tool. Finally, our laboratory built an analysis pipeline specialized for UMI-adopted data. Through this pipeline, we were able to estimate the even on-target rates and filtered consensus reads for more accurate variant calling. These results suggest the potential of our analysis pipeline in the precise examination of quality and efficiency of conducted experiments.

Indexed as

Hybrid captureprecision medicinetargeted sequencingUMIvariant calling

Identifiers

PMID30602090
PMCPMC6440665

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LicenceCC BY-NC
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Registered trials

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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.