Statistical analysis of high throughput sequencing count data:
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
2013
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| Schlagworte: | |
| Online-Zugang: | kostenfrei Inhaltsverzeichnis |
| Beschreibung: | Nebentitel: Statistische Analyse von Hochdurchsatz-Sequenzierverfahren-Daten |
| Beschreibung: | VI, 107 S. Ill., graph. Darst. |
Internformat
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| 245 | 1 | 0 | |a Statistical analysis of high throughput sequencing count data |c Michael I. Love |
| 246 | 1 | 3 | |a Statistische Analyse von Hochdurchsatz-Sequenzierverfahren-Daten |
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Datensatz im Suchindex
| _version_ | 1804151454126047232 |
|---|---|
| adam_text | CONTENTS
1 INTRODUCTION 1
1.1 BIOLOGICAL INTRODUCTION 1
1.1.1 DNA 1
1.1.2 RNA 1
1.1.3 CHROMATIN 2
1.2 DESCRIPTIONS OF EXPERIMENTS 4
1.2.1 HIGH-THROUGHPUT SEQUENCING 4
1.2.2 GENOTYPING: DNA-SEQ 4
1.2.3 GENE EXPRESSION: RNA-SEQ 5
1.2.4 CHROMATIN STATE: CHLP-SEQ AND DNASE-SEQ 6
1.3 MOST EXPERIMENTS ARE ENSEMBLE AVERAGES 6
1.4 OPPORTUNITIES AND CHALLENGES OF GENOMIC COUNT DATA 7
1.5 THESIS OBJECTIVE AND STRUCTURE 8
1.5.1 OBJECTIVE 8
1.5.2 STRUCTURE 8
2 MOTIVATION OF DISCRETE DISTRIBUTIONS FOR SEQUENCING COUNTS 9
2.1 MULTINOMIAL, BINOMIAL AND POISSON DISTRIBUTIONS 9
2.2 OVERDISPERSION AND POISSON MIXTURE DISTRIBUTIONS 10
2.2.1 OVERDISPERSION 10
2.2.2 POISSON GAMMA / NEGATIVE BINOMIAL DISTRIBUTION 11
2.2.3 POISSON LOG NORMAL DISTRIBUTION 12
2.2.4 ADDITIONAL APPROACHES INVOLVING DISCRETE DISTRIBUTIONS 12
2.3 COMPARISON OF DISCRETE DISTRIBUTIONAL MODELING WITH ALTERNATIVES 12
2.3.1 WHY USE DISCRETE DISTRIBUTIONS? 12
2.3.2 NON-PARAMETRIC MODELING 13
2.3.3 PARAMETRIC MODELING ON TRANSFORMED COUNTS 14
2.4 INTRODUCTION TO THE GENERALIZED LINEAR MODEL 16
2.5 PARAMETRIC MODEL FIT 17
3 MODELING READ COUNTS FOR CNV DETECTION IN EXOME SEQUENCING DATA 19
3.1 INTRODUCTION 19
3.2 METHODS 21
3.2.1 MODELING RESEQUENCING READ COUNTS 21
IV
HTTP://D-NB.INFO/104424075X
3.2.2 HIDDEN MARKOV MODEL TO PREDICT SAMPLE CNVS 24
3.3 RESULTS 28
3.3.1 XLID PROJECT: CHROMOSOME X EXOME RESEQUENCING 28
3.3.2 RECOVERING XLID CNVS WITH A CROSS-PLATFORM CONTROL SET 29
3.3.3 SENSITIVITY ANALYSIS ON SIMULATED AUTOSOMAL CNVS 31
3.4 DISCUSSION 35
4 DIFFERENTIAL EXPRESSION ANALYSIS FOR RNA-SEQ USING EMPIRICAL BAYES
PRI
ORS FOR DISPERSION AND FOLD CHANGE 38
4.1 INTRODUCTION 38
4.1.1 DETECTING DIFFERENCES BETWEEN SAMPLES OVER MANY GENES 38
4.1.2 GENERALIZED LINEAR MODEL FOR RNA-SEQ 39
4.1.3 SHRUNKEN FOLD CHANGE ESTIMATES 40
4.1.4 SHRINKAGE ESTIMATORS FOR DISPERSION 41
4.1.5 ROBUST ESTIMATION AND INFERENCE WITH DESEQ2 43
4.2 METHODS 43
4.2.1 GLM DEFINITION 43
4.2.2 DISPERSION ESTIMATES AND PRIOR 44
4.2.3 DISPERSION OUTLIERS 46
4.2.4 FINAL DISPERSION ESTIMATES 46
4.2.5 BETA PRIOR 46
4.2.6 FINAL BETA ESTIMATES 47
4.2.7 WALD TEST 47
4.2.8 COOK S DISTANCE FOR OUTLIER DETECTION 48
4.2.9 REGULARIZED LOG TRANSFORMATION 48
4.3 RESULTS 49
4.3.1 ACCURACY OF MAP DISPERSIONS FOR SIMULATED DATA 49
4.3.2 EFFECT OF PRIOR ON LOG FOLD CHANGES 50
4.3.3 DIFFERENTIAL EXPRESSION ANALYSIS ON RNA-SEQ DATA 51
4.3.4 REGULARIZED LOG TRANSFORMATION 52
4.3.5 COOK S DISTANCE FOR DETECTION OF OUTLIERS 54
4.3.6 COMPARISON OF DESEQ2 AGAINST OTHER METHODS 55
4.4 DISCUSSION 58
5 HIERARCHICAL BAYES MODELING OF CELL-TYPE-SPECIFIC GLUCOCORTICOID
RECEPTOR
BINDING PATTERNS 62
5.1 INTRODUCTION 62
5.2 METHODS 63
5.2.1 SEQUENCING DATA PREPARATION 63
5.2.2 MOTIF SCORE CALCULATION 65
5.2.3 HIERARCHICAL BAYES MODELING 65
5.3 RESULTS 67
5.3.1 GENOMIC LOCATION OF GR BINDING 67
5.3.2 INTERPRETATION OF HIERARCHICAL MODEL PARAMETERS 68
5.3.3 CELL-TYPE-SPECIFIC PARAMETERS ARE TYPICAL PROMOTERS MARKS 70
5.3.4 EXPLANATORY POWER OF THE MODEL 70
5.3.5 GR MOTIF SCORE DISTRIBUTION AT DHS AND PROMOTERS 72
5.4 DISCUSSION 73
BIBLIOGRAPHY 75
LIST OF FIGURES 89
LIST OF TABLES 91
A SUPPLEMENTARY FIGURES 92
B SUPPLEMENTARY TABLES 95
C SOFTWARE 98
D NOTATION 100
D.L ACRONYMS 100
D.2 SYMBOLS 101
E CURRICULUM VITAE 102
F ZUSAMMENFASSUNG 105
G SUMMARY 106
H EHRENWORTLICHE ERKLARUNG 107
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| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 572 - Biochemistry |
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| dewey-search | 572.86015195 |
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| spelling | Love, Michael I. Verfasser (DE-588)1043111328 aut Statistical analysis of high throughput sequencing count data Michael I. Love Statistische Analyse von Hochdurchsatz-Sequenzierverfahren-Daten 2013 VI, 107 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Nebentitel: Statistische Analyse von Hochdurchsatz-Sequenzierverfahren-Daten Berlin, Freie Univ., Diss., 2013 (DE-588)4113937-9 Hochschulschrift gnd-content Erscheint auch als Online-Ausgabe urn:nbn:de:kobv:188-fudissthesis000000095251-4 http://www.diss.fu-berlin.de/diss/receive/FUDISS_thesis_000000095251 kostenfrei Volltext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026814791&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Love, Michael I. Statistical analysis of high throughput sequencing count data |
| subject_GND | (DE-588)4113937-9 |
| title | Statistical analysis of high throughput sequencing count data |
| title_alt | Statistische Analyse von Hochdurchsatz-Sequenzierverfahren-Daten |
| title_auth | Statistical analysis of high throughput sequencing count data |
| title_exact_search | Statistical analysis of high throughput sequencing count data |
| title_full | Statistical analysis of high throughput sequencing count data Michael I. Love |
| title_fullStr | Statistical analysis of high throughput sequencing count data Michael I. Love |
| title_full_unstemmed | Statistical analysis of high throughput sequencing count data Michael I. Love |
| title_short | Statistical analysis of high throughput sequencing count data |
| title_sort | statistical analysis of high throughput sequencing count data |
| topic_facet | Hochschulschrift |
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