title: Multiplexing of ChIP-Seq Samples in an Optimized Experimental Condition Has Minimal Impact on Peak Detection.
abstract: Multiplexing samples in sequencing experiments is a common approach to maximize information yield while minimizing cost. In most cases the number of samples that are multiplexed is determined by financial consideration or experimental convenience, with limited understanding on the effects on the experimental results. Here we set to examine the impact of multiplexing ChIP-seq experiments on the ability to identify a specific epigenetic modification. We performed peak detection analyses to determine the effects of multiplexing. These include false discovery rates, size, position and statistical significance of peak detection, and changes in gene annotation. We found that, for histone marker H3K4me3, one can multiplex up to 8 samples (7 IP + 1 input) at ~21 million single-end reads each and still detect over 90% of all peaks found when using a full lane for sample (~181 million reads). Furthermore, there are no variations introduced by indexing or lane batch effects and importantly there is no significant reduction in the number of genes with neighboring H3K4me3 peaks. We conclude that, for a well characterized antibody and, therefore, model IP condition, multiplexing 8 samples per lane is sufficient to capture most of the biological signal.
authors.affiliation: Department of Medicine, Division of Hematology/Oncology, Epigenomics Core Facility, Weill Cornell Medical College, New York, New York, United States of America.
authors.forename: Thadeous J
authors.initials: TJ
authors.lastname: Kacmarczyk
authors.affiliation: Department of Surgery, Weill Cornell Medical College, New York, New York, United States of America; Department of Medicine, Weill Cornell Medical College, New York, New York, United States of America.
authors.forename: Caitlin
authors.initials: C
authors.lastname: Bourque
authors.affiliation: Department of Medicine, Division of Hematology/Oncology, Epigenomics Core Facility, Weill Cornell Medical College, New York, New York, United States of America.
authors.forename: Xihui
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Department of Medicine, Division of Hematology/Oncology, Epigenomics Core Facility, Weill Cornell Medical College, New York, New York, United States of America.
authors.forename: Yanwen
authors.initials: Y
authors.lastname: Jiang
authors.affiliation: Department of Surgery, Weill Cornell Medical College, New York, New York, United States of America; Department of Medicine, Weill Cornell Medical College, New York, New York, United States of America.
authors.forename: Yariv
authors.initials: Y
authors.lastname: Houvras
authors.affiliation: Department of Medicine, Division of Hematology/Oncology, Epigenomics Core Facility, Weill Cornell Medical College, New York, New York, United States of America.
authors.forename: Alicia
authors.initials: A
authors.lastname: Alonso
authors.affiliation: Department of Medicine, Division of Hematology/Oncology, Epigenomics Core Facility, Weill Cornell Medical College, New York, New York, United States of America; Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, United States of America.
authors.forename: Doron
authors.initials: D
authors.lastname: Betel
mesh_terms: D045744:Cell Line, Tumor; D047369:Chromatin Immunoprecipitation; D059014:High-Throughput Nucleotide Sequencing; D006657:Histones / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D006801:Humans; D017422:Sequence Analysis, DNA
chemical_list: D006657:Histones