Additional file 14: of Efficient identification of neoantigen-specific T-cell responses in advanced human ovarian cancer

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Liu, Song;Matsuzaki, Junko;Wei, Lei;Tsuji, Takemasa;Battaglia, Sebastiano;Hu, Qiang;Cortes, Eduardo;Wong, Laiping;Yan, Li;Long, Mark;Miliotto, Anthony;Bateman, Nicholas;Lele, Shashikant;Chodon, Thinle;Koya, Richard;Yao, Song;Zhu, Qianqian;Conrads, Thomas;Wang, Jianmin;Maxwell, George;Lugade, Amit;Odunsi, Kunle

Description

Table S3. Somatic mutation burdens and predicted neoantigen load in the 20 patients. The predicted neoantigens are classified as expressed or non-expressed based on the mutant alleleâ s expression level in RNAseq data (see Method section). (XLSX 10 kb)

Citations (1)

https://doi.org/10.1186/s40425-019-0629-6
MDC
Cited on 20 June 2019
Weight: 1.00

Mentions (0)

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Metrics

Dataset Index

0.5

FAIR Score

85%

Citations

Mentions

Metrics Over Time

Publication Details

DOI

10.6084/m9.figshare.8305028.v1

Publisher

figshare

Assigned Domain

Subfield

Molecular Biology

Field

Biochemistry, Genetics and Molecular Biology

Domain

Life Sciences

Confidence Score

64%

Source

Scholar Data Model

Keywords

BiochemistryMedicineMicrobiologyFOS: Biological sciencesGeneticsMolecular BiologyPharmacologyImmunologyFOS: Clinical medicineBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedDevelopmental BiologyInfectious DiseasesFOS: Health sciencesVirology

Normalization Factors

30.77

CTw

1.00

MTw

1.00