-
Notifications
You must be signed in to change notification settings - Fork 13
/
how_much_memory.html
623 lines (540 loc) · 18.2 KB
/
how_much_memory.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
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<meta name="generator" content="pandoc" />
<meta http-equiv="X-UA-Compatible" content="IE=EDGE" />
<meta name="author" content="Brian J. Knaus" />
<meta name="date" content="2017-06-07" />
<title>How much memory do I need?</title>
<script src="site_libs/header-attrs-2.16/header-attrs.js"></script>
<script src="site_libs/jquery-3.6.0/jquery-3.6.0.min.js"></script>
<meta name="viewport" content="width=device-width, initial-scale=1" />
<link href="site_libs/bootstrap-3.3.5/css/sandstone.min.css" rel="stylesheet" />
<script src="site_libs/bootstrap-3.3.5/js/bootstrap.min.js"></script>
<script src="site_libs/bootstrap-3.3.5/shim/html5shiv.min.js"></script>
<script src="site_libs/bootstrap-3.3.5/shim/respond.min.js"></script>
<style>h1 {font-size: 34px;}
h1.title {font-size: 38px;}
h2 {font-size: 30px;}
h3 {font-size: 24px;}
h4 {font-size: 18px;}
h5 {font-size: 16px;}
h6 {font-size: 12px;}
code {color: inherit; background-color: rgba(0, 0, 0, 0.04);}
pre:not([class]) { background-color: white }</style>
<script src="site_libs/navigation-1.1/tabsets.js"></script>
<link href="site_libs/highlightjs-9.12.0/textmate.css" rel="stylesheet" />
<script src="site_libs/highlightjs-9.12.0/highlight.js"></script>
<!-- Global Site Tag (gtag.js) - Google Analytics -->
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-107144798-2"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments)};
gtag('js', new Date());
gtag('config', 'UA-107144798-2');
</script>
<!-- Global Site Tag (gtag.js) - Google Analytics -->
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-107144798-1"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments)};
gtag('js', new Date());
gtag('config', 'UA-107144798-1');
</script>
<style type="text/css">
code{white-space: pre-wrap;}
span.smallcaps{font-variant: small-caps;}
span.underline{text-decoration: underline;}
div.column{display: inline-block; vertical-align: top; width: 50%;}
div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
ul.task-list{list-style: none;}
</style>
<style type="text/css">code{white-space: pre;}</style>
<script type="text/javascript">
if (window.hljs) {
hljs.configure({languages: []});
hljs.initHighlightingOnLoad();
if (document.readyState && document.readyState === "complete") {
window.setTimeout(function() { hljs.initHighlighting(); }, 0);
}
}
</script>
<link rel="stylesheet" href="styles.css" type="text/css" />
<style type = "text/css">
.main-container {
max-width: 940px;
margin-left: auto;
margin-right: auto;
}
img {
max-width:100%;
}
.tabbed-pane {
padding-top: 12px;
}
.html-widget {
margin-bottom: 20px;
}
button.code-folding-btn:focus {
outline: none;
}
summary {
display: list-item;
}
details > summary > p:only-child {
display: inline;
}
pre code {
padding: 0;
}
</style>
<style type="text/css">
.dropdown-submenu {
position: relative;
}
.dropdown-submenu>.dropdown-menu {
top: 0;
left: 100%;
margin-top: -6px;
margin-left: -1px;
border-radius: 0 6px 6px 6px;
}
.dropdown-submenu:hover>.dropdown-menu {
display: block;
}
.dropdown-submenu>a:after {
display: block;
content: " ";
float: right;
width: 0;
height: 0;
border-color: transparent;
border-style: solid;
border-width: 5px 0 5px 5px;
border-left-color: #cccccc;
margin-top: 5px;
margin-right: -10px;
}
.dropdown-submenu:hover>a:after {
border-left-color: #adb5bd;
}
.dropdown-submenu.pull-left {
float: none;
}
.dropdown-submenu.pull-left>.dropdown-menu {
left: -100%;
margin-left: 10px;
border-radius: 6px 0 6px 6px;
}
</style>
<script type="text/javascript">
// manage active state of menu based on current page
$(document).ready(function () {
// active menu anchor
href = window.location.pathname
href = href.substr(href.lastIndexOf('/') + 1)
if (href === "")
href = "index.html";
var menuAnchor = $('a[href="' + href + '"]');
// mark the anchor link active (and if it's in a dropdown, also mark that active)
var dropdown = menuAnchor.closest('li.dropdown');
if (window.bootstrap) { // Bootstrap 4+
menuAnchor.addClass('active');
dropdown.find('> .dropdown-toggle').addClass('active');
} else { // Bootstrap 3
menuAnchor.parent().addClass('active');
dropdown.addClass('active');
}
// Navbar adjustments
var navHeight = $(".navbar").first().height() + 15;
var style = document.createElement('style');
var pt = "padding-top: " + navHeight + "px; ";
var mt = "margin-top: -" + navHeight + "px; ";
var css = "";
// offset scroll position for anchor links (for fixed navbar)
for (var i = 1; i <= 6; i++) {
css += ".section h" + i + "{ " + pt + mt + "}\n";
}
style.innerHTML = "body {" + pt + "padding-bottom: 40px; }\n" + css;
document.head.appendChild(style);
});
</script>
<!-- tabsets -->
<style type="text/css">
.tabset-dropdown > .nav-tabs {
display: inline-table;
max-height: 500px;
min-height: 44px;
overflow-y: auto;
border: 1px solid #ddd;
border-radius: 4px;
}
.tabset-dropdown > .nav-tabs > li.active:before {
content: "";
font-family: 'Glyphicons Halflings';
display: inline-block;
padding: 10px;
border-right: 1px solid #ddd;
}
.tabset-dropdown > .nav-tabs.nav-tabs-open > li.active:before {
content: "";
border: none;
}
.tabset-dropdown > .nav-tabs.nav-tabs-open:before {
content: "";
font-family: 'Glyphicons Halflings';
display: inline-block;
padding: 10px;
border-right: 1px solid #ddd;
}
.tabset-dropdown > .nav-tabs > li.active {
display: block;
}
.tabset-dropdown > .nav-tabs > li > a,
.tabset-dropdown > .nav-tabs > li > a:focus,
.tabset-dropdown > .nav-tabs > li > a:hover {
border: none;
display: inline-block;
border-radius: 4px;
background-color: transparent;
}
.tabset-dropdown > .nav-tabs.nav-tabs-open > li {
display: block;
float: none;
}
.tabset-dropdown > .nav-tabs > li {
display: none;
}
</style>
<!-- code folding -->
</head>
<body>
<div class="container-fluid main-container">
<div class="navbar navbar-default navbar-fixed-top" role="navigation">
<div class="container">
<div class="navbar-header">
<button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-bs-toggle="collapse" data-target="#navbar" data-bs-target="#navbar">
<span class="icon-bar"></span>
<span class="icon-bar"></span>
<span class="icon-bar"></span>
</button>
<a class="navbar-brand" href="index.html">vcfR</a>
</div>
<div id="navbar" class="navbar-collapse collapse">
<ul class="nav navbar-nav">
<li>
<a href="index.html">Home</a>
</li>
<li>
<a href="rlanguage.html">R language</a>
</li>
<li class="dropdown">
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false">
Tutorial
<span class="caret"></span>
</a>
<ul class="dropdown-menu" role="menu">
<li>
<a href="quick_intro.html">A quick introduction</a>
</li>
<li>
<a href="vcf_data.html">VCF data</a>
</li>
<li>
<a href="vcfR_object.html">vcfR objects</a>
</li>
<li>
<a href="how_much_memory.html">How much memory</a>
</li>
<li>
<a href="matrices.html">Extracting matrices</a>
</li>
<li>
<a href="tidy_vcfR.html">Tidy vcfR</a>
</li>
<li>
<a href="chromR_object.html">chromR objects</a>
</li>
<li>
<a href="visualization_1.html">Visualization 1</a>
</li>
<li>
<a href="visualization_2.html">Visualization 2</a>
</li>
<li>
<a href="sequence_coverage.html">Sequence coverage</a>
</li>
<li>
<a href="filtering_data.html">Filtering data</a>
</li>
<li>
<a href="ranking_data.html">Ranking data</a>
</li>
<li>
<a href="windowing.html">Windowing</a>
</li>
<li>
<a href="genetic_differentiation.html">Genetic differentiation</a>
</li>
</ul>
</li>
<li class="dropdown">
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false">
GBS class
<span class="caret"></span>
</a>
<ul class="dropdown-menu" role="menu">
<li>
<a href="gbs_class.html">GBS class</a>
</li>
<li>
<a href="vcf_data.html">VCF data</a>
</li>
<li>
<a href="extract_data.html">Extract data</a>
</li>
<li>
<a href="depth_plot.html">Depth plot</a>
</li>
<li>
<a href="missing_data.html">Missing data</a>
</li>
<li>
<a href="censoring_data.html">Censoring data</a>
</li>
<li>
<a href="omitting_data.html">Omitting data</a>
</li>
<li>
<a href="apply.html">Apply</a>
</li>
</ul>
</li>
<li class="dropdown">
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false">
Ploidy
<span class="caret"></span>
</a>
<ul class="dropdown-menu" role="menu">
<li>
<a href="ploidy.html">Ploidy</a>
</li>
<li>
<a href="determining_ploidy_1.html">Determining ploidy 1</a>
</li>
<li>
<a href="determining_ploidy_2.html">Determining ploidy 2</a>
</li>
</ul>
</li>
<li class="dropdown">
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false">
Export
<span class="caret"></span>
</a>
<ul class="dropdown-menu" role="menu">
<li>
<a href="export.html">Overview</a>
</li>
<li>
<a href="export_vcfgz.html">Export to *vcf.gz</a>
</li>
<li>
<a href="export_genind_genclone.html">Genind and Genclone</a>
</li>
<li>
<a href="export_genlight_snpclone.html">Genlight and SNPclone</a>
</li>
<li>
<a href="dnabin.html">DNAbin</a>
</li>
</ul>
</li>
<li class="dropdown">
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false">
FAQ
<span class="caret"></span>
</a>
<ul class="dropdown-menu" role="menu">
<li>
<a href="subset_data_to_1chrom.html">Subset to 1 chromosome</a>
</li>
<li>
<a href="missing_data.html">Missing data</a>
</li>
<li>
<a href="vcf_software.html">VCF software</a>
</li>
<li>
<a href="dip_to_hap.html">Haploidizing diploid data</a>
</li>
<li>
<a href="compiling_vcfR.html">Compiling vcfR</a>
</li>
<li>
<a href="reporting_issue.html">Reporting an issue</a>
</li>
</ul>
</li>
</ul>
<ul class="nav navbar-nav navbar-right">
</ul>
</div><!--/.nav-collapse -->
</div><!--/.container -->
</div><!--/.navbar -->
<p>
<center>
<h3>vcfR documentation</h3>
by
<br>
Brian J. Knaus and Niklaus J. Grünwald
</center>
</p>
<div id="header">
<h1 class="title toc-ignore">How much memory do I need?</h1>
<h4 class="author">Brian J. Knaus</h4>
<h4 class="date">June 7, 2017</h4>
</div>
<p>The R package vcfR attempts to read all data into memory (RAM) in
order to perform manipulations or analyses. This is similar to other R
packages. The catch with vcfR is that VCF files frequently contain large
quantities of data. This may create a situation where you have more data
than you can read into memory. Here I explore the memory footprint of a
vcfR object to help you decide whether you have enough memory to read in
your entire file, or whether you need to develop strategies for working
on subsets of this data.</p>
<div id="the-vcfr-object" class="section level2">
<h2>The vcfR object</h2>
<p>The vcfR object is an S4 class object consisting of three slots. The
<code>meta</code> slot is a character vector. It is recommended, but not
required, that the meta data include information for each chromosome in
the reference. In mature projects, with a small number of chromosomes,
the size of this data may be fairly small. In less mature projects,
where the reference may consist of thousands of contigs, this region may
become noticable in size. However, it is likely to be small relative to
the rest of the VCF data. The <code>fix</code> slot is a character
matrix that always consists of eight columns but has as many rows as
there are variants in the VCF file, plus one more row for the header.
The <code>gt</code> slot is a character matrix that contains a column
for each sample, plus one column to designate the format for each
variant, and it has as one row for each variant. As the number of
variants in your data grow the sizes of the <code>fix</code> and
<code>gt</code> slots grow to accomodate these variants. As the number
of samples in your dataset grow the number of columns in your
<code>gt</code> slot grows. Here we’ll explore how many variants may
require how much memory.</p>
</div>
<div id="simulation-of-data" class="section level2">
<h2>Simulation of data</h2>
<p>In order to estimate the memory footprint of vcfR objects containing
different numbers of variants we’ll use the R package
<code>memuse</code>. For simplicity, we’ll ignore the <code>meta</code>
slot and instead of using both a <code>fix</code> and a <code>gt</code>
slot we’ll use a single matrix of 10 columns. This approximates VCF data
containing one sample. As your sample size increases, so will your
memory footprint. Depending on your comfort level with R, you may be
able to modify the below code to match your data set.</p>
<pre class="r"><code>library('memuse')
nvar <- 10^{2:8}
nMb <- howbig(nrow=10, ncol=10, unit="MB")@size
for(i in nvar){
nMb <- c(nMb, howbig(nrow=i, ncol=10, unit="MB")@size)
}
nvar <- c(10, nvar)</code></pre>
</div>
<div id="visualization" class="section level2">
<h2>Visualization</h2>
<p>Once we’ve simulated our data, we can visualize it. Here we’ll use a
simple line graph.</p>
<pre class="r"><code>par(mar=c(5,5,4,2))
plot(log10(nvar), log10(nMb), xaxt="n", yaxt="n", type='b', xlab="Number of variants", ylab = "")
axis(side = 1, at = log10(nvar), labels=nvar)
axis(side = 2, at = log10(nMb), labels=nMb, las=2)
title(ylab="Memory use (Mb)", line=4)
abline(h=log10(nMb), lwd=2, col="#C0C0C066")
abline(v=log10(nvar), lwd=2, col="#C0C0C066")</code></pre>
<p><img src="how_much_memory_files/figure-html/unnamed-chunk-2-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>par(mar=c(5,4,4,2))</code></pre>
<p>This should give us an idea of how much data we can read into a vcfR
object. When we have 100,000 variants we’ll need about 640 Mb of memory.
If we have 1 million variants we’ll need about 6.4 Gb of memory. This is
asking a lot of your typical work station. In the past I’ve found that
creating objects in R that are over about 1 GB starts to affect the
performance of the system. This may change in the future as R is
constantly improving.</p>
</div>
<div id="dont-know-how-many-variants-are-in-your-file"
class="section level2">
<h2>Don’t know how many variants are in your file?</h2>
<p>If you don’t know how many variants are in your VCF file you may be a
t aloss for guessing how much memory you need. If you’re working on a
flavor of Unix (OSX, Linux, etc.) you can use the shell to get an
idea.</p>
<pre class="bash"><code>grep -v "^#" myVcfFile.vcf | head -n 1000000 | wc -l</code></pre>
<p>Or for gzipped files.</p>
<pre class="bash"><code>zgrep -v "^#" myVcfFile.vcf.gz | head -n 1000000 | wc -l</code></pre>
<p>The <code>zgrep -v "^#" myVcfFile.vcf.gz</code> command sends the
contents of your VCF file to standard output, while omitting the meta
and header information which have lines begining with a pound or hash
sign. By piping this to head you limit the number of lines you count. If
you have a really large number of variants you may not want to count
them all. By piping this to <code>wc -l</code> it should count the lines
for you where each variant is one line. This should help you get an idea
of how many variants are in your file.</p>
</div>
<div id="summary" class="section level2">
<h2>Summary</h2>
<p>Our lab works on plant pathogens that have genomes in the range of
tens to hundreds of millions of base pairs in size. We typically work on
complete GBS datasets consisting of over 100 samples. These datasets
appear to read into memory and work quite well. For genomic projects we
typically have more variants than we can comfortably read into memory.
For these projects we typically work on a per supercontig manner as a
way of decomposing a genomic project into more manageable subsets. The
function <code>read.vcfR()</code> includes parameters <code>nrows</code>
and <code>skip</code> to allow you to read portions of VCF files into
memory. Note that this will require serial access so that selecting
regions of a file that are near the end of the file may require some
time to access. I find that breaking a VCF file into several files, one
for each supercontig, helps me sort through a genome more efficiently.
Hopefully this information will help you as well.</p>
</div>
<center>
<hr class="style1">
<p>Copyright © 2017, 2018 Brian J. Knaus. All rights reserved.</p>
<p>USDA Agricultural Research Service, Horticultural Crops Research Lab.</p>
</center>
</div>
<script>
// add bootstrap table styles to pandoc tables
function bootstrapStylePandocTables() {
$('tr.odd').parent('tbody').parent('table').addClass('table table-condensed');
}
$(document).ready(function () {
bootstrapStylePandocTables();
});
</script>
<!-- tabsets -->
<script>
$(document).ready(function () {
window.buildTabsets("TOC");
});
$(document).ready(function () {
$('.tabset-dropdown > .nav-tabs > li').click(function () {
$(this).parent().toggleClass('nav-tabs-open');
});
});
</script>
<!-- code folding -->
<!-- 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-AMS-MML_HTMLorMML";
document.getElementsByTagName("head")[0].appendChild(script);
})();
</script>
</body>
</html>