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MethBase2

Thousands of high-quality uniformly analyzed methylomes.

The UCSC Genome Browser provides visualization for methylomes in MethBase2.

A track hub organized by SRA Study can be turned on for human hg38 with this link.

This track hub URL can be used to load MethBase2 by SRA Study in any UCSC Genome Browser mirror:

http://smithlab.usc.edu/trackdata/methylation/hub.txt

You can also find it among the public hubs in the list at the UCSC Genome Browser.

Data in MethBase2

MethBase2 includes methylomes for the following genomes. 16,223 high-quality methylomes (2026-09-01).

speciesassemblycount
Mousemm396670
Humanhg386537
CowbosTau9588
PigsusScr11473
ZebrafishdanRer11339
ChickengalGal6283
RhesusrheMac10270
A. melliferaapiMel2210
Ratrn7201
SheepoviAri4175
DogcanFam6145
SticklebackgasAcu160
ChimppanTro659
OpossummonDom544
Crab-eating macaquemacFas534
Sea hareaplCal124
MedakaoryLat222
Zebra finchtaeGut220
X. tropicalisxenTro1015
Fugufr315
CatfelCat99
GorillagorGor66
S. purpuratusstrPur24
RabbitoryCun24
TetraodontetNig23
PandaailMel13
OrangutanponAbe33
HorseequCab33
PlatypusornAna21
GibbonnomLeu31
Elephant sharkcalMil11
DolphinturTru21

If you would like to suggest a publicly available methylome for inclusion, please submit an issue here.

The database includes many more methylomes than are available for viewing with the methbase track hub. Those selected for the track hub meet criteria that help ensure they have been analyzed correctly.

Currently the criteria are:

  • 0.9: Minimum bisulfite conversion rate.
  • 0.7: Minimum fraction of CpG sites covered.

Assuming a Poisson distribution for the mapped reads (the most conservative assumption here), a fraction of 0.632 of CpG sites covered implies at least a 1x average coverage across the genome. Distributions of mapped reads are never Poisson, so requiring 0.7 of the sites to be covered at least once tends to ensure much deeper average coverage of sites.

Methylome features

Moving forward, not all methylomes will have each kind of "feature" available through the track hub. The criteria are below (in progress). If you want something and you can't find it, possibly those features did not meet criteria. Please contact me to ask and I can check if they might have barely failed to meet the criteria and I might be able to adjust or provide them to you directly.

Hypomethylated regions (HMRs)

HMRs are valleys of low methylation in the background of high global methylation in healthy primary vertebrate methylomes. These are identified with the hmr command in dnmtools, which is very similar to the tool I wrote for the Molaro (2011) paper. For MethBase2, the analysis workflow attempts to identify HMRs in every high-quality methylome from a vertebrate species. These features don't make sense in all situations. In the most extreme example, cells with DNA methylation erased should not be understood in terms of "valleys" of low methylation. Currently the following criteria are used to ensure available sets of HMRs make sense:

  • Human: between 25K and 110K HMRs, with mean size between 750 bp and 4K bp.
  • Mouse: between 20K and 100K HMRs, with mean size between 750 bp and 3K bp.

Criteria for other species will be updated here.

About

Thousands of high-quality analyzed methylomes.

Resources

Readme
MIT license

Code of conduct

Code of conduct
Activity
Custom properties

Stars

1 star

Watchers

8 watching

Forks

0 forks
Report repository

Releases

Packages

Used by

Contributors

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Repository files navigation
MethBase2
Thousands of high-quality uniformly analyzed methylomes.
The UCSC Genome Browser provides visualization for methylomes in MethBase2.
A track hub organized by SRA Study can be turned on for human hg38 with this
link.
This track hub URL can be used to load MethBase2 by SRA Study in any UCSC Genome
Browser mirror:
http://smithlab.usc.edu/trackdata/methylation/hub.txt

You can also find it among the public hubs in the list at the UCSC Genome
Browser.
Data in MethBase2
MethBase2 includes methylomes for the following genomes. 16,223 high-quality
methylomes (2026-09-01).
speciesassemblycount
Mousemm396670
Humanhg386537
CowbosTau9588
PigsusScr11473
ZebrafishdanRer11339
ChickengalGal6283
RhesusrheMac10270
A. melliferaapiMel2210
Ratrn7201
SheepoviAri4175
DogcanFam6145
SticklebackgasAcu160
ChimppanTro659
OpossummonDom544
Crab-eating macaquemacFas534
Sea hareaplCal124
MedakaoryLat222
Zebra finchtaeGut220
X. tropicalisxenTro1015
Fugufr315
CatfelCat99
GorillagorGor66
S. purpuratusstrPur24
RabbitoryCun24
TetraodontetNig23
PandaailMel13
OrangutanponAbe33
HorseequCab33
PlatypusornAna21
GibbonnomLeu31
Elephant sharkcalMil11
DolphinturTru21
If you would like to suggest a publicly available methylome for inclusion,
please submit an issue here.
The database includes many more methylomes than are available for viewing with
the methbase track hub. Those selected for the track hub meet criteria that help
ensure they have been analyzed correctly.
Currently the criteria are:
  • 0.9: Minimum bisulfite conversion rate.
  • 0.7: Minimum fraction of CpG sites covered.
Assuming a Poisson distribution for the mapped reads (the most conservative
assumption here), a fraction of 0.632 of CpG sites covered implies at least a 1x
average coverage across the genome. Distributions of mapped reads are never
Poisson, so requiring 0.7 of the sites to be covered at least once tends to
ensure much deeper average coverage of sites.
Methylome features
Moving forward, not all methylomes will have each kind of "feature" available
through the track hub. The criteria are below (in progress). If you want
something and you can't find it, possibly those features did not meet
criteria. Please contact me to ask and I can check if they might have barely
failed to meet the criteria and I might be able to adjust or provide them to you
directly.
Hypomethylated regions (HMRs)
HMRs are valleys of low methylation in the background of high global methylation
in healthy primary vertebrate methylomes. These are identified with the hmr
command in dnmtools, which is very similar to the tool I wrote for the Molaro
(2011) paper. For MethBase2, the analysis workflow attempts to identify HMRs in
every high-quality methylome from a vertebrate species. These features don't
make sense in all situations. In the most extreme example, cells with DNA
methylation erased should not be understood in terms of "valleys" of low
methylation. Currently the following criteria are used to ensure available sets
of HMRs make sense:
  • Human: between 25K and 110K HMRs, with mean size between 750 bp and 4K bp.
  • Mouse: between 20K and 100K HMRs, with mean size between 750 bp and 3K bp.
Criteria for other species will be updated here.
About
Thousands of high-quality analyzed methylomes.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Activity
Custom properties
Stars
1 star
Watchers
8 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
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var __re = new RegExp('^' + ".*" + '

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CODE_OF_CONDUCT.md
CODE_OF_CONDUCT.md
LICENSE
LICENSE
README.md
README.md
Repository files navigation
MethBase2
Thousands of high-quality uniformly analyzed methylomes.
The UCSC Genome Browser provides visualization for methylomes in MethBase2.
A track hub organized by SRA Study can be turned on for human hg38 with this
link.
This track hub URL can be used to load MethBase2 by SRA Study in any UCSC Genome
Browser mirror:
http://smithlab.usc.edu/trackdata/methylation/hub.txt

You can also find it among the public hubs in the list at the UCSC Genome
Browser.
Data in MethBase2
MethBase2 includes methylomes for the following genomes. 16,223 high-quality
methylomes (2026-09-01).
speciesassemblycount
Mousemm396670
Humanhg386537
CowbosTau9588
PigsusScr11473
ZebrafishdanRer11339
ChickengalGal6283
RhesusrheMac10270
A. melliferaapiMel2210
Ratrn7201
SheepoviAri4175
DogcanFam6145
SticklebackgasAcu160
ChimppanTro659
OpossummonDom544
Crab-eating macaquemacFas534
Sea hareaplCal124
MedakaoryLat222
Zebra finchtaeGut220
X. tropicalisxenTro1015
Fugufr315
CatfelCat99
GorillagorGor66
S. purpuratusstrPur24
RabbitoryCun24
TetraodontetNig23
PandaailMel13
OrangutanponAbe33
HorseequCab33
PlatypusornAna21
GibbonnomLeu31
Elephant sharkcalMil11
DolphinturTru21
If you would like to suggest a publicly available methylome for inclusion,
please submit an issue here.
The database includes many more methylomes than are available for viewing with
the methbase track hub. Those selected for the track hub meet criteria that help
ensure they have been analyzed correctly.
Currently the criteria are:
  • 0.9: Minimum bisulfite conversion rate.
  • 0.7: Minimum fraction of CpG sites covered.
Assuming a Poisson distribution for the mapped reads (the most conservative
assumption here), a fraction of 0.632 of CpG sites covered implies at least a 1x
average coverage across the genome. Distributions of mapped reads are never
Poisson, so requiring 0.7 of the sites to be covered at least once tends to
ensure much deeper average coverage of sites.
Methylome features
Moving forward, not all methylomes will have each kind of "feature" available
through the track hub. The criteria are below (in progress). If you want
something and you can't find it, possibly those features did not meet
criteria. Please contact me to ask and I can check if they might have barely
failed to meet the criteria and I might be able to adjust or provide them to you
directly.
Hypomethylated regions (HMRs)
HMRs are valleys of low methylation in the background of high global methylation
in healthy primary vertebrate methylomes. These are identified with the hmr
command in dnmtools, which is very similar to the tool I wrote for the Molaro
(2011) paper. For MethBase2, the analysis workflow attempts to identify HMRs in
every high-quality methylome from a vertebrate species. These features don't
make sense in all situations. In the most extreme example, cells with DNA
methylation erased should not be understood in terms of "valleys" of low
methylation. Currently the following criteria are used to ensure available sets
of HMRs make sense:
  • Human: between 25K and 110K HMRs, with mean size between 750 bp and 4K bp.
  • Mouse: between 20K and 100K HMRs, with mean size between 750 bp and 3K bp.
Criteria for other species will be updated here.
About
Thousands of high-quality analyzed methylomes.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Activity
Custom properties
Stars
1 star
Watchers
8 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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CODE_OF_CONDUCT.md
CODE_OF_CONDUCT.md
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README.md
README.md
Repository files navigation
MethBase2
Thousands of high-quality uniformly analyzed methylomes.
The UCSC Genome Browser provides visualization for methylomes in MethBase2.
A track hub organized by SRA Study can be turned on for human hg38 with this
link.
This track hub URL can be used to load MethBase2 by SRA Study in any UCSC Genome
Browser mirror:
http://smithlab.usc.edu/trackdata/methylation/hub.txt

You can also find it among the public hubs in the list at the UCSC Genome
Browser.
Data in MethBase2
MethBase2 includes methylomes for the following genomes. 16,223 high-quality
methylomes (2026-09-01).
speciesassemblycount
Mousemm396670
Humanhg386537
CowbosTau9588
PigsusScr11473
ZebrafishdanRer11339
ChickengalGal6283
RhesusrheMac10270
A. melliferaapiMel2210
Ratrn7201
SheepoviAri4175
DogcanFam6145
SticklebackgasAcu160
ChimppanTro659
OpossummonDom544
Crab-eating macaquemacFas534
Sea hareaplCal124
MedakaoryLat222
Zebra finchtaeGut220
X. tropicalisxenTro1015
Fugufr315
CatfelCat99
GorillagorGor66
S. purpuratusstrPur24
RabbitoryCun24
TetraodontetNig23
PandaailMel13
OrangutanponAbe33
HorseequCab33
PlatypusornAna21
GibbonnomLeu31
Elephant sharkcalMil11
DolphinturTru21
If you would like to suggest a publicly available methylome for inclusion,
please submit an issue here.
The database includes many more methylomes than are available for viewing with
the methbase track hub. Those selected for the track hub meet criteria that help
ensure they have been analyzed correctly.
Currently the criteria are:
  • 0.9: Minimum bisulfite conversion rate.
  • 0.7: Minimum fraction of CpG sites covered.
Assuming a Poisson distribution for the mapped reads (the most conservative
assumption here), a fraction of 0.632 of CpG sites covered implies at least a 1x
average coverage across the genome. Distributions of mapped reads are never
Poisson, so requiring 0.7 of the sites to be covered at least once tends to
ensure much deeper average coverage of sites.
Methylome features
Moving forward, not all methylomes will have each kind of "feature" available
through the track hub. The criteria are below (in progress). If you want
something and you can't find it, possibly those features did not meet
criteria. Please contact me to ask and I can check if they might have barely
failed to meet the criteria and I might be able to adjust or provide them to you
directly.
Hypomethylated regions (HMRs)
HMRs are valleys of low methylation in the background of high global methylation
in healthy primary vertebrate methylomes. These are identified with the hmr
command in dnmtools, which is very similar to the tool I wrote for the Molaro
(2011) paper. For MethBase2, the analysis workflow attempts to identify HMRs in
every high-quality methylome from a vertebrate species. These features don't
make sense in all situations. In the most extreme example, cells with DNA
methylation erased should not be understood in terms of "valleys" of low
methylation. Currently the following criteria are used to ensure available sets
of HMRs make sense:
  • Human: between 25K and 110K HMRs, with mean size between 750 bp and 4K bp.
  • Mouse: between 20K and 100K HMRs, with mean size between 750 bp and 3K bp.
Criteria for other species will be updated here.
About
Thousands of high-quality analyzed methylomes.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Activity
Custom properties
Stars
1 star
Watchers
8 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
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})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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86 Commits
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NameName
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CODE_OF_CONDUCT.md
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README.md
README.md
Repository files navigation
MethBase2
Thousands of high-quality uniformly analyzed methylomes.
The UCSC Genome Browser provides visualization for methylomes in MethBase2.
A track hub organized by SRA Study can be turned on for human hg38 with this
link.
This track hub URL can be used to load MethBase2 by SRA Study in any UCSC Genome
Browser mirror:
http://smithlab.usc.edu/trackdata/methylation/hub.txt

You can also find it among the public hubs in the list at the UCSC Genome
Browser.
Data in MethBase2
MethBase2 includes methylomes for the following genomes. 16,223 high-quality
methylomes (2026-09-01).
speciesassemblycount
Mousemm396670
Humanhg386537
CowbosTau9588
PigsusScr11473
ZebrafishdanRer11339
ChickengalGal6283
RhesusrheMac10270
A. melliferaapiMel2210
Ratrn7201
SheepoviAri4175
DogcanFam6145
SticklebackgasAcu160
ChimppanTro659
OpossummonDom544
Crab-eating macaquemacFas534
Sea hareaplCal124
MedakaoryLat222
Zebra finchtaeGut220
X. tropicalisxenTro1015
Fugufr315
CatfelCat99
GorillagorGor66
S. purpuratusstrPur24
RabbitoryCun24
TetraodontetNig23
PandaailMel13
OrangutanponAbe33
HorseequCab33
PlatypusornAna21
GibbonnomLeu31
Elephant sharkcalMil11
DolphinturTru21
If you would like to suggest a publicly available methylome for inclusion,
please submit an issue here.
The database includes many more methylomes than are available for viewing with
the methbase track hub. Those selected for the track hub meet criteria that help
ensure they have been analyzed correctly.
Currently the criteria are:
  • 0.9: Minimum bisulfite conversion rate.
  • 0.7: Minimum fraction of CpG sites covered.
Assuming a Poisson distribution for the mapped reads (the most conservative
assumption here), a fraction of 0.632 of CpG sites covered implies at least a 1x
average coverage across the genome. Distributions of mapped reads are never
Poisson, so requiring 0.7 of the sites to be covered at least once tends to
ensure much deeper average coverage of sites.
Methylome features
Moving forward, not all methylomes will have each kind of "feature" available
through the track hub. The criteria are below (in progress). If you want
something and you can't find it, possibly those features did not meet
criteria. Please contact me to ask and I can check if they might have barely
failed to meet the criteria and I might be able to adjust or provide them to you
directly.
Hypomethylated regions (HMRs)
HMRs are valleys of low methylation in the background of high global methylation
in healthy primary vertebrate methylomes. These are identified with the hmr
command in dnmtools, which is very similar to the tool I wrote for the Molaro
(2011) paper. For MethBase2, the analysis workflow attempts to identify HMRs in
every high-quality methylome from a vertebrate species. These features don't
make sense in all situations. In the most extreme example, cells with DNA
methylation erased should not be understood in terms of "valleys" of low
methylation. Currently the following criteria are used to ensure available sets
of HMRs make sense:
  • Human: between 25K and 110K HMRs, with mean size between 750 bp and 4K bp.
  • Mouse: between 20K and 100K HMRs, with mean size between 750 bp and 3K bp.
Criteria for other species will be updated here.
About
Thousands of high-quality analyzed methylomes.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Activity
Custom properties
Stars
1 star
Watchers
8 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
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})();
(function(){
try {
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MethBase2
Thousands of high-quality uniformly analyzed methylomes.
The UCSC Genome Browser provides visualization for methylomes in MethBase2.
A track hub organized by SRA Study can be turned on for human hg38 with this
link.
This track hub URL can be used to load MethBase2 by SRA Study in any UCSC Genome
Browser mirror:
http://smithlab.usc.edu/trackdata/methylation/hub.txt

You can also find it among the public hubs in the list at the UCSC Genome
Browser.
Data in MethBase2
MethBase2 includes methylomes for the following genomes. 16,223 high-quality
methylomes (2026-09-01).
speciesassemblycount
Mousemm396670
Humanhg386537
CowbosTau9588
PigsusScr11473
ZebrafishdanRer11339
ChickengalGal6283
RhesusrheMac10270
A. melliferaapiMel2210
Ratrn7201
SheepoviAri4175
DogcanFam6145
SticklebackgasAcu160
ChimppanTro659
OpossummonDom544
Crab-eating macaquemacFas534
Sea hareaplCal124
MedakaoryLat222
Zebra finchtaeGut220
X. tropicalisxenTro1015
Fugufr315
CatfelCat99
GorillagorGor66
S. purpuratusstrPur24
RabbitoryCun24
TetraodontetNig23
PandaailMel13
OrangutanponAbe33
HorseequCab33
PlatypusornAna21
GibbonnomLeu31
Elephant sharkcalMil11
DolphinturTru21
If you would like to suggest a publicly available methylome for inclusion,
please submit an issue here.
The database includes many more methylomes than are available for viewing with
the methbase track hub. Those selected for the track hub meet criteria that help
ensure they have been analyzed correctly.
Currently the criteria are:
  • 0.9: Minimum bisulfite conversion rate.
  • 0.7: Minimum fraction of CpG sites covered.
Assuming a Poisson distribution for the mapped reads (the most conservative
assumption here), a fraction of 0.632 of CpG sites covered implies at least a 1x
average coverage across the genome. Distributions of mapped reads are never
Poisson, so requiring 0.7 of the sites to be covered at least once tends to
ensure much deeper average coverage of sites.
Methylome features
Moving forward, not all methylomes will have each kind of "feature" available
through the track hub. The criteria are below (in progress). If you want
something and you can't find it, possibly those features did not meet
criteria. Please contact me to ask and I can check if they might have barely
failed to meet the criteria and I might be able to adjust or provide them to you
directly.
Hypomethylated regions (HMRs)
HMRs are valleys of low methylation in the background of high global methylation
in healthy primary vertebrate methylomes. These are identified with the hmr
command in dnmtools, which is very similar to the tool I wrote for the Molaro
(2011) paper. For MethBase2, the analysis workflow attempts to identify HMRs in
every high-quality methylome from a vertebrate species. These features don't
make sense in all situations. In the most extreme example, cells with DNA
methylation erased should not be understood in terms of "valleys" of low
methylation. Currently the following criteria are used to ensure available sets
of HMRs make sense:
  • Human: between 25K and 110K HMRs, with mean size between 750 bp and 4K bp.
  • Mouse: between 20K and 100K HMRs, with mean size between 750 bp and 3K bp.
Criteria for other species will be updated here.
About
Thousands of high-quality analyzed methylomes.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Activity
Custom properties
Stars
1 star
Watchers
8 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors

, 'i');
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injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
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CODE_OF_CONDUCT.md
CODE_OF_CONDUCT.md
LICENSE
LICENSE
README.md
README.md
Repository files navigation
MethBase2
Thousands of high-quality uniformly analyzed methylomes.
The UCSC Genome Browser provides visualization for methylomes in MethBase2.
A track hub organized by SRA Study can be turned on for human hg38 with this
link.
This track hub URL can be used to load MethBase2 by SRA Study in any UCSC Genome
Browser mirror:
http://smithlab.usc.edu/trackdata/methylation/hub.txt

You can also find it among the public hubs in the list at the UCSC Genome
Browser.
Data in MethBase2
MethBase2 includes methylomes for the following genomes. 16,223 high-quality
methylomes (2026-09-01).
speciesassemblycount
Mousemm396670
Humanhg386537
CowbosTau9588
PigsusScr11473
ZebrafishdanRer11339
ChickengalGal6283
RhesusrheMac10270
A. melliferaapiMel2210
Ratrn7201
SheepoviAri4175
DogcanFam6145
SticklebackgasAcu160
ChimppanTro659
OpossummonDom544
Crab-eating macaquemacFas534
Sea hareaplCal124
MedakaoryLat222
Zebra finchtaeGut220
X. tropicalisxenTro1015
Fugufr315
CatfelCat99
GorillagorGor66
S. purpuratusstrPur24
RabbitoryCun24
TetraodontetNig23
PandaailMel13
OrangutanponAbe33
HorseequCab33
PlatypusornAna21
GibbonnomLeu31
Elephant sharkcalMil11
DolphinturTru21
If you would like to suggest a publicly available methylome for inclusion,
please submit an issue here.
The database includes many more methylomes than are available for viewing with
the methbase track hub. Those selected for the track hub meet criteria that help
ensure they have been analyzed correctly.
Currently the criteria are:
  • 0.9: Minimum bisulfite conversion rate.
  • 0.7: Minimum fraction of CpG sites covered.
Assuming a Poisson distribution for the mapped reads (the most conservative
assumption here), a fraction of 0.632 of CpG sites covered implies at least a 1x
average coverage across the genome. Distributions of mapped reads are never
Poisson, so requiring 0.7 of the sites to be covered at least once tends to
ensure much deeper average coverage of sites.
Methylome features
Moving forward, not all methylomes will have each kind of "feature" available
through the track hub. The criteria are below (in progress). If you want
something and you can't find it, possibly those features did not meet
criteria. Please contact me to ask and I can check if they might have barely
failed to meet the criteria and I might be able to adjust or provide them to you
directly.
Hypomethylated regions (HMRs)
HMRs are valleys of low methylation in the background of high global methylation
in healthy primary vertebrate methylomes. These are identified with the hmr
command in dnmtools, which is very similar to the tool I wrote for the Molaro
(2011) paper. For MethBase2, the analysis workflow attempts to identify HMRs in
every high-quality methylome from a vertebrate species. These features don't
make sense in all situations. In the most extreme example, cells with DNA
methylation erased should not be understood in terms of "valleys" of low
methylation. Currently the following criteria are used to ensure available sets
of HMRs make sense:
  • Human: between 25K and 110K HMRs, with mean size between 750 bp and 4K bp.
  • Mouse: between 20K and 100K HMRs, with mean size between 750 bp and 3K bp.
Criteria for other species will be updated here.
About
Thousands of high-quality analyzed methylomes.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Activity
Custom properties
Stars
1 star
Watchers
8 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
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README.md
README.md
Repository files navigation
MethBase2
Thousands of high-quality uniformly analyzed methylomes.
The UCSC Genome Browser provides visualization for methylomes in MethBase2.
A track hub organized by SRA Study can be turned on for human hg38 with this
link.
This track hub URL can be used to load MethBase2 by SRA Study in any UCSC Genome
Browser mirror:
http://smithlab.usc.edu/trackdata/methylation/hub.txt

You can also find it among the public hubs in the list at the UCSC Genome
Browser.
Data in MethBase2
MethBase2 includes methylomes for the following genomes. 16,223 high-quality
methylomes (2026-09-01).
speciesassemblycount
Mousemm396670
Humanhg386537
CowbosTau9588
PigsusScr11473
ZebrafishdanRer11339
ChickengalGal6283
RhesusrheMac10270
A. melliferaapiMel2210
Ratrn7201
SheepoviAri4175
DogcanFam6145
SticklebackgasAcu160
ChimppanTro659
OpossummonDom544
Crab-eating macaquemacFas534
Sea hareaplCal124
MedakaoryLat222
Zebra finchtaeGut220
X. tropicalisxenTro1015
Fugufr315
CatfelCat99
GorillagorGor66
S. purpuratusstrPur24
RabbitoryCun24
TetraodontetNig23
PandaailMel13
OrangutanponAbe33
HorseequCab33
PlatypusornAna21
GibbonnomLeu31
Elephant sharkcalMil11
DolphinturTru21
If you would like to suggest a publicly available methylome for inclusion,
please submit an issue here.
The database includes many more methylomes than are available for viewing with
the methbase track hub. Those selected for the track hub meet criteria that help
ensure they have been analyzed correctly.
Currently the criteria are:
  • 0.9: Minimum bisulfite conversion rate.
  • 0.7: Minimum fraction of CpG sites covered.
Assuming a Poisson distribution for the mapped reads (the most conservative
assumption here), a fraction of 0.632 of CpG sites covered implies at least a 1x
average coverage across the genome. Distributions of mapped reads are never
Poisson, so requiring 0.7 of the sites to be covered at least once tends to
ensure much deeper average coverage of sites.
Methylome features
Moving forward, not all methylomes will have each kind of "feature" available
through the track hub. The criteria are below (in progress). If you want
something and you can't find it, possibly those features did not meet
criteria. Please contact me to ask and I can check if they might have barely
failed to meet the criteria and I might be able to adjust or provide them to you
directly.
Hypomethylated regions (HMRs)
HMRs are valleys of low methylation in the background of high global methylation
in healthy primary vertebrate methylomes. These are identified with the hmr
command in dnmtools, which is very similar to the tool I wrote for the Molaro
(2011) paper. For MethBase2, the analysis workflow attempts to identify HMRs in
every high-quality methylome from a vertebrate species. These features don't
make sense in all situations. In the most extreme example, cells with DNA
methylation erased should not be understood in terms of "valleys" of low
methylation. Currently the following criteria are used to ensure available sets
of HMRs make sense:
  • Human: between 25K and 110K HMRs, with mean size between 750 bp and 4K bp.
  • Mouse: between 20K and 100K HMRs, with mean size between 750 bp and 3K bp.
Criteria for other species will be updated here.
About
Thousands of high-quality analyzed methylomes.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Activity
Custom properties
Stars
1 star
Watchers
8 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors