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008181129s2018 ||| | | | eng d
020 ▼a 9780438207776
035 ▼a (MiAaPQ)AAI10842833
035 ▼a (MiAaPQ)wisc:15546
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0491 ▼f DP
0820 ▼a 310
1001 ▼a Nguyen, Duy.
24510 ▼a Statistical Methods for Differential Analysis of Hi-C And ChIP-Seq Data.
260 ▼a [S.l.] : ▼b The University of Wisconsin - Madison., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 140 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Adviser: Sunduz Keles.
5021 ▼a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2018.
520 ▼a High-throughput sequencing has become a standard method in genomics research and made it possible to address important biological questions. In this thesis, we focus on developing statistical methodologies and software to analyze two important h
520 ▼a This thesis contains three major parts. In the first part, we discuss challenges in quantitative comparison of Hi-C data (often referred as ``differential (interaction) analysis'' problem) across different cellular conditions. Prior to this work
520 ▼a For the second part, we investigate statistical challenges in quantitative comparison of histone profiles across different cellular conditions from ChIP-seq data. Quantitative comparison of histone profiles largely depends on methods borrowed fr
520 ▼a In the last part, we describe our two novel software in the R packages TreeHic and tan. Through applications to real Hi-C and ChIP-seq data, we present how these software could reveal biological insights that are not captures in standard data a
590 ▼a School code: 0262.
650 4 ▼a Statistics.
650 4 ▼a Biostatistics.
690 ▼a 0463
690 ▼a 0308
71020 ▼a The University of Wisconsin - Madison. ▼b Statistics.
7730 ▼t Dissertation Abstracts International ▼g 79-12B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0262
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14999873 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자 ▼b 관리자