-
Notifications
You must be signed in to change notification settings - Fork 0
/
exercises-3.html
614 lines (575 loc) · 77 KB
/
exercises-3.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
<!DOCTYPE html>
<html lang="" xml:lang="">
<head>
<meta charset="utf-8" />
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<title>5.16 Exercises | Computational Genomics with R</title>
<meta name="description" content="A guide to computationa genomics using R. The book covers fundemental topics with practical examples for an interdisciplinery audience" />
<meta name="generator" content="bookdown 0.19 and GitBook 2.6.7" />
<meta property="og:title" content="5.16 Exercises | Computational Genomics with R" />
<meta property="og:type" content="book" />
<meta property="og:url" content="https://compmgenomr.github.io/book/" />
<meta property="og:image" content="https://compmgenomr.github.io/book/images/cover.jpg" />
<meta property="og:description" content="A guide to computationa genomics using R. The book covers fundemental topics with practical examples for an interdisciplinery audience" />
<meta name="github-repo" content="compgenomr/book" />
<meta name="twitter:card" content="summary" />
<meta name="twitter:title" content="5.16 Exercises | Computational Genomics with R" />
<meta name="twitter:description" content="A guide to computationa genomics using R. The book covers fundemental topics with practical examples for an interdisciplinery audience" />
<meta name="twitter:image" content="https://compmgenomr.github.io/book/images/cover.jpg" />
<meta name="author" content="Altuna Akalin" />
<meta name="date" content="2020-09-30" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<meta name="apple-mobile-web-app-capable" content="yes" />
<meta name="apple-mobile-web-app-status-bar-style" content="black" />
<link rel="prev" href="predicting-continuous-variables-regression-with-machine-learning.html"/>
<link rel="next" href="genomicIntervals.html"/>
<script src="libs/jquery-2.2.3/jquery.min.js"></script>
<link href="libs/gitbook-2.6.7/css/style.css" rel="stylesheet" />
<link href="libs/gitbook-2.6.7/css/plugin-table.css" rel="stylesheet" />
<link href="libs/gitbook-2.6.7/css/plugin-bookdown.css" rel="stylesheet" />
<link href="libs/gitbook-2.6.7/css/plugin-highlight.css" rel="stylesheet" />
<link href="libs/gitbook-2.6.7/css/plugin-search.css" rel="stylesheet" />
<link href="libs/gitbook-2.6.7/css/plugin-fontsettings.css" rel="stylesheet" />
<link href="libs/gitbook-2.6.7/css/plugin-clipboard.css" rel="stylesheet" />
<!-- Global site tag (gtag.js) - Google Analytics -->
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-83786243-1"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments);}
gtag('js', new Date());
gtag('config', 'UA-83786243-1');
</script>
<style type="text/css">
code.sourceCode > span { display: inline-block; line-height: 1.25; }
code.sourceCode > span { color: inherit; text-decoration: inherit; }
code.sourceCode > span:empty { height: 1.2em; }
.sourceCode { overflow: visible; }
code.sourceCode { white-space: pre; position: relative; }
pre.sourceCode { margin: 0; }
@media screen {
div.sourceCode { overflow: auto; }
}
@media print {
code.sourceCode { white-space: pre-wrap; }
code.sourceCode > span { text-indent: -5em; padding-left: 5em; }
}
pre.numberSource code
{ counter-reset: source-line 0; }
pre.numberSource code > span
{ position: relative; left: -4em; counter-increment: source-line; }
pre.numberSource code > span > a:first-child::before
{ content: counter(source-line);
position: relative; left: -1em; text-align: right; vertical-align: baseline;
border: none; display: inline-block;
-webkit-touch-callout: none; -webkit-user-select: none;
-khtml-user-select: none; -moz-user-select: none;
-ms-user-select: none; user-select: none;
padding: 0 4px; width: 4em;
color: #aaaaaa;
}
pre.numberSource { margin-left: 3em; border-left: 1px solid #aaaaaa; padding-left: 4px; }
div.sourceCode
{ }
@media screen {
code.sourceCode > span > a:first-child::before { text-decoration: underline; }
}
code span.al { color: #ff0000; font-weight: bold; } /* Alert */
code span.an { color: #60a0b0; font-weight: bold; font-style: italic; } /* Annotation */
code span.at { color: #7d9029; } /* Attribute */
code span.bn { color: #40a070; } /* BaseN */
code span.bu { } /* BuiltIn */
code span.cf { color: #007020; font-weight: bold; } /* ControlFlow */
code span.ch { color: #4070a0; } /* Char */
code span.cn { color: #880000; } /* Constant */
code span.co { color: #60a0b0; font-style: italic; } /* Comment */
code span.cv { color: #60a0b0; font-weight: bold; font-style: italic; } /* CommentVar */
code span.do { color: #ba2121; font-style: italic; } /* Documentation */
code span.dt { color: #902000; } /* DataType */
code span.dv { color: #40a070; } /* DecVal */
code span.er { color: #ff0000; font-weight: bold; } /* Error */
code span.ex { } /* Extension */
code span.fl { color: #40a070; } /* Float */
code span.fu { color: #06287e; } /* Function */
code span.im { } /* Import */
code span.in { color: #60a0b0; font-weight: bold; font-style: italic; } /* Information */
code span.kw { color: #007020; font-weight: bold; } /* Keyword */
code span.op { color: #666666; } /* Operator */
code span.ot { color: #007020; } /* Other */
code span.pp { color: #bc7a00; } /* Preprocessor */
code span.sc { color: #4070a0; } /* SpecialChar */
code span.ss { color: #bb6688; } /* SpecialString */
code span.st { color: #4070a0; } /* String */
code span.va { color: #19177c; } /* Variable */
code span.vs { color: #4070a0; } /* VerbatimString */
code span.wa { color: #60a0b0; font-weight: bold; font-style: italic; } /* Warning */
</style>
<link rel="stylesheet" href="css/style.css" type="text/css" />
</head>
<body>
<div class="book without-animation with-summary font-size-2 font-family-1" data-basepath=".">
<div class="book-summary">
<nav role="navigation">
<ul class="summary">
<li><a href="./">Computational Genomics with R</a></li>
<li class="divider"></li>
<li class="chapter" data-level="" data-path="index.html"><a href="index.html"><i class="fa fa-check"></i>Preface</a><ul>
<li class="chapter" data-level="" data-path="who-is-this-book-for.html"><a href="who-is-this-book-for.html"><i class="fa fa-check"></i>Who is this book for?</a><ul>
<li class="chapter" data-level="" data-path="who-is-this-book-for.html"><a href="who-is-this-book-for.html#what-will-you-get-out-of-this"><i class="fa fa-check"></i>What will you get out of this?</a></li>
</ul></li>
<li class="chapter" data-level="" data-path="structure-of-the-book.html"><a href="structure-of-the-book.html"><i class="fa fa-check"></i>Structure of the book</a></li>
<li class="chapter" data-level="" data-path="software-information-and-conventions.html"><a href="software-information-and-conventions.html"><i class="fa fa-check"></i>Software information and conventions</a><ul>
<li class="chapter" data-level="" data-path="software-information-and-conventions.html"><a href="software-information-and-conventions.html#assignment-operator-convention"><i class="fa fa-check"></i>Assignment operator convention</a></li>
<li class="chapter" data-level="" data-path="software-information-and-conventions.html"><a href="software-information-and-conventions.html#packages-needed-to-run-the-book-code"><i class="fa fa-check"></i>Packages needed to run the book code</a></li>
</ul></li>
<li class="chapter" data-level="" data-path="data-for-the-book.html"><a href="data-for-the-book.html"><i class="fa fa-check"></i>Data for the book</a></li>
<li class="chapter" data-level="" data-path="exercises-in-the-book.html"><a href="exercises-in-the-book.html"><i class="fa fa-check"></i>Exercises in the book</a></li>
<li class="chapter" data-level="" data-path="reproducibility-statement.html"><a href="reproducibility-statement.html"><i class="fa fa-check"></i>Reproducibility statement</a></li>
<li class="chapter" data-level="" data-path="acknowledgements.html"><a href="acknowledgements.html"><i class="fa fa-check"></i>Acknowledgements</a></li>
<li class="chapter" data-level="" data-path="how-to-contribute.html"><a href="how-to-contribute.html"><i class="fa fa-check"></i>How to contribute</a></li>
</ul></li>
<li class="chapter" data-level="" data-path="about-the-authors.html"><a href="about-the-authors.html"><i class="fa fa-check"></i>About the Authors</a></li>
<li class="chapter" data-level="1" data-path="intro.html"><a href="intro.html"><i class="fa fa-check"></i><b>1</b> Introduction to Genomics</a><ul>
<li class="chapter" data-level="1.1" data-path="genes-dna-and-central-dogma.html"><a href="genes-dna-and-central-dogma.html"><i class="fa fa-check"></i><b>1.1</b> Genes, DNA and central dogma</a><ul>
<li class="chapter" data-level="1.1.1" data-path="genes-dna-and-central-dogma.html"><a href="genes-dna-and-central-dogma.html#what-is-a-genome"><i class="fa fa-check"></i><b>1.1.1</b> What is a genome?</a></li>
<li class="chapter" data-level="1.1.2" data-path="genes-dna-and-central-dogma.html"><a href="genes-dna-and-central-dogma.html#what-is-a-gene"><i class="fa fa-check"></i><b>1.1.2</b> What is a gene?</a></li>
<li class="chapter" data-level="1.1.3" data-path="genes-dna-and-central-dogma.html"><a href="genes-dna-and-central-dogma.html#how-are-genes-controlled-transcriptional-and-post-transcriptional-regulation"><i class="fa fa-check"></i><b>1.1.3</b> How are genes controlled? Transcriptional and post-transcriptional regulation</a></li>
<li class="chapter" data-level="1.1.4" data-path="genes-dna-and-central-dogma.html"><a href="genes-dna-and-central-dogma.html#what-does-a-gene-look-like"><i class="fa fa-check"></i><b>1.1.4</b> What does a gene look like?</a></li>
</ul></li>
<li class="chapter" data-level="1.2" data-path="elements-of-gene-regulation.html"><a href="elements-of-gene-regulation.html"><i class="fa fa-check"></i><b>1.2</b> Elements of gene regulation</a><ul>
<li class="chapter" data-level="1.2.1" data-path="elements-of-gene-regulation.html"><a href="elements-of-gene-regulation.html#transcriptional-regulation"><i class="fa fa-check"></i><b>1.2.1</b> Transcriptional regulation</a></li>
<li class="chapter" data-level="1.2.2" data-path="elements-of-gene-regulation.html"><a href="elements-of-gene-regulation.html#post-transcriptional-regulation"><i class="fa fa-check"></i><b>1.2.2</b> Post-transcriptional regulation</a></li>
</ul></li>
<li class="chapter" data-level="1.3" data-path="shaping-the-genome-dna-mutation.html"><a href="shaping-the-genome-dna-mutation.html"><i class="fa fa-check"></i><b>1.3</b> Shaping the genome: DNA mutation</a></li>
<li class="chapter" data-level="1.4" data-path="high-throughput-experimental-methods-in-genomics.html"><a href="high-throughput-experimental-methods-in-genomics.html"><i class="fa fa-check"></i><b>1.4</b> High-throughput experimental methods in genomics</a><ul>
<li class="chapter" data-level="1.4.1" data-path="high-throughput-experimental-methods-in-genomics.html"><a href="high-throughput-experimental-methods-in-genomics.html#the-general-idea-behind-high-throughput-techniques"><i class="fa fa-check"></i><b>1.4.1</b> The general idea behind high-throughput techniques</a></li>
<li class="chapter" data-level="1.4.2" data-path="high-throughput-experimental-methods-in-genomics.html"><a href="high-throughput-experimental-methods-in-genomics.html#high-throughput-sequencing"><i class="fa fa-check"></i><b>1.4.2</b> High-throughput sequencing</a></li>
</ul></li>
<li class="chapter" data-level="1.5" data-path="visualization-and-data-repositories-for-genomics.html"><a href="visualization-and-data-repositories-for-genomics.html"><i class="fa fa-check"></i><b>1.5</b> Visualization and data repositories for genomics</a></li>
</ul></li>
<li class="chapter" data-level="2" data-path="Rintro.html"><a href="Rintro.html"><i class="fa fa-check"></i><b>2</b> Introduction to R for Genomic Data Analysis</a><ul>
<li class="chapter" data-level="2.1" data-path="steps-of-genomic-data-analysis.html"><a href="steps-of-genomic-data-analysis.html"><i class="fa fa-check"></i><b>2.1</b> Steps of (genomic) data analysis</a><ul>
<li class="chapter" data-level="2.1.1" data-path="steps-of-genomic-data-analysis.html"><a href="steps-of-genomic-data-analysis.html#data-collection"><i class="fa fa-check"></i><b>2.1.1</b> Data collection</a></li>
<li class="chapter" data-level="2.1.2" data-path="steps-of-genomic-data-analysis.html"><a href="steps-of-genomic-data-analysis.html#data-quality-check-and-cleaning"><i class="fa fa-check"></i><b>2.1.2</b> Data quality check and cleaning</a></li>
<li class="chapter" data-level="2.1.3" data-path="steps-of-genomic-data-analysis.html"><a href="steps-of-genomic-data-analysis.html#data-processing"><i class="fa fa-check"></i><b>2.1.3</b> Data processing</a></li>
<li class="chapter" data-level="2.1.4" data-path="steps-of-genomic-data-analysis.html"><a href="steps-of-genomic-data-analysis.html#exploratory-data-analysis-and-modeling"><i class="fa fa-check"></i><b>2.1.4</b> Exploratory data analysis and modeling</a></li>
<li class="chapter" data-level="2.1.5" data-path="steps-of-genomic-data-analysis.html"><a href="steps-of-genomic-data-analysis.html#visualization-and-reporting"><i class="fa fa-check"></i><b>2.1.5</b> Visualization and reporting</a></li>
<li class="chapter" data-level="2.1.6" data-path="steps-of-genomic-data-analysis.html"><a href="steps-of-genomic-data-analysis.html#why-use-r-for-genomics"><i class="fa fa-check"></i><b>2.1.6</b> Why use R for genomics ?</a></li>
</ul></li>
<li class="chapter" data-level="2.2" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html"><i class="fa fa-check"></i><b>2.2</b> Getting started with R</a><ul>
<li class="chapter" data-level="2.2.1" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#installing-packages"><i class="fa fa-check"></i><b>2.2.1</b> Installing packages</a></li>
<li class="chapter" data-level="2.2.2" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#installing-packages-in-custom-locations"><i class="fa fa-check"></i><b>2.2.2</b> Installing packages in custom locations</a></li>
<li class="chapter" data-level="2.2.3" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#getting-help-on-functions-and-packages"><i class="fa fa-check"></i><b>2.2.3</b> Getting help on functions and packages</a></li>
</ul></li>
<li class="chapter" data-level="2.3" data-path="computations-in-r.html"><a href="computations-in-r.html"><i class="fa fa-check"></i><b>2.3</b> Computations in R</a></li>
<li class="chapter" data-level="2.4" data-path="data-structures.html"><a href="data-structures.html"><i class="fa fa-check"></i><b>2.4</b> Data structures</a><ul>
<li class="chapter" data-level="2.4.1" data-path="data-structures.html"><a href="data-structures.html#vectors"><i class="fa fa-check"></i><b>2.4.1</b> Vectors</a></li>
<li class="chapter" data-level="2.4.2" data-path="data-structures.html"><a href="data-structures.html#matrices"><i class="fa fa-check"></i><b>2.4.2</b> Matrices</a></li>
<li class="chapter" data-level="2.4.3" data-path="data-structures.html"><a href="data-structures.html#data-frames"><i class="fa fa-check"></i><b>2.4.3</b> Data frames</a></li>
<li class="chapter" data-level="2.4.4" data-path="data-structures.html"><a href="data-structures.html#lists"><i class="fa fa-check"></i><b>2.4.4</b> Lists</a></li>
<li class="chapter" data-level="2.4.5" data-path="data-structures.html"><a href="data-structures.html#factors"><i class="fa fa-check"></i><b>2.4.5</b> Factors</a></li>
</ul></li>
<li class="chapter" data-level="2.5" data-path="data-types.html"><a href="data-types.html"><i class="fa fa-check"></i><b>2.5</b> Data types</a></li>
<li class="chapter" data-level="2.6" data-path="reading-and-writing-data.html"><a href="reading-and-writing-data.html"><i class="fa fa-check"></i><b>2.6</b> Reading and writing data</a><ul>
<li class="chapter" data-level="2.6.1" data-path="reading-and-writing-data.html"><a href="reading-and-writing-data.html#reading-large-files"><i class="fa fa-check"></i><b>2.6.1</b> Reading large files</a></li>
</ul></li>
<li class="chapter" data-level="2.7" data-path="plotting-in-r-with-base-graphics.html"><a href="plotting-in-r-with-base-graphics.html"><i class="fa fa-check"></i><b>2.7</b> Plotting in R with base graphics</a><ul>
<li class="chapter" data-level="2.7.1" data-path="plotting-in-r-with-base-graphics.html"><a href="plotting-in-r-with-base-graphics.html#combining-multiple-plots"><i class="fa fa-check"></i><b>2.7.1</b> Combining multiple plots</a></li>
<li class="chapter" data-level="2.7.2" data-path="plotting-in-r-with-base-graphics.html"><a href="plotting-in-r-with-base-graphics.html#saving-plots"><i class="fa fa-check"></i><b>2.7.2</b> Saving plots</a></li>
</ul></li>
<li class="chapter" data-level="2.8" data-path="plotting-in-r-with-ggplot2.html"><a href="plotting-in-r-with-ggplot2.html"><i class="fa fa-check"></i><b>2.8</b> Plotting in R with ggplot2</a><ul>
<li class="chapter" data-level="2.8.1" data-path="plotting-in-r-with-ggplot2.html"><a href="plotting-in-r-with-ggplot2.html#combining-multiple-plots-1"><i class="fa fa-check"></i><b>2.8.1</b> Combining multiple plots</a></li>
<li class="chapter" data-level="2.8.2" data-path="plotting-in-r-with-ggplot2.html"><a href="plotting-in-r-with-ggplot2.html#ggplot2-and-tidyverse"><i class="fa fa-check"></i><b>2.8.2</b> ggplot2 and tidyverse</a></li>
</ul></li>
<li class="chapter" data-level="2.9" data-path="functions-and-control-structures-for-ifelse-etc-.html"><a href="functions-and-control-structures-for-ifelse-etc-.html"><i class="fa fa-check"></i><b>2.9</b> Functions and control structures (for, if/else etc.)</a><ul>
<li class="chapter" data-level="2.9.1" data-path="functions-and-control-structures-for-ifelse-etc-.html"><a href="functions-and-control-structures-for-ifelse-etc-.html#user-defined-functions"><i class="fa fa-check"></i><b>2.9.1</b> User-defined functions</a></li>
<li class="chapter" data-level="2.9.2" data-path="functions-and-control-structures-for-ifelse-etc-.html"><a href="functions-and-control-structures-for-ifelse-etc-.html#loops-and-looping-structures-in-r"><i class="fa fa-check"></i><b>2.9.2</b> Loops and looping structures in R</a></li>
</ul></li>
<li class="chapter" data-level="2.10" data-path="exercises.html"><a href="exercises.html"><i class="fa fa-check"></i><b>2.10</b> Exercises</a><ul>
<li class="chapter" data-level="2.10.1" data-path="exercises.html"><a href="exercises.html#computations-in-r-1"><i class="fa fa-check"></i><b>2.10.1</b> Computations in R</a></li>
<li class="chapter" data-level="2.10.2" data-path="exercises.html"><a href="exercises.html#data-structures-in-r"><i class="fa fa-check"></i><b>2.10.2</b> Data structures in R</a></li>
<li class="chapter" data-level="2.10.3" data-path="exercises.html"><a href="exercises.html#reading-in-and-writing-data-out-in-r"><i class="fa fa-check"></i><b>2.10.3</b> Reading in and writing data out in R</a></li>
<li class="chapter" data-level="2.10.4" data-path="exercises.html"><a href="exercises.html#plotting-in-r"><i class="fa fa-check"></i><b>2.10.4</b> Plotting in R</a></li>
<li class="chapter" data-level="2.10.5" data-path="exercises.html"><a href="exercises.html#functions-and-control-structures-for-ifelse-etc.-1"><i class="fa fa-check"></i><b>2.10.5</b> Functions and control structures (for, if/else, etc.)</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="3" data-path="stats.html"><a href="stats.html"><i class="fa fa-check"></i><b>3</b> Statistics for Genomics</a><ul>
<li class="chapter" data-level="3.1" data-path="how-to-summarize-collection-of-data-points-the-idea-behind-statistical-distributions.html"><a href="how-to-summarize-collection-of-data-points-the-idea-behind-statistical-distributions.html"><i class="fa fa-check"></i><b>3.1</b> How to summarize collection of data points: The idea behind statistical distributions</a><ul>
<li class="chapter" data-level="3.1.1" data-path="how-to-summarize-collection-of-data-points-the-idea-behind-statistical-distributions.html"><a href="how-to-summarize-collection-of-data-points-the-idea-behind-statistical-distributions.html#describing-the-central-tendency-mean-and-median"><i class="fa fa-check"></i><b>3.1.1</b> Describing the central tendency: Mean and median</a></li>
<li class="chapter" data-level="3.1.2" data-path="how-to-summarize-collection-of-data-points-the-idea-behind-statistical-distributions.html"><a href="how-to-summarize-collection-of-data-points-the-idea-behind-statistical-distributions.html#describing-the-spread-measurements-of-variation"><i class="fa fa-check"></i><b>3.1.2</b> Describing the spread: Measurements of variation</a></li>
<li class="chapter" data-level="3.1.3" data-path="how-to-summarize-collection-of-data-points-the-idea-behind-statistical-distributions.html"><a href="how-to-summarize-collection-of-data-points-the-idea-behind-statistical-distributions.html#precision-of-estimates-confidence-intervals"><i class="fa fa-check"></i><b>3.1.3</b> Precision of estimates: Confidence intervals</a></li>
</ul></li>
<li class="chapter" data-level="3.2" data-path="how-to-test-for-differences-between-samples.html"><a href="how-to-test-for-differences-between-samples.html"><i class="fa fa-check"></i><b>3.2</b> How to test for differences between samples</a><ul>
<li class="chapter" data-level="3.2.1" data-path="how-to-test-for-differences-between-samples.html"><a href="how-to-test-for-differences-between-samples.html#randomization-based-testing-for-difference-of-the-means"><i class="fa fa-check"></i><b>3.2.1</b> Randomization-based testing for difference of the means</a></li>
<li class="chapter" data-level="3.2.2" data-path="how-to-test-for-differences-between-samples.html"><a href="how-to-test-for-differences-between-samples.html#using-t-test-for-difference-of-the-means-between-two-samples"><i class="fa fa-check"></i><b>3.2.2</b> Using t-test for difference of the means between two samples</a></li>
<li class="chapter" data-level="3.2.3" data-path="how-to-test-for-differences-between-samples.html"><a href="how-to-test-for-differences-between-samples.html#multiple-testing-correction"><i class="fa fa-check"></i><b>3.2.3</b> Multiple testing correction</a></li>
<li class="chapter" data-level="3.2.4" data-path="how-to-test-for-differences-between-samples.html"><a href="how-to-test-for-differences-between-samples.html#moderated-t-tests-using-information-from-multiple-comparisons"><i class="fa fa-check"></i><b>3.2.4</b> Moderated t-tests: Using information from multiple comparisons</a></li>
</ul></li>
<li class="chapter" data-level="3.3" data-path="relationship-between-variables-linear-models-and-correlation.html"><a href="relationship-between-variables-linear-models-and-correlation.html"><i class="fa fa-check"></i><b>3.3</b> Relationship between variables: Linear models and correlation</a><ul>
<li class="chapter" data-level="3.3.1" data-path="relationship-between-variables-linear-models-and-correlation.html"><a href="relationship-between-variables-linear-models-and-correlation.html#how-to-fit-a-line"><i class="fa fa-check"></i><b>3.3.1</b> How to fit a line</a></li>
<li class="chapter" data-level="3.3.2" data-path="relationship-between-variables-linear-models-and-correlation.html"><a href="relationship-between-variables-linear-models-and-correlation.html#how-to-estimate-the-error-of-the-coefficients"><i class="fa fa-check"></i><b>3.3.2</b> How to estimate the error of the coefficients</a></li>
<li class="chapter" data-level="3.3.3" data-path="relationship-between-variables-linear-models-and-correlation.html"><a href="relationship-between-variables-linear-models-and-correlation.html#accuracy-of-the-model"><i class="fa fa-check"></i><b>3.3.3</b> Accuracy of the model</a></li>
<li class="chapter" data-level="3.3.4" data-path="relationship-between-variables-linear-models-and-correlation.html"><a href="relationship-between-variables-linear-models-and-correlation.html#regression-with-categorical-variables"><i class="fa fa-check"></i><b>3.3.4</b> Regression with categorical variables</a></li>
<li class="chapter" data-level="3.3.5" data-path="relationship-between-variables-linear-models-and-correlation.html"><a href="relationship-between-variables-linear-models-and-correlation.html#regression-pitfalls"><i class="fa fa-check"></i><b>3.3.5</b> Regression pitfalls</a></li>
</ul></li>
<li class="chapter" data-level="3.4" data-path="exercises-1.html"><a href="exercises-1.html"><i class="fa fa-check"></i><b>3.4</b> Exercises</a><ul>
<li class="chapter" data-level="3.4.1" data-path="exercises-1.html"><a href="exercises-1.html#how-to-summarize-collection-of-data-points-the-idea-behind-statistical-distributions-1"><i class="fa fa-check"></i><b>3.4.1</b> How to summarize collection of data points: The idea behind statistical distributions</a></li>
<li class="chapter" data-level="3.4.2" data-path="exercises-1.html"><a href="exercises-1.html#how-to-test-for-differences-in-samples"><i class="fa fa-check"></i><b>3.4.2</b> How to test for differences in samples</a></li>
<li class="chapter" data-level="3.4.3" data-path="exercises-1.html"><a href="exercises-1.html#relationship-between-variables-linear-models-and-correlation-1"><i class="fa fa-check"></i><b>3.4.3</b> Relationship between variables: Linear models and correlation</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="4" data-path="unsupervisedLearning.html"><a href="unsupervisedLearning.html"><i class="fa fa-check"></i><b>4</b> Exploratory Data Analysis with Unsupervised Machine Learning</a><ul>
<li class="chapter" data-level="4.1" data-path="clustering-grouping-samples-based-on-their-similarity.html"><a href="clustering-grouping-samples-based-on-their-similarity.html"><i class="fa fa-check"></i><b>4.1</b> Clustering: Grouping samples based on their similarity</a><ul>
<li class="chapter" data-level="4.1.1" data-path="clustering-grouping-samples-based-on-their-similarity.html"><a href="clustering-grouping-samples-based-on-their-similarity.html#distance-metrics"><i class="fa fa-check"></i><b>4.1.1</b> Distance metrics</a></li>
<li class="chapter" data-level="4.1.2" data-path="clustering-grouping-samples-based-on-their-similarity.html"><a href="clustering-grouping-samples-based-on-their-similarity.html#hiearchical-clustering"><i class="fa fa-check"></i><b>4.1.2</b> Hiearchical clustering</a></li>
<li class="chapter" data-level="4.1.3" data-path="clustering-grouping-samples-based-on-their-similarity.html"><a href="clustering-grouping-samples-based-on-their-similarity.html#k-means-clustering"><i class="fa fa-check"></i><b>4.1.3</b> K-means clustering</a></li>
<li class="chapter" data-level="4.1.4" data-path="clustering-grouping-samples-based-on-their-similarity.html"><a href="clustering-grouping-samples-based-on-their-similarity.html#how-to-choose-k-the-number-of-clusters"><i class="fa fa-check"></i><b>4.1.4</b> How to choose “k”, the number of clusters</a></li>
</ul></li>
<li class="chapter" data-level="4.2" data-path="dimensionality-reduction-techniques-visualizing-complex-data-sets-in-2d.html"><a href="dimensionality-reduction-techniques-visualizing-complex-data-sets-in-2d.html"><i class="fa fa-check"></i><b>4.2</b> Dimensionality reduction techniques: Visualizing complex data sets in 2D</a><ul>
<li class="chapter" data-level="4.2.1" data-path="dimensionality-reduction-techniques-visualizing-complex-data-sets-in-2d.html"><a href="dimensionality-reduction-techniques-visualizing-complex-data-sets-in-2d.html#principal-component-analysis"><i class="fa fa-check"></i><b>4.2.1</b> Principal component analysis</a></li>
<li class="chapter" data-level="4.2.2" data-path="dimensionality-reduction-techniques-visualizing-complex-data-sets-in-2d.html"><a href="dimensionality-reduction-techniques-visualizing-complex-data-sets-in-2d.html#other-matrix-factorization-methods-for-dimensionality-reduction"><i class="fa fa-check"></i><b>4.2.2</b> Other matrix factorization methods for dimensionality reduction</a></li>
<li class="chapter" data-level="4.2.3" data-path="dimensionality-reduction-techniques-visualizing-complex-data-sets-in-2d.html"><a href="dimensionality-reduction-techniques-visualizing-complex-data-sets-in-2d.html#multi-dimensional-scaling"><i class="fa fa-check"></i><b>4.2.3</b> Multi-dimensional scaling</a></li>
<li class="chapter" data-level="4.2.4" data-path="dimensionality-reduction-techniques-visualizing-complex-data-sets-in-2d.html"><a href="dimensionality-reduction-techniques-visualizing-complex-data-sets-in-2d.html#t-distributed-stochastic-neighbor-embedding-t-sne"><i class="fa fa-check"></i><b>4.2.4</b> t-Distributed Stochastic Neighbor Embedding (t-SNE)</a></li>
</ul></li>
<li class="chapter" data-level="4.3" data-path="exercises-2.html"><a href="exercises-2.html"><i class="fa fa-check"></i><b>4.3</b> Exercises</a><ul>
<li class="chapter" data-level="4.3.1" data-path="exercises-2.html"><a href="exercises-2.html#clustering"><i class="fa fa-check"></i><b>4.3.1</b> Clustering</a></li>
<li class="chapter" data-level="4.3.2" data-path="exercises-2.html"><a href="exercises-2.html#dimension-reduction"><i class="fa fa-check"></i><b>4.3.2</b> Dimension reduction</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="5" data-path="supervisedLearning.html"><a href="supervisedLearning.html"><i class="fa fa-check"></i><b>5</b> Predictive Modeling with Supervised Machine Learning</a><ul>
<li class="chapter" data-level="5.1" data-path="how-are-machine-learning-models-fit.html"><a href="how-are-machine-learning-models-fit.html"><i class="fa fa-check"></i><b>5.1</b> How are machine learning models fit?</a><ul>
<li class="chapter" data-level="5.1.1" data-path="how-are-machine-learning-models-fit.html"><a href="how-are-machine-learning-models-fit.html#machine-learning-vs.-statistics"><i class="fa fa-check"></i><b>5.1.1</b> Machine learning vs. statistics</a></li>
</ul></li>
<li class="chapter" data-level="5.2" data-path="steps-in-supervised-machine-learning.html"><a href="steps-in-supervised-machine-learning.html"><i class="fa fa-check"></i><b>5.2</b> Steps in supervised machine learning</a></li>
<li class="chapter" data-level="5.3" data-path="use-case-disease-subtype-from-genomics-data.html"><a href="use-case-disease-subtype-from-genomics-data.html"><i class="fa fa-check"></i><b>5.3</b> Use case: Disease subtype from genomics data</a></li>
<li class="chapter" data-level="5.4" data-path="data-preprocessing.html"><a href="data-preprocessing.html"><i class="fa fa-check"></i><b>5.4</b> Data preprocessing</a><ul>
<li class="chapter" data-level="5.4.1" data-path="data-preprocessing.html"><a href="data-preprocessing.html#data-transformation"><i class="fa fa-check"></i><b>5.4.1</b> Data transformation</a></li>
<li class="chapter" data-level="5.4.2" data-path="data-preprocessing.html"><a href="data-preprocessing.html#filtering-data-and-scaling"><i class="fa fa-check"></i><b>5.4.2</b> Filtering data and scaling</a></li>
<li class="chapter" data-level="5.4.3" data-path="data-preprocessing.html"><a href="data-preprocessing.html#dealing-with-missing-values"><i class="fa fa-check"></i><b>5.4.3</b> Dealing with missing values</a></li>
</ul></li>
<li class="chapter" data-level="5.5" data-path="splitting-the-data.html"><a href="splitting-the-data.html"><i class="fa fa-check"></i><b>5.5</b> Splitting the data</a><ul>
<li class="chapter" data-level="5.5.1" data-path="splitting-the-data.html"><a href="splitting-the-data.html#holdout-test-dataset"><i class="fa fa-check"></i><b>5.5.1</b> Holdout test dataset</a></li>
<li class="chapter" data-level="5.5.2" data-path="splitting-the-data.html"><a href="splitting-the-data.html#cross-validation"><i class="fa fa-check"></i><b>5.5.2</b> Cross-validation</a></li>
<li class="chapter" data-level="5.5.3" data-path="splitting-the-data.html"><a href="splitting-the-data.html#bootstrap-resampling"><i class="fa fa-check"></i><b>5.5.3</b> Bootstrap resampling</a></li>
</ul></li>
<li class="chapter" data-level="5.6" data-path="predicting-the-subtype-with-k-nearest-neighbors.html"><a href="predicting-the-subtype-with-k-nearest-neighbors.html"><i class="fa fa-check"></i><b>5.6</b> Predicting the subtype with k-nearest neighbors</a></li>
<li class="chapter" data-level="5.7" data-path="assessing-the-performance-of-our-model.html"><a href="assessing-the-performance-of-our-model.html"><i class="fa fa-check"></i><b>5.7</b> Assessing the performance of our model</a><ul>
<li class="chapter" data-level="5.7.1" data-path="assessing-the-performance-of-our-model.html"><a href="assessing-the-performance-of-our-model.html#receiver-operating-characteristic-roc-curves"><i class="fa fa-check"></i><b>5.7.1</b> Receiver Operating Characteristic (ROC) curves</a></li>
</ul></li>
<li class="chapter" data-level="5.8" data-path="model-tuning-and-avoiding-overfitting.html"><a href="model-tuning-and-avoiding-overfitting.html"><i class="fa fa-check"></i><b>5.8</b> Model tuning and avoiding overfitting</a><ul>
<li class="chapter" data-level="5.8.1" data-path="model-tuning-and-avoiding-overfitting.html"><a href="model-tuning-and-avoiding-overfitting.html#model-complexity-and-bias-variance-trade-off"><i class="fa fa-check"></i><b>5.8.1</b> Model complexity and bias variance trade-off</a></li>
<li class="chapter" data-level="5.8.2" data-path="model-tuning-and-avoiding-overfitting.html"><a href="model-tuning-and-avoiding-overfitting.html#data-split-strategies-for-model-tuning-and-testing"><i class="fa fa-check"></i><b>5.8.2</b> Data split strategies for model tuning and testing</a></li>
</ul></li>
<li class="chapter" data-level="5.9" data-path="variable-importance.html"><a href="variable-importance.html"><i class="fa fa-check"></i><b>5.9</b> Variable importance</a></li>
<li class="chapter" data-level="5.10" data-path="how-to-deal-with-class-imbalance.html"><a href="how-to-deal-with-class-imbalance.html"><i class="fa fa-check"></i><b>5.10</b> How to deal with class imbalance</a><ul>
<li class="chapter" data-level="5.10.1" data-path="how-to-deal-with-class-imbalance.html"><a href="how-to-deal-with-class-imbalance.html#sampling-for-class-balance"><i class="fa fa-check"></i><b>5.10.1</b> Sampling for class balance</a></li>
<li class="chapter" data-level="5.10.2" data-path="how-to-deal-with-class-imbalance.html"><a href="how-to-deal-with-class-imbalance.html#altering-case-weights"><i class="fa fa-check"></i><b>5.10.2</b> Altering case weights</a></li>
<li class="chapter" data-level="5.10.3" data-path="how-to-deal-with-class-imbalance.html"><a href="how-to-deal-with-class-imbalance.html#selecting-different-classification-score-cutoffs"><i class="fa fa-check"></i><b>5.10.3</b> Selecting different classification score cutoffs</a></li>
</ul></li>
<li class="chapter" data-level="5.11" data-path="dealing-with-correlated-predictors.html"><a href="dealing-with-correlated-predictors.html"><i class="fa fa-check"></i><b>5.11</b> Dealing with correlated predictors</a></li>
<li class="chapter" data-level="5.12" data-path="trees-and-forests-random-forests-in-action.html"><a href="trees-and-forests-random-forests-in-action.html"><i class="fa fa-check"></i><b>5.12</b> Trees and forests: Random forests in action</a><ul>
<li class="chapter" data-level="5.12.1" data-path="trees-and-forests-random-forests-in-action.html"><a href="trees-and-forests-random-forests-in-action.html#decision-trees"><i class="fa fa-check"></i><b>5.12.1</b> Decision trees</a></li>
<li class="chapter" data-level="5.12.2" data-path="trees-and-forests-random-forests-in-action.html"><a href="trees-and-forests-random-forests-in-action.html#trees-to-forests"><i class="fa fa-check"></i><b>5.12.2</b> Trees to forests</a></li>
<li class="chapter" data-level="5.12.3" data-path="trees-and-forests-random-forests-in-action.html"><a href="trees-and-forests-random-forests-in-action.html#variable-importance-1"><i class="fa fa-check"></i><b>5.12.3</b> Variable importance</a></li>
</ul></li>
<li class="chapter" data-level="5.13" data-path="logistic-regression-and-regularization.html"><a href="logistic-regression-and-regularization.html"><i class="fa fa-check"></i><b>5.13</b> Logistic regression and regularization</a><ul>
<li class="chapter" data-level="5.13.1" data-path="logistic-regression-and-regularization.html"><a href="logistic-regression-and-regularization.html#regularization-in-order-to-avoid-overfitting"><i class="fa fa-check"></i><b>5.13.1</b> Regularization in order to avoid overfitting</a></li>
<li class="chapter" data-level="5.13.2" data-path="logistic-regression-and-regularization.html"><a href="logistic-regression-and-regularization.html#variable-importance-2"><i class="fa fa-check"></i><b>5.13.2</b> Variable importance</a></li>
</ul></li>
<li class="chapter" data-level="5.14" data-path="other-supervised-algorithms.html"><a href="other-supervised-algorithms.html"><i class="fa fa-check"></i><b>5.14</b> Other supervised algorithms</a><ul>
<li class="chapter" data-level="5.14.1" data-path="other-supervised-algorithms.html"><a href="other-supervised-algorithms.html#gradient-boosting"><i class="fa fa-check"></i><b>5.14.1</b> Gradient boosting</a></li>
<li class="chapter" data-level="5.14.2" data-path="other-supervised-algorithms.html"><a href="other-supervised-algorithms.html#support-vector-machines-svm"><i class="fa fa-check"></i><b>5.14.2</b> Support Vector Machines (SVM)</a></li>
<li class="chapter" data-level="5.14.3" data-path="other-supervised-algorithms.html"><a href="other-supervised-algorithms.html#neural-networks-and-deep-versions-of-it"><i class="fa fa-check"></i><b>5.14.3</b> Neural networks and deep versions of it</a></li>
<li class="chapter" data-level="5.14.4" data-path="other-supervised-algorithms.html"><a href="other-supervised-algorithms.html#ensemble-learning"><i class="fa fa-check"></i><b>5.14.4</b> Ensemble learning</a></li>
</ul></li>
<li class="chapter" data-level="5.15" data-path="predicting-continuous-variables-regression-with-machine-learning.html"><a href="predicting-continuous-variables-regression-with-machine-learning.html"><i class="fa fa-check"></i><b>5.15</b> Predicting continuous variables: Regression with machine learning</a><ul>
<li class="chapter" data-level="5.15.1" data-path="predicting-continuous-variables-regression-with-machine-learning.html"><a href="predicting-continuous-variables-regression-with-machine-learning.html#use-case-predicting-age-from-dna-methylation"><i class="fa fa-check"></i><b>5.15.1</b> Use case: Predicting age from DNA methylation</a></li>
<li class="chapter" data-level="5.15.2" data-path="predicting-continuous-variables-regression-with-machine-learning.html"><a href="predicting-continuous-variables-regression-with-machine-learning.html#reading-and-processing-the-data"><i class="fa fa-check"></i><b>5.15.2</b> Reading and processing the data</a></li>
<li class="chapter" data-level="5.15.3" data-path="predicting-continuous-variables-regression-with-machine-learning.html"><a href="predicting-continuous-variables-regression-with-machine-learning.html#running-random-forest-regression"><i class="fa fa-check"></i><b>5.15.3</b> Running random forest regression</a></li>
</ul></li>
<li class="chapter" data-level="5.16" data-path="exercises-3.html"><a href="exercises-3.html"><i class="fa fa-check"></i><b>5.16</b> Exercises</a><ul>
<li class="chapter" data-level="5.16.1" data-path="exercises-3.html"><a href="exercises-3.html#classification"><i class="fa fa-check"></i><b>5.16.1</b> Classification</a></li>
<li class="chapter" data-level="5.16.2" data-path="exercises-3.html"><a href="exercises-3.html#regression"><i class="fa fa-check"></i><b>5.16.2</b> Regression</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="6" data-path="genomicIntervals.html"><a href="genomicIntervals.html"><i class="fa fa-check"></i><b>6</b> Operations on Genomic Intervals and Genome Arithmetic</a><ul>
<li class="chapter" data-level="6.1" data-path="operations-on-genomic-intervals-with-genomicranges-package.html"><a href="operations-on-genomic-intervals-with-genomicranges-package.html"><i class="fa fa-check"></i><b>6.1</b> Operations on genomic intervals with <code>GenomicRanges</code> package</a><ul>
<li class="chapter" data-level="6.1.1" data-path="operations-on-genomic-intervals-with-genomicranges-package.html"><a href="operations-on-genomic-intervals-with-genomicranges-package.html#how-to-create-and-manipulate-a-granges-object"><i class="fa fa-check"></i><b>6.1.1</b> How to create and manipulate a GRanges object</a></li>
<li class="chapter" data-level="6.1.2" data-path="operations-on-genomic-intervals-with-genomicranges-package.html"><a href="operations-on-genomic-intervals-with-genomicranges-package.html#getting-genomic-regions-into-r-as-granges-objects"><i class="fa fa-check"></i><b>6.1.2</b> Getting genomic regions into R as GRanges objects</a></li>
<li class="chapter" data-level="6.1.3" data-path="operations-on-genomic-intervals-with-genomicranges-package.html"><a href="operations-on-genomic-intervals-with-genomicranges-package.html#finding-regions-that-dodo-not-overlap-with-another-set-of-regions"><i class="fa fa-check"></i><b>6.1.3</b> Finding regions that do/do not overlap with another set of regions</a></li>
</ul></li>
<li class="chapter" data-level="6.2" data-path="dealing-with-mapped-high-throughput-sequencing-reads.html"><a href="dealing-with-mapped-high-throughput-sequencing-reads.html"><i class="fa fa-check"></i><b>6.2</b> Dealing with mapped high-throughput sequencing reads</a><ul>
<li class="chapter" data-level="6.2.1" data-path="dealing-with-mapped-high-throughput-sequencing-reads.html"><a href="dealing-with-mapped-high-throughput-sequencing-reads.html#counting-mapped-reads-for-a-set-of-regions"><i class="fa fa-check"></i><b>6.2.1</b> Counting mapped reads for a set of regions</a></li>
</ul></li>
<li class="chapter" data-level="6.3" data-path="dealing-with-continuous-scores-over-the-genome.html"><a href="dealing-with-continuous-scores-over-the-genome.html"><i class="fa fa-check"></i><b>6.3</b> Dealing with continuous scores over the genome</a><ul>
<li class="chapter" data-level="6.3.1" data-path="dealing-with-continuous-scores-over-the-genome.html"><a href="dealing-with-continuous-scores-over-the-genome.html#extracting-subsections-of-rle-and-rlelist-objects"><i class="fa fa-check"></i><b>6.3.1</b> Extracting subsections of Rle and RleList objects</a></li>
</ul></li>
<li class="chapter" data-level="6.4" data-path="genomic-intervals-with-more-information-summarizedexperiment-class.html"><a href="genomic-intervals-with-more-information-summarizedexperiment-class.html"><i class="fa fa-check"></i><b>6.4</b> Genomic intervals with more information: SummarizedExperiment class</a><ul>
<li class="chapter" data-level="6.4.1" data-path="genomic-intervals-with-more-information-summarizedexperiment-class.html"><a href="genomic-intervals-with-more-information-summarizedexperiment-class.html#create-a-summarizedexperiment-object"><i class="fa fa-check"></i><b>6.4.1</b> Create a SummarizedExperiment object</a></li>
<li class="chapter" data-level="6.4.2" data-path="genomic-intervals-with-more-information-summarizedexperiment-class.html"><a href="genomic-intervals-with-more-information-summarizedexperiment-class.html#subset-and-manipulate-the-summarizedexperiment-object"><i class="fa fa-check"></i><b>6.4.2</b> Subset and manipulate the SummarizedExperiment object</a></li>
</ul></li>
<li class="chapter" data-level="6.5" data-path="visualizing-and-summarizing-genomic-intervals.html"><a href="visualizing-and-summarizing-genomic-intervals.html"><i class="fa fa-check"></i><b>6.5</b> Visualizing and summarizing genomic intervals</a><ul>
<li class="chapter" data-level="6.5.1" data-path="visualizing-and-summarizing-genomic-intervals.html"><a href="visualizing-and-summarizing-genomic-intervals.html#visualizing-intervals-on-a-locus-of-interest"><i class="fa fa-check"></i><b>6.5.1</b> Visualizing intervals on a locus of interest</a></li>
<li class="chapter" data-level="6.5.2" data-path="visualizing-and-summarizing-genomic-intervals.html"><a href="visualizing-and-summarizing-genomic-intervals.html#summaries-of-genomic-intervals-on-multiple-loci"><i class="fa fa-check"></i><b>6.5.2</b> Summaries of genomic intervals on multiple loci</a></li>
<li class="chapter" data-level="6.5.3" data-path="visualizing-and-summarizing-genomic-intervals.html"><a href="visualizing-and-summarizing-genomic-intervals.html#making-karyograms-and-circos-plots"><i class="fa fa-check"></i><b>6.5.3</b> Making karyograms and circos plots</a></li>
</ul></li>
<li class="chapter" data-level="6.6" data-path="exercises-4.html"><a href="exercises-4.html"><i class="fa fa-check"></i><b>6.6</b> Exercises</a><ul>
<li class="chapter" data-level="6.6.1" data-path="exercises-4.html"><a href="exercises-4.html#operations-on-genomic-intervals-with-the-genomicranges-package"><i class="fa fa-check"></i><b>6.6.1</b> Operations on genomic intervals with the <code>GenomicRanges</code> package</a></li>
<li class="chapter" data-level="6.6.2" data-path="exercises-4.html"><a href="exercises-4.html#dealing-with-mapped-high-throughput-sequencing-reads-1"><i class="fa fa-check"></i><b>6.6.2</b> Dealing with mapped high-throughput sequencing reads</a></li>
<li class="chapter" data-level="6.6.3" data-path="exercises-4.html"><a href="exercises-4.html#dealing-with-contiguous-scores-over-the-genome"><i class="fa fa-check"></i><b>6.6.3</b> Dealing with contiguous scores over the genome</a></li>
<li class="chapter" data-level="6.6.4" data-path="exercises-4.html"><a href="exercises-4.html#visualizing-and-summarizing-genomic-intervals-1"><i class="fa fa-check"></i><b>6.6.4</b> Visualizing and summarizing genomic intervals</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="7" data-path="processingReads.html"><a href="processingReads.html"><i class="fa fa-check"></i><b>7</b> Quality Check, Processing and Alignment of High-throughput Sequencing Reads</a><ul>
<li class="chapter" data-level="7.1" data-path="fasta-and-fastq-formats.html"><a href="fasta-and-fastq-formats.html"><i class="fa fa-check"></i><b>7.1</b> FASTA and FASTQ formats</a></li>
<li class="chapter" data-level="7.2" data-path="quality-check-on-sequencing-reads.html"><a href="quality-check-on-sequencing-reads.html"><i class="fa fa-check"></i><b>7.2</b> Quality check on sequencing reads</a><ul>
<li class="chapter" data-level="7.2.1" data-path="quality-check-on-sequencing-reads.html"><a href="quality-check-on-sequencing-reads.html#sequence-quality-per-basecycle"><i class="fa fa-check"></i><b>7.2.1</b> Sequence quality per base/cycle</a></li>
<li class="chapter" data-level="7.2.2" data-path="quality-check-on-sequencing-reads.html"><a href="quality-check-on-sequencing-reads.html#sequence-content-per-basecycle"><i class="fa fa-check"></i><b>7.2.2</b> Sequence content per base/cycle</a></li>
<li class="chapter" data-level="7.2.3" data-path="quality-check-on-sequencing-reads.html"><a href="quality-check-on-sequencing-reads.html#read-frequency-plot"><i class="fa fa-check"></i><b>7.2.3</b> Read frequency plot</a></li>
<li class="chapter" data-level="7.2.4" data-path="quality-check-on-sequencing-reads.html"><a href="quality-check-on-sequencing-reads.html#other-quality-metrics-and-qc-tools"><i class="fa fa-check"></i><b>7.2.4</b> Other quality metrics and QC tools</a></li>
</ul></li>
<li class="chapter" data-level="7.3" data-path="filtering-and-trimming-reads.html"><a href="filtering-and-trimming-reads.html"><i class="fa fa-check"></i><b>7.3</b> Filtering and trimming reads</a></li>
<li class="chapter" data-level="7.4" data-path="mappingaligning-reads-to-the-genome.html"><a href="mappingaligning-reads-to-the-genome.html"><i class="fa fa-check"></i><b>7.4</b> Mapping/aligning reads to the genome</a></li>
<li class="chapter" data-level="7.5" data-path="further-processing-of-aligned-reads.html"><a href="further-processing-of-aligned-reads.html"><i class="fa fa-check"></i><b>7.5</b> Further processing of aligned reads</a></li>
<li class="chapter" data-level="7.6" data-path="exercises-5.html"><a href="exercises-5.html"><i class="fa fa-check"></i><b>7.6</b> Exercises</a></li>
</ul></li>
<li class="chapter" data-level="8" data-path="rnaseqanalysis.html"><a href="rnaseqanalysis.html"><i class="fa fa-check"></i><b>8</b> RNA-seq Analysis</a><ul>
<li class="chapter" data-level="8.1" data-path="what-is-gene-expression.html"><a href="what-is-gene-expression.html"><i class="fa fa-check"></i><b>8.1</b> What is gene expression?</a></li>
<li class="chapter" data-level="8.2" data-path="methods-to-detect-gene-expression.html"><a href="methods-to-detect-gene-expression.html"><i class="fa fa-check"></i><b>8.2</b> Methods to detect gene expression</a></li>
<li class="chapter" data-level="8.3" data-path="gene-expression-analysis-using-high-throughput-sequencing-technologies.html"><a href="gene-expression-analysis-using-high-throughput-sequencing-technologies.html"><i class="fa fa-check"></i><b>8.3</b> Gene expression analysis using high-throughput sequencing technologies</a><ul>
<li class="chapter" data-level="8.3.1" data-path="gene-expression-analysis-using-high-throughput-sequencing-technologies.html"><a href="gene-expression-analysis-using-high-throughput-sequencing-technologies.html#processing-raw-data"><i class="fa fa-check"></i><b>8.3.1</b> Processing raw data</a></li>
<li class="chapter" data-level="8.3.2" data-path="gene-expression-analysis-using-high-throughput-sequencing-technologies.html"><a href="gene-expression-analysis-using-high-throughput-sequencing-technologies.html#alignment"><i class="fa fa-check"></i><b>8.3.2</b> Alignment</a></li>
<li class="chapter" data-level="8.3.3" data-path="gene-expression-analysis-using-high-throughput-sequencing-technologies.html"><a href="gene-expression-analysis-using-high-throughput-sequencing-technologies.html#quantification"><i class="fa fa-check"></i><b>8.3.3</b> Quantification</a></li>
<li class="chapter" data-level="8.3.4" data-path="gene-expression-analysis-using-high-throughput-sequencing-technologies.html"><a href="gene-expression-analysis-using-high-throughput-sequencing-technologies.html#within-sample-normalization-of-the-read-counts"><i class="fa fa-check"></i><b>8.3.4</b> Within sample normalization of the read counts</a></li>
<li class="chapter" data-level="8.3.5" data-path="gene-expression-analysis-using-high-throughput-sequencing-technologies.html"><a href="gene-expression-analysis-using-high-throughput-sequencing-technologies.html#computing-different-normalization-schemes-in-r"><i class="fa fa-check"></i><b>8.3.5</b> Computing different normalization schemes in R</a></li>
<li class="chapter" data-level="8.3.6" data-path="gene-expression-analysis-using-high-throughput-sequencing-technologies.html"><a href="gene-expression-analysis-using-high-throughput-sequencing-technologies.html#exploratory-analysis-of-the-read-count-table"><i class="fa fa-check"></i><b>8.3.6</b> Exploratory analysis of the read count table</a></li>
<li class="chapter" data-level="8.3.7" data-path="gene-expression-analysis-using-high-throughput-sequencing-technologies.html"><a href="gene-expression-analysis-using-high-throughput-sequencing-technologies.html#differential-expression-analysis"><i class="fa fa-check"></i><b>8.3.7</b> Differential expression analysis</a></li>
<li class="chapter" data-level="8.3.8" data-path="gene-expression-analysis-using-high-throughput-sequencing-technologies.html"><a href="gene-expression-analysis-using-high-throughput-sequencing-technologies.html#functional-enrichment-analysis"><i class="fa fa-check"></i><b>8.3.8</b> Functional enrichment analysis</a></li>
<li class="chapter" data-level="8.3.9" data-path="gene-expression-analysis-using-high-throughput-sequencing-technologies.html"><a href="gene-expression-analysis-using-high-throughput-sequencing-technologies.html#accounting-for-additional-sources-of-variation"><i class="fa fa-check"></i><b>8.3.9</b> Accounting for additional sources of variation</a></li>
</ul></li>
<li class="chapter" data-level="8.4" data-path="other-applications-of-rna-seq.html"><a href="other-applications-of-rna-seq.html"><i class="fa fa-check"></i><b>8.4</b> Other applications of RNA-seq</a></li>
<li class="chapter" data-level="8.5" data-path="exercises-6.html"><a href="exercises-6.html"><i class="fa fa-check"></i><b>8.5</b> Exercises</a><ul>
<li class="chapter" data-level="8.5.1" data-path="exercises-6.html"><a href="exercises-6.html#exploring-the-count-tables"><i class="fa fa-check"></i><b>8.5.1</b> Exploring the count tables</a></li>
<li class="chapter" data-level="8.5.2" data-path="exercises-6.html"><a href="exercises-6.html#differential-expression-analysis-1"><i class="fa fa-check"></i><b>8.5.2</b> Differential expression analysis</a></li>
<li class="chapter" data-level="8.5.3" data-path="exercises-6.html"><a href="exercises-6.html#functional-enrichment-analysis-1"><i class="fa fa-check"></i><b>8.5.3</b> Functional enrichment analysis</a></li>
<li class="chapter" data-level="8.5.4" data-path="exercises-6.html"><a href="exercises-6.html#removing-unwanted-variation-from-the-expression-data"><i class="fa fa-check"></i><b>8.5.4</b> Removing unwanted variation from the expression data</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="9" data-path="chipseq.html"><a href="chipseq.html"><i class="fa fa-check"></i><b>9</b> ChIP-seq analysis</a><ul>
<li class="chapter" data-level="9.1" data-path="regulatory-protein-dna-interactions.html"><a href="regulatory-protein-dna-interactions.html"><i class="fa fa-check"></i><b>9.1</b> Regulatory protein-DNA interactions</a></li>
<li class="chapter" data-level="9.2" data-path="measuring-protein-dna-interactions-with-chip-seq.html"><a href="measuring-protein-dna-interactions-with-chip-seq.html"><i class="fa fa-check"></i><b>9.2</b> Measuring protein-DNA interactions with ChIP-seq</a></li>
<li class="chapter" data-level="9.3" data-path="factors-that-affect-chip-seq-experiment-and-analysis-quality.html"><a href="factors-that-affect-chip-seq-experiment-and-analysis-quality.html"><i class="fa fa-check"></i><b>9.3</b> Factors that affect ChIP-seq experiment and analysis quality</a><ul>
<li class="chapter" data-level="9.3.1" data-path="factors-that-affect-chip-seq-experiment-and-analysis-quality.html"><a href="factors-that-affect-chip-seq-experiment-and-analysis-quality.html#antibody-specificity"><i class="fa fa-check"></i><b>9.3.1</b> Antibody specificity</a></li>
<li class="chapter" data-level="9.3.2" data-path="factors-that-affect-chip-seq-experiment-and-analysis-quality.html"><a href="factors-that-affect-chip-seq-experiment-and-analysis-quality.html#sequencing-depth"><i class="fa fa-check"></i><b>9.3.2</b> Sequencing depth</a></li>
<li class="chapter" data-level="9.3.3" data-path="factors-that-affect-chip-seq-experiment-and-analysis-quality.html"><a href="factors-that-affect-chip-seq-experiment-and-analysis-quality.html#pcr-duplication"><i class="fa fa-check"></i><b>9.3.3</b> PCR duplication</a></li>
<li class="chapter" data-level="9.3.4" data-path="factors-that-affect-chip-seq-experiment-and-analysis-quality.html"><a href="factors-that-affect-chip-seq-experiment-and-analysis-quality.html#biological-replicates"><i class="fa fa-check"></i><b>9.3.4</b> Biological replicates</a></li>
<li class="chapter" data-level="9.3.5" data-path="factors-that-affect-chip-seq-experiment-and-analysis-quality.html"><a href="factors-that-affect-chip-seq-experiment-and-analysis-quality.html#control-experiments"><i class="fa fa-check"></i><b>9.3.5</b> Control experiments</a></li>
<li class="chapter" data-level="9.3.6" data-path="factors-that-affect-chip-seq-experiment-and-analysis-quality.html"><a href="factors-that-affect-chip-seq-experiment-and-analysis-quality.html#using-tagged-proteins"><i class="fa fa-check"></i><b>9.3.6</b> Using tagged proteins</a></li>
</ul></li>
<li class="chapter" data-level="9.4" data-path="pre-processing-chip-data.html"><a href="pre-processing-chip-data.html"><i class="fa fa-check"></i><b>9.4</b> Pre-processing ChIP data</a><ul>
<li class="chapter" data-level="9.4.1" data-path="pre-processing-chip-data.html"><a href="pre-processing-chip-data.html#mapping-of-chip-seq-data"><i class="fa fa-check"></i><b>9.4.1</b> Mapping of ChIP-seq data</a></li>
</ul></li>
<li class="chapter" data-level="9.5" data-path="chip-quality-control.html"><a href="chip-quality-control.html"><i class="fa fa-check"></i><b>9.5</b> ChIP quality control</a><ul>
<li class="chapter" data-level="9.5.1" data-path="chip-quality-control.html"><a href="chip-quality-control.html#the-data"><i class="fa fa-check"></i><b>9.5.1</b> The data</a></li>
<li class="chapter" data-level="9.5.2" data-path="chip-quality-control.html"><a href="chip-quality-control.html#sample-clustering"><i class="fa fa-check"></i><b>9.5.2</b> Sample clustering</a></li>
<li class="chapter" data-level="9.5.3" data-path="chip-quality-control.html"><a href="chip-quality-control.html#visualization-in-the-genome-browser"><i class="fa fa-check"></i><b>9.5.3</b> Visualization in the genome browser</a></li>
<li class="chapter" data-level="9.5.4" data-path="chip-quality-control.html"><a href="chip-quality-control.html#plus-and-minus-strand-cross-correlation"><i class="fa fa-check"></i><b>9.5.4</b> Plus and minus strand cross-correlation</a></li>
<li class="chapter" data-level="9.5.5" data-path="chip-quality-control.html"><a href="chip-quality-control.html#gc-bias-quantification"><i class="fa fa-check"></i><b>9.5.5</b> GC bias quantification</a></li>
<li class="chapter" data-level="9.5.6" data-path="chip-quality-control.html"><a href="chip-quality-control.html#sequence-read-genomic-distribution"><i class="fa fa-check"></i><b>9.5.6</b> Sequence read genomic distribution</a></li>
</ul></li>
<li class="chapter" data-level="9.6" data-path="peak-calling.html"><a href="peak-calling.html"><i class="fa fa-check"></i><b>9.6</b> Peak calling</a><ul>
<li class="chapter" data-level="9.6.1" data-path="peak-calling.html"><a href="peak-calling.html#types-of-chip-seq-experiments"><i class="fa fa-check"></i><b>9.6.1</b> Types of ChIP-seq experiments</a></li>
<li class="chapter" data-level="9.6.2" data-path="peak-calling.html"><a href="peak-calling.html#peak-calling-sharp-peaks"><i class="fa fa-check"></i><b>9.6.2</b> Peak calling: Sharp peaks</a></li>
<li class="chapter" data-level="9.6.3" data-path="peak-calling.html"><a href="peak-calling.html#peak-calling-broad-regions"><i class="fa fa-check"></i><b>9.6.3</b> Peak calling: Broad regions</a></li>
<li class="chapter" data-level="9.6.4" data-path="peak-calling.html"><a href="peak-calling.html#peak-quality-control"><i class="fa fa-check"></i><b>9.6.4</b> Peak quality control</a></li>
<li class="chapter" data-level="9.6.5" data-path="peak-calling.html"><a href="peak-calling.html#peak-annotation"><i class="fa fa-check"></i><b>9.6.5</b> Peak annotation</a></li>
</ul></li>
<li class="chapter" data-level="9.7" data-path="motif-discovery.html"><a href="motif-discovery.html"><i class="fa fa-check"></i><b>9.7</b> Motif discovery</a><ul>
<li class="chapter" data-level="9.7.1" data-path="motif-discovery.html"><a href="motif-discovery.html#motif-comparison"><i class="fa fa-check"></i><b>9.7.1</b> Motif comparison</a></li>
</ul></li>
<li class="chapter" data-level="9.8" data-path="what-to-do-next.html"><a href="what-to-do-next.html"><i class="fa fa-check"></i><b>9.8</b> What to do next?</a></li>
<li class="chapter" data-level="9.9" data-path="exercises-7.html"><a href="exercises-7.html"><i class="fa fa-check"></i><b>9.9</b> Exercises</a><ul>
<li class="chapter" data-level="9.9.1" data-path="exercises-7.html"><a href="exercises-7.html#quality-control"><i class="fa fa-check"></i><b>9.9.1</b> Quality control</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="10" data-path="bsseq.html"><a href="bsseq.html"><i class="fa fa-check"></i><b>10</b> DNA methylation analysis using bisulfite sequencing data</a><ul>
<li class="chapter" data-level="10.1" data-path="what-is-dna-methylation.html"><a href="what-is-dna-methylation.html"><i class="fa fa-check"></i><b>10.1</b> What is DNA methylation?</a><ul>
<li class="chapter" data-level="10.1.1" data-path="what-is-dna-methylation.html"><a href="what-is-dna-methylation.html#how-dna-methylation-is-set"><i class="fa fa-check"></i><b>10.1.1</b> How DNA methylation is set ?</a></li>
<li class="chapter" data-level="10.1.2" data-path="what-is-dna-methylation.html"><a href="what-is-dna-methylation.html#how-to-measure-dna-methylation-with-bisulfite-sequencing"><i class="fa fa-check"></i><b>10.1.2</b> How to measure DNA methylation with bisulfite sequencing</a></li>
</ul></li>
<li class="chapter" data-level="10.2" data-path="analyzing-dna-methylation-data.html"><a href="analyzing-dna-methylation-data.html"><i class="fa fa-check"></i><b>10.2</b> Analyzing DNA methylation data</a></li>
<li class="chapter" data-level="10.3" data-path="processing-raw-data-and-getting-data-into-r.html"><a href="processing-raw-data-and-getting-data-into-r.html"><i class="fa fa-check"></i><b>10.3</b> Processing raw data and getting data into R</a></li>
<li class="chapter" data-level="10.4" data-path="data-filtering-and-exploratory-analysis.html"><a href="data-filtering-and-exploratory-analysis.html"><i class="fa fa-check"></i><b>10.4</b> Data filtering and exploratory analysis</a><ul>
<li class="chapter" data-level="10.4.1" data-path="data-filtering-and-exploratory-analysis.html"><a href="data-filtering-and-exploratory-analysis.html#reading-methylation-call-files"><i class="fa fa-check"></i><b>10.4.1</b> Reading methylation call files</a></li>
<li class="chapter" data-level="10.4.2" data-path="data-filtering-and-exploratory-analysis.html"><a href="data-filtering-and-exploratory-analysis.html#further-quality-check"><i class="fa fa-check"></i><b>10.4.2</b> Further quality check</a></li>
<li class="chapter" data-level="10.4.3" data-path="data-filtering-and-exploratory-analysis.html"><a href="data-filtering-and-exploratory-analysis.html#merging-samples-into-a-single-table"><i class="fa fa-check"></i><b>10.4.3</b> Merging samples into a single table</a></li>
<li class="chapter" data-level="10.4.4" data-path="data-filtering-and-exploratory-analysis.html"><a href="data-filtering-and-exploratory-analysis.html#filtering-cpgs"><i class="fa fa-check"></i><b>10.4.4</b> Filtering CpGs</a></li>
<li class="chapter" data-level="10.4.5" data-path="data-filtering-and-exploratory-analysis.html"><a href="data-filtering-and-exploratory-analysis.html#clustering-samples"><i class="fa fa-check"></i><b>10.4.5</b> Clustering samples</a></li>
<li class="chapter" data-level="10.4.6" data-path="data-filtering-and-exploratory-analysis.html"><a href="data-filtering-and-exploratory-analysis.html#principal-component-analysis-1"><i class="fa fa-check"></i><b>10.4.6</b> Principal component analysis</a></li>
</ul></li>
<li class="chapter" data-level="10.5" data-path="extracting-interesting-regions-differential-methylation-and-segmentation.html"><a href="extracting-interesting-regions-differential-methylation-and-segmentation.html"><i class="fa fa-check"></i><b>10.5</b> Extracting interesting regions: Differential methylation and segmentation</a><ul>
<li class="chapter" data-level="10.5.1" data-path="extracting-interesting-regions-differential-methylation-and-segmentation.html"><a href="extracting-interesting-regions-differential-methylation-and-segmentation.html#differential-methylation"><i class="fa fa-check"></i><b>10.5.1</b> Differential methylation</a></li>
<li class="chapter" data-level="10.5.2" data-path="extracting-interesting-regions-differential-methylation-and-segmentation.html"><a href="extracting-interesting-regions-differential-methylation-and-segmentation.html#methylation-segmentation"><i class="fa fa-check"></i><b>10.5.2</b> Methylation segmentation</a></li>
<li class="chapter" data-level="10.5.3" data-path="extracting-interesting-regions-differential-methylation-and-segmentation.html"><a href="extracting-interesting-regions-differential-methylation-and-segmentation.html#working-with-large-files"><i class="fa fa-check"></i><b>10.5.3</b> Working with large files</a></li>
</ul></li>
<li class="chapter" data-level="10.6" data-path="annotation-of-dmrsdmcs-and-segments.html"><a href="annotation-of-dmrsdmcs-and-segments.html"><i class="fa fa-check"></i><b>10.6</b> Annotation of DMRs/DMCs and segments</a><ul>
<li class="chapter" data-level="10.6.1" data-path="annotation-of-dmrsdmcs-and-segments.html"><a href="annotation-of-dmrsdmcs-and-segments.html#further-annotation-with-genes-or-gene-sets"><i class="fa fa-check"></i><b>10.6.1</b> Further annotation with genes or gene sets</a></li>
</ul></li>
<li class="chapter" data-level="10.7" data-path="other-r-packages-that-can-be-used-for-methylation-analysis.html"><a href="other-r-packages-that-can-be-used-for-methylation-analysis.html"><i class="fa fa-check"></i><b>10.7</b> Other R packages that can be used for methylation analysis</a></li>
<li class="chapter" data-level="10.8" data-path="exercises-8.html"><a href="exercises-8.html"><i class="fa fa-check"></i><b>10.8</b> Exercises</a><ul>
<li class="chapter" data-level="10.8.1" data-path="exercises-8.html"><a href="exercises-8.html#differential-methylation-1"><i class="fa fa-check"></i><b>10.8.1</b> Differential methylation</a></li>
<li class="chapter" data-level="10.8.2" data-path="exercises-8.html"><a href="exercises-8.html#methylome-segmentation"><i class="fa fa-check"></i><b>10.8.2</b> Methylome segmentation</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="11" data-path="multiomics.html"><a href="multiomics.html"><i class="fa fa-check"></i><b>11</b> Multi-omics Analysis</a><ul>
<li class="chapter" data-level="11.1" data-path="use-case-multi-omics-data-from-colorectal-cancer.html"><a href="use-case-multi-omics-data-from-colorectal-cancer.html"><i class="fa fa-check"></i><b>11.1</b> Use case: Multi-omics data from colorectal cancer</a></li>
<li class="chapter" data-level="11.2" data-path="latent-variable-models-for-multi-omics-integration.html"><a href="latent-variable-models-for-multi-omics-integration.html"><i class="fa fa-check"></i><b>11.2</b> Latent variable models for multi-omics integration</a></li>
<li class="chapter" data-level="11.3" data-path="matrix-factorization-methods-for-unsupervised-multi-omics-data-integration.html"><a href="matrix-factorization-methods-for-unsupervised-multi-omics-data-integration.html"><i class="fa fa-check"></i><b>11.3</b> Matrix factorization methods for unsupervised multi-omics data integration</a><ul>
<li class="chapter" data-level="11.3.1" data-path="matrix-factorization-methods-for-unsupervised-multi-omics-data-integration.html"><a href="matrix-factorization-methods-for-unsupervised-multi-omics-data-integration.html#multiple-factor-analysis"><i class="fa fa-check"></i><b>11.3.1</b> Multiple factor analysis</a></li>
<li class="chapter" data-level="11.3.2" data-path="matrix-factorization-methods-for-unsupervised-multi-omics-data-integration.html"><a href="matrix-factorization-methods-for-unsupervised-multi-omics-data-integration.html#joint-non-negative-matrix-factorization"><i class="fa fa-check"></i><b>11.3.2</b> Joint non-negative matrix factorization</a></li>
<li class="chapter" data-level="11.3.3" data-path="matrix-factorization-methods-for-unsupervised-multi-omics-data-integration.html"><a href="matrix-factorization-methods-for-unsupervised-multi-omics-data-integration.html#icluster"><i class="fa fa-check"></i><b>11.3.3</b> iCluster</a></li>
</ul></li>
<li class="chapter" data-level="11.4" data-path="clustering-using-latent-factors.html"><a href="clustering-using-latent-factors.html"><i class="fa fa-check"></i><b>11.4</b> Clustering using latent factors</a><ul>
<li class="chapter" data-level="11.4.1" data-path="clustering-using-latent-factors.html"><a href="clustering-using-latent-factors.html#one-hot-clustering"><i class="fa fa-check"></i><b>11.4.1</b> One-hot clustering</a></li>
<li class="chapter" data-level="11.4.2" data-path="clustering-using-latent-factors.html"><a href="clustering-using-latent-factors.html#k-means-clustering-1"><i class="fa fa-check"></i><b>11.4.2</b> K-means clustering</a></li>
</ul></li>
<li class="chapter" data-level="11.5" data-path="biological-interpretation-of-latent-factors.html"><a href="biological-interpretation-of-latent-factors.html"><i class="fa fa-check"></i><b>11.5</b> Biological interpretation of latent factors</a><ul>
<li class="chapter" data-level="11.5.1" data-path="biological-interpretation-of-latent-factors.html"><a href="biological-interpretation-of-latent-factors.html#inspection-of-feature-weights-in-loading-vectors"><i class="fa fa-check"></i><b>11.5.1</b> Inspection of feature weights in loading vectors</a></li>
<li class="chapter" data-level="11.5.2" data-path="biological-interpretation-of-latent-factors.html"><a href="biological-interpretation-of-latent-factors.html#making-sense-of-factors-using-enrichment-analysis"><i class="fa fa-check"></i><b>11.5.2</b> Making sense of factors using enrichment analysis</a></li>
<li class="chapter" data-level="11.5.3" data-path="biological-interpretation-of-latent-factors.html"><a href="biological-interpretation-of-latent-factors.html#interpretation-using-additional-covariates"><i class="fa fa-check"></i><b>11.5.3</b> Interpretation using additional covariates</a></li>
</ul></li>
<li class="chapter" data-level="11.6" data-path="exercises-9.html"><a href="exercises-9.html"><i class="fa fa-check"></i><b>11.6</b> Exercises</a><ul>
<li class="chapter" data-level="11.6.1" data-path="exercises-9.html"><a href="exercises-9.html#matrix-factorization-methods"><i class="fa fa-check"></i><b>11.6.1</b> Matrix factorization methods</a></li>
<li class="chapter" data-level="11.6.2" data-path="exercises-9.html"><a href="exercises-9.html#clustering-using-latent-factors-1"><i class="fa fa-check"></i><b>11.6.2</b> Clustering using latent factors</a></li>
<li class="chapter" data-level="11.6.3" data-path="exercises-9.html"><a href="exercises-9.html#biological-interpretation-of-latent-factors-1"><i class="fa fa-check"></i><b>11.6.3</b> Biological interpretation of latent factors</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="" data-path="references.html"><a href="references.html"><i class="fa fa-check"></i>References</a></li>
<li class="divider"></li>
<li><a href="https://bookdown.org" target="_blank">Published with bookdown</a></li>
</ul>
</nav>
</div>
<div class="book-body">
<div class="body-inner">
<div class="book-header" role="navigation">
<h1>
<i class="fa fa-circle-o-notch fa-spin"></i><a href="./">Computational Genomics with R</a>
</h1>
</div>
<div class="page-wrapper" tabindex="-1" role="main">
<div class="page-inner">
<section class="normal" id="section-">
<div id="exercises-3" class="section level2">
<h2><span class="header-section-number">5.16</span> Exercises</h2>
<div id="classification" class="section level3">
<h3><span class="header-section-number">5.16.1</span> Classification</h3>
<p>For this set of exercises we will be using the gene expression and patient annotation data from the glioblastoma patient. You can read the data as shown below:</p>
<div class="sourceCode" id="cb299"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb299-1"><a href="exercises-3.html#cb299-1"></a><span class="kw">library</span>(compGenomRData)</span>
<span id="cb299-2"><a href="exercises-3.html#cb299-2"></a><span class="co"># get file paths</span></span>
<span id="cb299-3"><a href="exercises-3.html#cb299-3"></a>fileLGGexp=<span class="kw">system.file</span>(<span class="st">"extdata"</span>,</span>
<span id="cb299-4"><a href="exercises-3.html#cb299-4"></a> <span class="st">"LGGrnaseq.rds"</span>,</span>
<span id="cb299-5"><a href="exercises-3.html#cb299-5"></a> <span class="dt">package=</span><span class="st">"compGenomRData"</span>)</span>
<span id="cb299-6"><a href="exercises-3.html#cb299-6"></a>fileLGGann=<span class="kw">system.file</span>(<span class="st">"extdata"</span>,</span>
<span id="cb299-7"><a href="exercises-3.html#cb299-7"></a> <span class="st">"patient2LGGsubtypes.rds"</span>,</span>
<span id="cb299-8"><a href="exercises-3.html#cb299-8"></a> <span class="dt">package=</span><span class="st">"compGenomRData"</span>)</span>
<span id="cb299-9"><a href="exercises-3.html#cb299-9"></a><span class="co"># gene expression values</span></span>
<span id="cb299-10"><a href="exercises-3.html#cb299-10"></a>gexp=<span class="kw">readRDS</span>(fileLGGexp)</span>
<span id="cb299-11"><a href="exercises-3.html#cb299-11"></a></span>
<span id="cb299-12"><a href="exercises-3.html#cb299-12"></a><span class="co"># patient annotation</span></span>
<span id="cb299-13"><a href="exercises-3.html#cb299-13"></a>patient=<span class="kw">readRDS</span>(fileLGGann)</span></code></pre></div>
<ol style="list-style-type: decimal">
<li><p>Our first task is to not use any data transformation and do classification. Run the k-NN classifier on the data without any transformation or scaling. What is the effect on classification accuracy for k-NN predicting the CIMP and noCIMP status of the patient? [Difficulty: <strong>Beginner</strong>]</p></li>
<li><p>Bootstrap resampling can be used to measure the variability of the prediction error. Use bootstrap resampling with k-NN for the prediction accuracy. How different is it from cross-validation for different <span class="math inline">\(k\)</span>s? [Difficulty: <strong>Intermediate</strong>]</p></li>
<li><p>There are a number of ways to get variable importance for a classification problem. Run random forests on the classification problem above. Compare the variable importance metrics from random forest and the one obtained from DALEX. How many variables are the same in the top 10? [Difficulty: <strong>Advanced</strong>]</p></li>
<li><p>Come up with a unified importance score by normalizing importance scores from random forests and DALEX, followed by taking the average of those scores. [Difficulty: <strong>Advanced</strong>]</p></li>
</ol>
</div>
<div id="regression" class="section level3">
<h3><span class="header-section-number">5.16.2</span> Regression</h3>
<p>For this set of problems we will use the regression data set where we tried to predict the age of the sample from the methylation values. The data can be loaded as shown below:</p>
<div class="sourceCode" id="cb300"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb300-1"><a href="exercises-3.html#cb300-1"></a><span class="co"># file path for CpG methylation and age</span></span>
<span id="cb300-2"><a href="exercises-3.html#cb300-2"></a>fileMethAge=<span class="kw">system.file</span>(<span class="st">"extdata"</span>,</span>
<span id="cb300-3"><a href="exercises-3.html#cb300-3"></a> <span class="st">"CpGmeth2Age.rds"</span>,</span>
<span id="cb300-4"><a href="exercises-3.html#cb300-4"></a> <span class="dt">package=</span><span class="st">"compGenomRData"</span>)</span>
<span id="cb300-5"><a href="exercises-3.html#cb300-5"></a></span>
<span id="cb300-6"><a href="exercises-3.html#cb300-6"></a><span class="co"># read methylation-age table</span></span>
<span id="cb300-7"><a href="exercises-3.html#cb300-7"></a>ameth=<span class="kw">readRDS</span>(fileMethAge)</span></code></pre></div>
<ol style="list-style-type: decimal">
<li><p>Run random forest regression and plot the importance metrics. [Difficulty: <strong>Beginner</strong>]</p></li>
<li><p>Split 20% of the methylation-age data as test data and run elastic net regression on the training portion to tune parameters and test it on the test portion. [Difficulty: <strong>Intermediate</strong>]</p></li>
<li><p>Run an ensemble model for regression using the <strong>caretEnsemble</strong> or <strong>mlr</strong> package and compare the results with the elastic net and random forest model. Did the test accuracy increase?
<strong>HINT:</strong> You need to install these extra packages and learn how to use them in the context of ensemble models. [Difficulty: <strong>Advanced</strong>]</p></li>
</ol>
</div>
</div>
<!-- </div> -->
</section>
</div>
</div>
</div>
<a href="predicting-continuous-variables-regression-with-machine-learning.html" class="navigation navigation-prev " aria-label="Previous page"><i class="fa fa-angle-left"></i></a>
<a href="genomicIntervals.html" class="navigation navigation-next " aria-label="Next page"><i class="fa fa-angle-right"></i></a>
</div>
</div>
<script src="libs/gitbook-2.6.7/js/app.min.js"></script>
<script src="libs/gitbook-2.6.7/js/lunr.js"></script>
<script src="libs/gitbook-2.6.7/js/clipboard.min.js"></script>
<script src="libs/gitbook-2.6.7/js/plugin-search.js"></script>
<script src="libs/gitbook-2.6.7/js/plugin-sharing.js"></script>
<script src="libs/gitbook-2.6.7/js/plugin-fontsettings.js"></script>
<script src="libs/gitbook-2.6.7/js/plugin-bookdown.js"></script>
<script src="libs/gitbook-2.6.7/js/jquery.highlight.js"></script>
<script src="libs/gitbook-2.6.7/js/plugin-clipboard.js"></script>
<script>
gitbook.require(["gitbook"], function(gitbook) {
gitbook.start({
"sharing": {
"github": true,
"facebook": false,
"twitter": true,
"linkedin": false,
"weibo": false,
"instapaper": false,
"vk": false,
"all": ["facebook", "twitter", "linkedin", "weibo", "instapaper"]
},
"fontsettings": {
"theme": "white",
"family": "sans",
"size": 2
},
"edit": {
"link": "https://github.com/compgenomr/book/edit/master/05-supervisedLearning.Rmd",
"text": "Edit"
},
"history": {
"link": null,
"text": null
},
"view": {
"link": null,
"text": null
},
"download": null,
"toc": {
"collapse": "none"
}
});
});
</script>
<!-- dynamically load mathjax for compatibility with self-contained -->
<script>
(function () {
var script = document.createElement("script");
script.type = "text/javascript";
var src = "true";
if (src === "" || src === "true") src = "https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-MML-AM_CHTML";
if (location.protocol !== "file:")
if (/^https?:/.test(src))
src = src.replace(/^https?:/, '');
script.src = src;
document.getElementsByTagName("head")[0].appendChild(script);
})();
</script>
</body>
</html>