-
Notifications
You must be signed in to change notification settings - Fork 0
/
intro-bioconductor.html
782 lines (597 loc) · 21 KB
/
intro-bioconductor.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
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
<!DOCTYPE html>
<html lang="" xml:lang="">
<head>
<title> An introduction to the R/Bioconductor Ecosystem</title>
<meta charset="utf-8" />
<meta name="author" content="Joselyn Chávez Twitter: @josschavezf1 josschavezf.netlify.app" />
<script src="libs/header-attrs-2.6/header-attrs.js"></script>
<link href="libs/remark-css-0.0.1/default.css" rel="stylesheet" />
<link href="libs/remark-css-0.0.1/rladies.css" rel="stylesheet" />
<link href="libs/remark-css-0.0.1/rladies-fonts.css" rel="stylesheet" />
<script src="libs/clipboard-2.0.6/clipboard.min.js"></script>
<link href="libs/xaringanExtra-clipboard-0.2.4/xaringanExtra-clipboard.css" rel="stylesheet" />
<script src="libs/xaringanExtra-clipboard-0.2.4/xaringanExtra-clipboard.js"></script>
<script>window.xaringanExtraClipboard(null, {"button":"Copy Code","success":"Copied!","error":"Press Ctrl+C to Copy"})</script>
</head>
<body>
<textarea id="source">
class: inverse center middle
background-image: url("images/joss.png"), url("images/rladies-bmore.png")
background-size: 140px, 140px
background-position: 90% 90%, 5% 5%
# <br> <br> An introduction to the R/Bioconductor Ecosystem
## Joselyn Chávez <br> <br> Twitter: @josschavezf1 <br> josschavezf.netlify.app
### January 28th, 2021
---
.center[
# Materials are available at:
## http://github.com/josschavezf/intro_bioconductor
# Or you can download them by running the following code in your R session:
]
```r
if (!require("usethis")) {
install.packages("usethis") }
usethis::use_course("josschavezf/intro_bioconductor")
```
---
class: middle center
# Slides are available at
## https://josschavezf.github.io/slides_rladies_bmore/intro-bioconductor.html
---
# What is Bioconductor?
A repository for the analysis of genomic data.
.center[
<img src = "images/sequencing.png" style="width:800px; " />
At date, contains **1974** software packages.
]
---
## Bioconductor have diferent types of packages:
<img src = "images/bioconductorlogo.jpg" style="width:400px; position:absolute; top:500px; left:280px; " />
.pull-left[
* Software (functions)
- Read sequence files
- Count
- Normalize
- Find differences
- Plot
* Annotation
- Databases
- Organism Sequences
- Gene identity
]
--
.pull-right[
* Experiment
- Sequences from a biological experiment.
- Functions to analyze the data.
- Lead to a result with biological relevance.
* Workflow
- Implementation of multiple Bioconductor packages.
- Show the steps to perform an analysis.
]
---
# How do we access to Bioconductor?
.center[
### https://www.bioconductor.org
<img src = "images/bioconductor.png" style="width:550px;" />
]
---
# How do we access to Bioconductor?
We will use the package **BiocManager**
Run the following code in your R session to install:
```r
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
```
--
**BiocManager** help us to:
* Install any package from Bioconductor, for example the package **Biostrings**:
```r
BiocManager::install("Biostrings")
```
--
* Keep all your installed Bioconductor packages up to date.
```r
BiocManager::install(version = "3.12")
```
<br>
Note: Bioconductor is updated twice a year, around April and October.
---
# The Bioconductor Environment
There are some kind of data, such as sequences and alignments that need to be treated in a different way that we use to do with lists or data frames.
Let's see some packages that will help us to deal with genomics data.
* Biostrings
* GenomicRanges
* AnnotationHub
* Gviz
<img src = "images/bioconductorlogo.jpg" style="width:400px; position:absolute; top:500px; left:430px; " />
---
# Manipulation of genomic sequences
The package **Biostrings** have functions to read, write and handling genomic sequences.
## Import data
```r
eco <- readDNAStringSet("../data/eco.fasta")
```
```
## DNAStringSet object of length 5:
## width seq names
## [1] 66 ATGAAACGCATTAGCACCACCATTACCAC...CATTACCACAGGTAACGGTGCGGGCTGA eco-b0001
## [2] 2463 ATGCGAGTGTTGAAGTTCGGCGGTACATC...TACCCTCTCATGGAAGTTAGGAGTCTGA eco-b0002
## [3] 933 ATGGTTAAAGTTTATGCCCCGGCTTCCAG...GGCGGGCGCACGAGTACTGGAAAACTAA eco-b0003
## [4] 1287 ATGAAACTCTACAATCTGAAAGATCACAA...GCGTAAATTGATGATGAATCATCAGTAA eco-b0004
## [5] 297 GTGAAAAAGATGCAATCTATCGTACTCGC...TCATGGTCCAGGCAAACATCACCGCTAA eco-b0005
```
---
We can get some attributes of the data, as well as subset some sequences of interest.
* Get the number of sequences
```r
length(eco)
```
```
## [1] 5
```
--
* Get the number of characters on each sequence.
```r
nchar(eco)
```
```
## [1] 66 2463 933 1287 297
```
--
* Get the frequency of specific characters
```r
letterFrequency(eco, "GC")
```
```
## G|C
## [1,] 34
## [2,] 1307
## [3,] 525
## [4,] 680
## [5,] 160
```
---
* Subset sequences
```r
eco[1:2]
```
```
## DNAStringSet object of length 2:
## width seq names
## [1] 66 ATGAAACGCATTAGCACCACCATTACCAC...CATTACCACAGGTAACGGTGCGGGCTGA eco-b0001
## [2] 2463 ATGCGAGTGTTGAAGTTCGGCGGTACATC...TACCCTCTCATGGAAGTTAGGAGTCTGA eco-b0002
```
```r
subseq(eco,start = 1, end = 10)
```
```
## DNAStringSet object of length 5:
## width seq names
## [1] 10 ATGAAACGCA eco-b0001
## [2] 10 ATGCGAGTGT eco-b0002
## [3] 10 ATGGTTAAAG eco-b0003
## [4] 10 ATGAAACTCT eco-b0004
## [5] 10 GTGAAAAAGA eco-b0005
```
--
* Translate sequences to amino acids
```r
translate(eco$`eco-b0001`)
```
```
## 22-letter AAString object
## seq: MKRISTTITTTITITTGNGAG*
```
---
## We can store more information from each sequence, (eg. genomic position and chromosome).
.center[
<img src = "images/genesABC.png" style="width:600px; " />
]
---
We need to use a **GenomicRanges** object.
```r
library(GenomicRanges)
GRanges(seqnames = c("geneA", "geneB", "geneC"),
ranges = IRanges(start = c(10, 20, 32),
end = c(15,27,42) ),
strand = c("+", "+", "-") )
```
```
## GRanges object with 3 ranges and 0 metadata columns:
## seqnames ranges strand
## <Rle> <IRanges> <Rle>
## [1] geneA 10-15 +
## [2] geneB 20-27 +
## [3] geneC 32-42 -
## -------
## seqinfo: 3 sequences from an unspecified genome; no seqlengths
```
.center[
<img src = "images/genesABC.png" style="width:450px; " />
]
--
* Note that we are using a special way to define the genomic position (IRanges)
---
# We can add more information by using Rle objects and metadata columns
```r
GRanges(seqnames = Rle(c("chr2", "chr2", "chr1", "chr3"),
c(1, 1, 2, 1)),
ranges = IRanges(1:5, width=10:14,
names=head(letters, 5)),
strand = Rle(strand(c("-", "+", "*")), c( 1,3, 1)),
score=1:5, GC=seq(1, 0, length=5) )
```
```
## GRanges object with 5 ranges and 2 metadata columns:
## seqnames ranges strand | score GC
## <Rle> <IRanges> <Rle> | <integer> <numeric>
## a chr2 1-10 - | 1 1.00
## b chr2 2-12 + | 2 0.75
## c chr1 3-14 + | 3 0.50
## d chr1 4-16 + | 4 0.25
## e chr3 5-18 * | 5 0.00
## -------
## seqinfo: 3 sequences from an unspecified genome; no seqlengths
```
---
# Genomic regions with biological relevance
.center[
<img src = "images/splicing.png" style="width:600px; " />
]
--
```
## GRanges object with 2 ranges and 1 metadata column:
## seqnames ranges strand | exon_id
## <Rle> <IRanges> <Rle> | <numeric>
## [1] geneM 10-15 + | 1
## [2] geneM 32-42 + | 2
## -------
## seqinfo: 1 sequence from an unspecified genome; no seqlengths
```
---
```
## GRanges object with 2 ranges and 1 metadata column:
## seqnames ranges strand | exon_id
## <Rle> <IRanges> <Rle> | <numeric>
## [1] geneM 10-15 + | 1
## [2] geneM 32-42 + | 2
## -------
## seqinfo: 1 sequence from an unspecified genome; no seqlengths
```
**range** retrieves the pre-processed gene range (with introns and exons)
```r
range(gr)
```
```
## GRanges object with 1 range and 0 metadata columns:
## seqnames ranges strand
## <Rle> <IRanges> <Rle>
## [1] geneM 10-42 +
## -------
## seqinfo: 1 sequence from an unspecified genome; no seqlengths
```
---
# Genomic regions with biological relevance
.center[
<img src = "images/promoter.png" style="width:600px; " />
]
**flank()** retrieves the upstream regulatory region
```r
gr <- GRanges(seqnames = "geneO",
ranges = IRanges(start = c(120, 180),
end = c(150,240) ),
strand = "+",
exon_id = c(1,2) )
flank(gr, 100)
```
```
## GRanges object with 2 ranges and 1 metadata column:
## seqnames ranges strand | exon_id
## <Rle> <IRanges> <Rle> | <numeric>
## [1] geneO 20-119 + | 1
## [2] geneO 80-179 + | 2
## -------
## seqinfo: 1 sequence from an unspecified genome; no seqlengths
```
---
class: center
<br><br>
# Where can we find genomic data?
--
# AnnotationHub
<img src = "images/journey.jpeg" style="width:350px;" />
---
# AnnotationHub
**AnnotationHub** connect with multiple genomic data providers and give us access to their data.
First use AnnotationHub() function to connect with the database.
Then, we are ready to explore available data.
```r
ah = AnnotationHub()
ah$species
```
```
## snapshotDate(): 2020-10-27
```
```
## [1] "Homo sapiens" "Vicugna pacos" "Dasypus novemcinctus"
## [4] "Otolemur garnettii" "Papio hamadryas" "Papio anubis"
## [7] "Felis catus" "Pan troglodytes" "Bos taurus"
## [10] "Canis familiaris"
```
At date, AnnotationHub contains data from 2643 species.
---
Once you find the desired data, you can download it to your session.
```r
hg_genes <- ah[["AH5036"]]
head(hg_genes)
```
```
## UCSC track 'knownGene'
## UCSCData object with 6 ranges and 5 metadata columns:
## seqnames ranges strand | name score itemRgb thick
## <Rle> <IRanges> <Rle> | <character> <numeric> <character> <IRanges>
## [1] chr1 11874-14409 + | uc001aaa.3 0 <NA> 11874-11873
## [2] chr1 11874-14409 + | uc010nxr.1 0 <NA> 11874-11873
## [3] chr1 11874-14409 + | uc010nxq.1 0 <NA> 12190-13639
## [4] chr1 14362-16765 - | uc009vis.3 0 <NA> 14362-14361
## [5] chr1 16858-17751 - | uc009vjc.1 0 <NA> 16858-16857
## [6] chr1 15796-18061 - | uc009vjd.2 0 <NA> 15796-15795
## blocks
## <IRangesList>
## [1] 1-354,740-848,1348-2536
## [2] 1-354,773-824,1348-2536
## [3] 1-354,722-848,1530-2536
## [4] 1-468,609-677,1435-1581,...
## [5] 1-198,376-894
## [6] 1-152,812-970,1063-1260,...
## -------
## seqinfo: 93 sequences (1 circular) from hg19 genome
```
Note that the results is a GRanges object
---
# Annotation packages for specific organisms
**org.Hs.eg.db** Maps Gene identifiers to GenBank Accession Numbers for the Human genome
```r
x <- org.Hs.eg.db
AnnotationDbi::select(x,
keys = "ATRX chromatin remodeler",
keytype = "GENENAME",
columns = c("ENTREZID",
"ALIAS", "UNIPROT") )
```
.center[
```
## GENENAME ENTREZID ALIAS UNIPROT
## 1 ATRX chromatin remodeler 546 JMS A4LAA3
## 2 ATRX chromatin remodeler 546 JMS B4DLW1
## 3 ATRX chromatin remodeler 546 JMS P46100
## 4 ATRX chromatin remodeler 546 MRX52 A4LAA3
## 5 ATRX chromatin remodeler 546 MRX52 B4DLW1
## 6 ATRX chromatin remodeler 546 MRX52 P46100
## 7 ATRX chromatin remodeler 546 RAD54 A4LAA3
## 8 ATRX chromatin remodeler 546 RAD54 B4DLW1
## 9 ATRX chromatin remodeler 546 RAD54 P46100
## 10 ATRX chromatin remodeler 546 RAD54L A4LAA3
```
]
---
# Plotting biological data
The package **Gviz** have functions to make representations of a variety of genomic annotation features, using data from public resources (e.g. ENSEMBL or UCSC) or in-house curated data.
Pros of using Gviz: plotting flexibility.
.center[
<!-- -->
]
---
# You can submit your own packages!
.center[
<img src = "images/cdsb.png" style="width:400px; " />
<img src = "images/regutoolsteam.png" style="width:500px; " />
]
--
<img src = "images/regutools1.png" style="width:180px; position:absolute; top:400px; left:140px; " />
--
<img src = "images/regutools2.png" style="width:410px; position:absolute; top:405px; left:350px; " />
.center[
<br><br><br><br><br><br><br><br><br><br>
http://www.bioconductor.org/packages/regutools
]
---
# How regutools works?
First we need to connect with the database and create a *regulondb* object:
```r
regulondb_conn <- connect_database()
e_coli_regulondb <-
regulondb(
database_conn = regulondb_conn,
organism = "E.coli",
database_version = "1",
genome_version = "1"
)
```
---
# Integration of regutools with the Bioconductor Ecosystem
The function **convert_to_granges()** converts a **regulondb_result** object into a **GRanges** object whenever possible to facilitate the integration with other Bioconductor workflows.
```r
res <- get_dataset(
regulondb = e_coli_regulondb,
dataset = "GENE",
attributes = c("posleft", "posright", "strand", "name"),
filters = list("name" = c("araC","crp","lacI"))
)
convert_to_granges(res)
```
```
## GRanges object with 3 ranges and 1 metadata column:
## seqnames ranges strand | name
## <Rle> <IRanges> <Rle> | <character>
## [1] E.coli 70387-71265 + | araC
## [2] E.coli 3486120-3486752 + | crp
## [3] E.coli 366428-367510 - | lacI
## -------
## seqinfo: 1 sequence from an unspecified genome; no seqlengths
```
---
Integrating your package results with the Bioconductor Ecosystem facilitates
the use of other packages in downstream steps (e.g. plotting).
```r
grange <- GenomicRanges::GRanges("chr",IRanges::IRanges(5000, 10000))
plot_dna_objects(
regulondb = e_coli_regulondb,
grange = grange,
elements = c("gene", "promoter")
)
```
.center[
<!-- -->
]
---
class: center
<br><br><br><br>
# Where can we find some help?
--
## browseVignettes() is a good start
browseVignettes("Biostrings")
--
# But...
---
# The Bioconductor community is an infinite source of knowledge
.pull-left[
### Support page of Bioconductor
https://support.bioconductor.org
<img src = "images/support.png" style="width:380px; position:absolute; top:370px; left:50px; " />
]
--
.pull-right[
### Slack channel
<img src = "images/slack.png" style="width:160px; position:absolute; top:190px; left:650px; " />
https://bioc-community.herokuapp.com
<img src = "images/slack2.png" style="width:380px; position:absolute; top:370px; left:450px; " />
]
---
# Share your contributions with the community!
.pull-left[
<img src = "images/bioc2019logo.png" style="width:100px; position:absolute; top:210px; left:80px; " />
<img src = "images/bioc2019text.png" style="width:220px; position:absolute; top:220px; left:190px; " />
<img src = "images/bioc2019ppt.png" style="width:320px; position:absolute; top:380px; left:80px; " />
]
.pull-right[
<img src = "images/bioc2019.png" style="width:290px; position:absolute; top:190px; left:480px; " />
]
--
.pull-right[
<img src = "images/bioc2021.png" style="width:290px; position:absolute; top:420px; left:480px; " />
<br><br><br><br><br><br><br><br><br><br><br><br>
https://bioc2021.bioconductor.org
]
---
class: inverse middle center
background-image: url("images/joss.png"), url("images/rladies-bmore.png")
background-size: 140px, 140px
background-position: 90% 90%, 5% 5%
# Thanks for your attention!
### Twitter: @josschavezf1
### josschavezf.netlify.app
---
class: inverse middle center
# These slides were made using the [xaringan](https://github.com/yihui/xaringan) package from Yihui Xie and the [rladies theme](https://alison.rbind.io/post/2017-12-18-r-ladies-presentation-ninja/) from Alison Hill.
</textarea>
<style data-target="print-only">@media screen {.remark-slide-container{display:block;}.remark-slide-scaler{box-shadow:none;}}</style>
<script src="https://remarkjs.com/downloads/remark-latest.min.js"></script>
<script>var slideshow = remark.create();
if (window.HTMLWidgets) slideshow.on('afterShowSlide', function (slide) {
window.dispatchEvent(new Event('resize'));
});
(function(d) {
var s = d.createElement("style"), r = d.querySelector(".remark-slide-scaler");
if (!r) return;
s.type = "text/css"; s.innerHTML = "@page {size: " + r.style.width + " " + r.style.height +"; }";
d.head.appendChild(s);
})(document);
(function(d) {
var el = d.getElementsByClassName("remark-slides-area");
if (!el) return;
var slide, slides = slideshow.getSlides(), els = el[0].children;
for (var i = 1; i < slides.length; i++) {
slide = slides[i];
if (slide.properties.continued === "true" || slide.properties.count === "false") {
els[i - 1].className += ' has-continuation';
}
}
var s = d.createElement("style");
s.type = "text/css"; s.innerHTML = "@media print { .has-continuation { display: none; } }";
d.head.appendChild(s);
})(document);
// delete the temporary CSS (for displaying all slides initially) when the user
// starts to view slides
(function() {
var deleted = false;
slideshow.on('beforeShowSlide', function(slide) {
if (deleted) return;
var sheets = document.styleSheets, node;
for (var i = 0; i < sheets.length; i++) {
node = sheets[i].ownerNode;
if (node.dataset["target"] !== "print-only") continue;
node.parentNode.removeChild(node);
}
deleted = true;
});
})();
(function() {
"use strict"
// Replace <script> tags in slides area to make them executable
var scripts = document.querySelectorAll(
'.remark-slides-area .remark-slide-container script'
);
if (!scripts.length) return;
for (var i = 0; i < scripts.length; i++) {
var s = document.createElement('script');
var code = document.createTextNode(scripts[i].textContent);
s.appendChild(code);
var scriptAttrs = scripts[i].attributes;
for (var j = 0; j < scriptAttrs.length; j++) {
s.setAttribute(scriptAttrs[j].name, scriptAttrs[j].value);
}
scripts[i].parentElement.replaceChild(s, scripts[i]);
}
})();
(function() {
var links = document.getElementsByTagName('a');
for (var i = 0; i < links.length; i++) {
if (/^(https?:)?\/\//.test(links[i].getAttribute('href'))) {
links[i].target = '_blank';
}
}
})();</script>
<script>
slideshow._releaseMath = function(el) {
var i, text, code, codes = el.getElementsByTagName('code');
for (i = 0; i < codes.length;) {
code = codes[i];
if (code.parentNode.tagName !== 'PRE' && code.childElementCount === 0) {
text = code.textContent;
if (/^\\\((.|\s)+\\\)$/.test(text) || /^\\\[(.|\s)+\\\]$/.test(text) ||
/^\$\$(.|\s)+\$\$$/.test(text) ||
/^\\begin\{([^}]+)\}(.|\s)+\\end\{[^}]+\}$/.test(text)) {
code.outerHTML = code.innerHTML; // remove <code></code>
continue;
}
}
i++;
}
};
slideshow._releaseMath(document);
</script>
<!-- dynamically load mathjax for compatibility with self-contained -->
<script>
(function () {
var script = document.createElement('script');
script.type = 'text/javascript';
script.src = 'https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-MML-AM_CHTML';
if (location.protocol !== 'file:' && /^https?:/.test(script.src))
script.src = script.src.replace(/^https?:/, '');
document.getElementsByTagName('head')[0].appendChild(script);
})();
</script>
</body>
</html>