qcCHIP: an R package to identify clonal hematopoiesis variants using cohort-specific data characteristics

Xiang Liu; Yi Han Tang; James Blachly; Stephen Edge; Yasminka A. Jakubek; Martin McCarter; Abdul Rafeh Naqash; Kenneth G. Nepple; Afaf Osman; Matthew J. Reilley; Gregory Riedlinger; Bodour Salhia; Bryan P. Schneider; Craig Shriver; Michelle L. Churchman; Robert J. Rounbehler; Jamie K. Teer; Nancy Gillis; Mingxiang Teng

doi:10.1093/bioinformatics/btaf522

qcCHIP: an R package to identify clonal hematopoiesis variants using cohort-specific data characteristics

Xiang Liu, Yi Han Tang, James Blachly, Stephen Edge, Yasminka A. Jakubek, Martin McCarter, Abdul Rafeh Naqash, Kenneth G. Nepple, Afaf Osman, Matthew J. Reilley, Gregory Riedlinger, Bodour Salhia, Bryan P. Schneider, Craig Shriver, Michelle L. Churchman, Robert J. Rounbehler, Jamie K. Teer, Nancy Gillis^*, Mingxiang Teng^*

^*Corresponding author for this work

Surgery

Research output: Contribution to journal › Article › peer-review

Abstract

Clonal hematopoiesis (CH) is a molecular biomarker associated with various adverse outcomes in both healthy individuals and those with underlying conditions, including cancer. Detecting CH usually involves genomic sequencing of individual blood samples followed by robust bioinformatics data filtering. We report an R package, qcCHIP, a bioinformatics pipeline that implements permutation-based parameter optimization to guide quality control filtering and cohort-specific CH identification. We benchmark qcCHIP under various data settings, including different sequencing depths, ranges of cohort sizes, with and without normal-tumor paired samples, and across different cancer types. We show that qcCHIP allows users to customize analysis needs to generate CH calls based on cohort-specific data characteristics.

Original language	English
Article number	btaf522
Journal	Bioinformatics
Volume	41
Issue number	9
DOIs	https://doi.org/10.1093/bioinformatics/btaf522
State	Published - 1 Sep 2025

Access to Document

10.1093/bioinformatics/btaf522

Cite this

Liu, X., Tang, Y. H., Blachly, J., Edge, S., Jakubek, Y. A., McCarter, M., Naqash, A. R., Nepple, K. G., Osman, A., Reilley, M. J., Riedlinger, G., Salhia, B., Schneider, B. P., Shriver, C., Churchman, M. L., Rounbehler, R. J., Teer, J. K., Gillis, N., & Teng, M. (2025). qcCHIP: an R package to identify clonal hematopoiesis variants using cohort-specific data characteristics. Bioinformatics, 41(9), Article btaf522. https://doi.org/10.1093/bioinformatics/btaf522

@article{2a0d54c45b374470af1214c2fd307e86,

title = "qcCHIP: an R package to identify clonal hematopoiesis variants using cohort-specific data characteristics",

abstract = "Clonal hematopoiesis (CH) is a molecular biomarker associated with various adverse outcomes in both healthy individuals and those with underlying conditions, including cancer. Detecting CH usually involves genomic sequencing of individual blood samples followed by robust bioinformatics data filtering. We report an R package, qcCHIP, a bioinformatics pipeline that implements permutation-based parameter optimization to guide quality control filtering and cohort-specific CH identification. We benchmark qcCHIP under various data settings, including different sequencing depths, ranges of cohort sizes, with and without normal-tumor paired samples, and across different cancer types. We show that qcCHIP allows users to customize analysis needs to generate CH calls based on cohort-specific data characteristics.",

author = "Xiang Liu and Tang, {Yi Han} and James Blachly and Stephen Edge and Jakubek, {Yasminka A.} and Martin McCarter and Naqash, {Abdul Rafeh} and Nepple, {Kenneth G.} and Afaf Osman and Reilley, {Matthew J.} and Gregory Riedlinger and Bodour Salhia and Schneider, {Bryan P.} and Craig Shriver and Churchman, {Michelle L.} and Rounbehler, {Robert J.} and Teer, {Jamie K.} and Nancy Gillis and Mingxiang Teng",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2025. Published by Oxford University Press.",

year = "2025",

month = sep,

day = "1",

doi = "10.1093/bioinformatics/btaf522",

language = "English",

volume = "41",

journal = "Bioinformatics",

issn = "1367-4803",

publisher = "Oxford University Press",

number = "9",

}

Liu, X, Tang, YH, Blachly, J, Edge, S, Jakubek, YA, McCarter, M, Naqash, AR, Nepple, KG, Osman, A, Reilley, MJ, Riedlinger, G, Salhia, B, Schneider, BP, Shriver, C, Churchman, ML, Rounbehler, RJ, Teer, JK, Gillis, N & Teng, M 2025, 'qcCHIP: an R package to identify clonal hematopoiesis variants using cohort-specific data characteristics', Bioinformatics, vol. 41, no. 9, btaf522. https://doi.org/10.1093/bioinformatics/btaf522

TY - JOUR

T1 - qcCHIP

T2 - an R package to identify clonal hematopoiesis variants using cohort-specific data characteristics

AU - Liu, Xiang

AU - Tang, Yi Han

AU - Blachly, James

AU - Edge, Stephen

AU - Jakubek, Yasminka A.

AU - McCarter, Martin

AU - Naqash, Abdul Rafeh

AU - Nepple, Kenneth G.

AU - Osman, Afaf

AU - Reilley, Matthew J.

AU - Riedlinger, Gregory

AU - Salhia, Bodour

AU - Schneider, Bryan P.

AU - Shriver, Craig

AU - Churchman, Michelle L.

AU - Rounbehler, Robert J.

AU - Teer, Jamie K.

AU - Gillis, Nancy

AU - Teng, Mingxiang

PY - 2025/9/1

Y1 - 2025/9/1

N2 - Clonal hematopoiesis (CH) is a molecular biomarker associated with various adverse outcomes in both healthy individuals and those with underlying conditions, including cancer. Detecting CH usually involves genomic sequencing of individual blood samples followed by robust bioinformatics data filtering. We report an R package, qcCHIP, a bioinformatics pipeline that implements permutation-based parameter optimization to guide quality control filtering and cohort-specific CH identification. We benchmark qcCHIP under various data settings, including different sequencing depths, ranges of cohort sizes, with and without normal-tumor paired samples, and across different cancer types. We show that qcCHIP allows users to customize analysis needs to generate CH calls based on cohort-specific data characteristics.

AB - Clonal hematopoiesis (CH) is a molecular biomarker associated with various adverse outcomes in both healthy individuals and those with underlying conditions, including cancer. Detecting CH usually involves genomic sequencing of individual blood samples followed by robust bioinformatics data filtering. We report an R package, qcCHIP, a bioinformatics pipeline that implements permutation-based parameter optimization to guide quality control filtering and cohort-specific CH identification. We benchmark qcCHIP under various data settings, including different sequencing depths, ranges of cohort sizes, with and without normal-tumor paired samples, and across different cancer types. We show that qcCHIP allows users to customize analysis needs to generate CH calls based on cohort-specific data characteristics.

UR - http://www.scopus.com/inward/record.url?scp=105017457565&partnerID=8YFLogxK

U2 - 10.1093/bioinformatics/btaf522

DO - 10.1093/bioinformatics/btaf522

M3 - Article

C2 - 40973027

AN - SCOPUS:105017457565

SN - 1367-4803

VL - 41

JO - Bioinformatics

JF - Bioinformatics

IS - 9

M1 - btaf522

ER -