Challenges and opportunities in processing NanoString nCounter data

被引：12

作者：

Chilimoniuk, Jaroslaw ^{[1
]}

Erol, Anna ^{[1
]}

Roediger, Stefan ^{[2
]}

Burdukiewicz, Michal ^{[1
,3
]}

机构：

[1] Med Univ Bialystok, Clin Res Ctr, Bialystok, Poland

[2] Brandenburg Univ Technol Cottbus Senftenberg, Inst Biotechnol, Fac Environm & Nat Sci, Senftenberg, Germany

[3] Autonomous Univ Barcelona, Inst Biotechnol & Biomed, Barcelona, Spain

来源：

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL | 2024年 / 23卷

关键词：

NanoString; nSolver; mRNA; miRNA; nCounter; Background correction; Normalization; Differential expression; GENE-EXPRESSION; RNA; SENSITIVITY; CANCER;

D O I：

10.1016/j.csbj.2024.04.061

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

NanoString nCounter is a medium -throughput technology used in mRNA and miRNA differential expression studies. It offers several advantages, including the absence of an amplification step and the ability to analyze low-grade samples. Despite its considerable strengths, the popularity of the nCounter platform in experimental research stabilized in 2022 and 2023, and this trend may continue in the upcoming years. Such stagnation could potentially be attributed to the absence of a standardized analytical pipeline or the indication of optimal processing methods for nCounter data analysis. To standardize the description of the nCounter data analysis workflow, we divided it into five distinct steps: data pre-processing, quality control, background correction, normalization and differential expression analysis. Next, we evaluated eleven R packages dedicated to nCounter data processing to point out functionalities belonging to these steps and provide comments on their applications in studies of mRNA and miRNA samples.

引用

页码：1951 / 1958

页数：8

共 52 条

[1]

Aboyoun Patrick, 2021, Bioconductor, DOI 10.18129/B9.BIOC.NANOSTRINGNCTOOLS

[2]

Alberts B., 2002, Molecular Biology of the Cell, V4th Edn

[3] Differential expression analysis for sequence count data [J].

Anders, Simon ;

Huber, Wolfgang .

GENOME BIOLOGY, 2010, 11 (10)

[4] Multi-gene technical assessment of qPCR and NanoString n-Counter analysis platforms in cynomolgus monkey cardiac allograft recipients [J].

Bergbower, Emily A. S. ;

Pierson, Richard N., III ;

Azimzadeh, Agnes M. .

CELLULAR IMMUNOLOGY, 2020, 347

[5] An approach for normalization and quality control for NanoString RNA expression data [J].

Bhattacharya, Arjun ;

Hamilton, Alina M. ;

Furberg, Helena ;

Pietzak, Eugene ;

Purdue, Mark P. ;

Troester, Melissa A. ;

Hoadley, Katherine A. ;

Love, Michael, I .

BRIEFINGS IN BIOINFORMATICS, 2021, 22 (03)

[6]

Bondar Galyna, 2020, Journal of Biological Methods, V7, pe123, DOI 10.14440/jbm.2020.300

[7] NanoStriDE: Normalization and Differential Expression Analysis of NanoString nCounter Data [J].

Brumbaugh, Christopher D. ;

Kim, Hyunsung J. ;

Giovacchini, Mario ;

Pourmand, Nader .

BMC BIOINFORMATICS, 2011, 12

[8] NACHO: an R package for quality control of NanoString nCounter data [J].

Canouil, Mickael ;

Bouland, Gerard A. ;

Bonnefond, Amelie ;

Froguel, Philippe ;

't Hart, Leen M. ;

Slieker, Roderick C. .

BIOINFORMATICS, 2020, 36 (03) :970-971

[9] A cross comparison of technologies for the detection of microRNAs in clinical FFPE samples of hepatoblastoma patients [J].

Chatterjee, Aniruddha ;

Leichter, Anna L. ;

Fan, Vicky ;

Tsai, Peter ;

Purcell, Rachel V. ;

Sullivan, Michael J. ;

Eccles, Michael R. .

SCIENTIFIC REPORTS, 2015, 5

[10] countfitteR: efficient selection of count distributions to assess DNA damage [J].

Chilimoniuk, Jaroslaw ;

Gosiewska, Alicja ;

Slowik, Jadwiga ;

Weiss, Romano ;

Deckert, P. Markus ;

Roediger, Stefan ;

Burdukiewicz, Michal .

ANNALS OF TRANSLATIONAL MEDICINE, 2021, 9 (07)

← 1 2 3 4 5 6 →