Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing.

Li Tai Fang, Bin Zhu, Yongmei Zhao, Wanqiu Chen, Zhaowei Yang, Liz Kerrigan, Kurt Langenbach, Maryellen de Mars, Charles Lu, Kenneth Idler, Howard Jacob, Yuanting Zheng, Luyao Ren, Ying Yu, Erich Jaeger

September 2021

Synopsis of Social media discussions

The discussions collectively demonstrate high enthusiasm and support for the publication's goal of improving benchmarking in cancer genomics, with posters emphasizing methods, collaborations, and future implications; language like 'big steps,' 'best practice,' and references to prestigious journals highlight the perceived significance and potential of this work.

A
Agreement
 Strong agreement

Most comments express strong support and approval for the importance of establishing standardized reference datasets, emphasizing consensus on its significance.

I
Interest
 High level of interest

Discussions reveal high interest, with multiple posts highlighting the practical applications and advancements in cancer genomics research.

E
Engagement
 High engagement

Posts delve into technical details, praising methods like the SomaticSeq App and referencing influential studies, indicating deep engagement.

I
Impact
 High level of impact

The coverage reflects recognition of the publication's potential to standardize practices and improve cancer mutation detection, showcasing a high perceived impact.

Social Mentions

YouTube

2 Videos

Twitter

25 Posts

Blogs

2 Articles

News

14 Articles

Metrics

Video Views

1,076

Total Likes

89

Extended Reach

386,870

Social Features

43

Timeline: Posts about article

Top Social Media Posts

Posts referencing the article

Establishing Reference Call Sets for Cancer Mutation Detection Using WGS

Establishing Reference Call Sets for Cancer Mutation Detection Using WGS

This presentation discusses methods to establish community reference samples and call sets for benchmarking cancer mutation detection using whole-genome sequencing. These standardized datasets aim to improve sequencing pipelines and algorithm performance in cancer genomics.

Li Tai Fang

June 27, 2021

839 views

Using SomaticSeq for Cancer Mutation Classification on precisionFDA

Using SomaticSeq for Cancer Mutation Classification on precisionFDA

Demo how to use SomaticSeq App on precisionFDA to create somatic mutation classifiers based on SEQC2 reference data and call sets and use the classifiers to make prediction for other cancer data sets. The study highlights the need for standardized DNA datasets in cancer genomics to improve sequencing pipelines and algorithm

Li Tai Fang

December 20, 2021

237 views

  • Li Tai Fang
    @ltfang (Twitter)

    Video presentation on the bioinformatic methods to establish high-confidence somatic mutation reference call sets for #SEQC2 cancer reference samples and data sets https://t.co/Xxs4kTEmJm
    view full post

    December 20, 2021

  • Li Tai Fang
    @ltfang (Twitter)

    Video demo of using the SomaticSeq App on precisionFDA to train and predict somatic mutations in paired tumor-normal sequencing data: https://t.co/JjmZXAOnnM
    view full post

    December 20, 2021

  • Zheng Ming Fang
    @zmfang (Twitter)

    RT @ltfang: WGS and WES cancer reference datasets from multi-center cross-platform benchmark study: https://t.co/kva4Glf56X - Best practi…
    view full post

    November 21, 2021

    1

  • Li Tai Fang
    @ltfang (Twitter)

    WGS and WES cancer reference datasets from multi-center cross-platform benchmark study: https://t.co/kva4Glf56X - Best practice: https://t.co/JLnWGPVVhz (https://t.co/W5PZ0wJk0B) - High-confidence somatic mutation call set: https://t.co/RAqSp04IT1 (https://t.co/BOYki3Toxf)
    view full post

    November 9, 2021

    1

    1

  • Steve, PhD
    @StevOmics (Twitter)

    Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing https://t.co/ldLwtAAhLv #science #genomics
    view full post

    November 7, 2021

    2

  • ashish (@acgt01@genomic.social)
    @acgt01 (Twitter)

    RT @notSoJunkDNA: Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing https://t.co/j79FvpFB4q Es…
    view full post

    October 1, 2021

    6

  • Steve, PhD
    @StevOmics (Twitter)

    Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing https://t.co/ldLwtAAhLv #science #genomics
    view full post

    September 28, 2021

    1

  • Steve, PhD
    @StevOmics (Twitter)

    Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing https://t.co/ldLwtAAhLv #science #genomics
    view full post

    September 26, 2021

    1

  • Zheng Ming Fang
    @zmfang (Twitter)

    RT @NatureBiotech: Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-geno…
    view full post

    September 19, 2021

    8

  • Marián Hajdúch
    @marian_hajduch (Twitter)

    Big steps towards practical use of WGS&WES in personalization of cancer therapy. Congrats to my colleagues form @IMTM_Olomouc, @EatrisEric, @FIMM_UH, @karolinskainst, etc. contributing to two papers in @NatureBiotech in one issue.
    view full post

    September 11, 2021

    11

  • Institute of Molecular and Translational Medicine
    @IMTM_Olomouc (Twitter)

    Fang LT, et al.: Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole genome sequencing. Nat Biotechnol. https://t.co/9IsTpMyyko
    view full post

    September 11, 2021

    3

  • Michelle
    @Michellisu_2018 (Twitter)

    RT @NatureBiotech: Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-geno…
    view full post

    September 10, 2021

    8

  • Javier Santoyo
    @jsantoyo (Twitter)

    Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing. #SEQC2 #WGS #BenchmarkingDataSets #MutationDetection https://t.co/RY9wXXqGJj @NatureBiotech
    view full post

    September 9, 2021

    1

  • aaaa
    @ngsstudent (Twitter)

    RT @notSoJunkDNA: Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing https://t.co/j79FvpFB4q Es…
    view full post

    September 9, 2021

    6

  • Tina Han
    @tingfordha (Twitter)

    RT @notSoJunkDNA: Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing https://t.co/j79FvpFB4q Es…
    view full post

    September 9, 2021

    6

  • Paz Polak
    @PolakPaz (Twitter)

    RT @notSoJunkDNA: Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing https://t.co/j79FvpFB4q Es…
    view full post

    September 9, 2021

    6

  • Chris Miller
    @chrisamiller (Twitter)

    RT @notSoJunkDNA: Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing https://t.co/j79FvpFB4q Es…
    view full post

    September 9, 2021

    6

  • Journal of Comparative Pathology
    @JournalCompPath (Twitter)

    RT @NatureBiotech: Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-geno…
    view full post

    September 9, 2021

    8

  • Absurd
    @qualityisarul3 (Twitter)

    RT @NatureBiotech: Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-geno…
    view full post

    September 9, 2021

    8

  • Anirban Maitra
    @Aiims1742 (Twitter)

    RT @notSoJunkDNA: Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing https://t.co/j79FvpFB4q Es…
    view full post

    September 9, 2021

    6

  • Nicolas Robine
    @notSoJunkDNA (Twitter)

    Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing https://t.co/j79FvpFB4q Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing https://t.co/ZS8GD66kXG
    view full post

    September 9, 2021

    23

    6

  • Skatiq
    @Skatiq3 (Twitter)

    RT @NatureBiotech: Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-geno…
    view full post

    September 9, 2021

    8

  • Lum Lab
    @lum_lab (Twitter)

    RT @NatureBiotech: Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-geno…
    view full post

    September 9, 2021

    8

  • syawal™ シ
    @syawal (Twitter)

    RT @NatureBiotech: Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-geno…
    view full post

    September 9, 2021

    8

  • Nature Biotechnology
    @NatureBiotech (Twitter)

    Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing https://t.co/HvmuSxq1t0 https://t.co/t6kEWmDXPD
    view full post

    September 9, 2021

    33

    8

Abstract Synopsis

  • The study highlights the need for standardized DNA datasets in cancer genomics to improve sequencing pipelines and algorithm performance.
  • The authors present reference call sets derived from paired tumor-normal genomic DNA samples from a breast cancer cell line, known for its genetic diversity and alterations.
  • These reference samples allow for better bias minimization in sequencing technologies and serve as a valuable resource for benchmarking tumor analysis methods, despite not being representative of primary clinical cancer cells.