How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes? View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-12-27

AUTHORS

Brian J Haas, Melissa Chin, Chad Nusbaum, Bruce W Birren, Jonathan Livny

ABSTRACT

BackgroundHigh-throughput sequencing of cDNA libraries (RNA-Seq) has proven to be a highly effective approach for studying bacterial transcriptomes. A central challenge in designing RNA-Seq-based experiments is estimating a priori the number of reads per sample needed to detect and quantify thousands of individual transcripts with a large dynamic range of abundance.ResultsWe have conducted a systematic examination of how changes in the number of RNA-Seq reads per sample influences both profiling of a single bacterial transcriptome and the comparison of gene expression among samples. Our findings suggest that the number of reads typically produced in a single lane of the Illumina HiSeq sequencer far exceeds the number needed to saturate the annotated transcriptomes of diverse bacteria growing in monoculture. Moreover, as sequencing depth increases, so too does the detection of cDNAs that likely correspond to spurious transcripts or genomic DNA contamination. Finally, even when dozens of barcoded individual cDNA libraries are sequenced in a single lane, the vast majority of transcripts in each sample can be detected and numerous genes differentially expressed between samples can be identified.ConclusionsOur analysis provides a guide for the many researchers seeking to determine the appropriate sequencing depth for RNA-Seq-based studies of diverse bacterial species. More... »

PAGES

734

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2164-13-734

DOI

http://dx.doi.org/10.1186/1471-2164-13-734

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1018646208

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23270466


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Genetics", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Escherichia coli", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Gene Expression Profiling", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Gene Library", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "High-Throughput Nucleotide Sequencing", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Molecular Sequence Annotation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Open Reading Frames", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA", 
          "id": "http://www.grid.ac/institutes/grid.66859.34", 
          "name": [
            "Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Haas", 
        "givenName": "Brian J", 
        "id": "sg:person.01163021216.55", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01163021216.55"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA", 
          "id": "http://www.grid.ac/institutes/grid.66859.34", 
          "name": [
            "Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chin", 
        "givenName": "Melissa", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA", 
          "id": "http://www.grid.ac/institutes/grid.66859.34", 
          "name": [
            "Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nusbaum", 
        "givenName": "Chad", 
        "id": "sg:person.01170225154.35", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01170225154.35"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA", 
          "id": "http://www.grid.ac/institutes/grid.66859.34", 
          "name": [
            "Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Birren", 
        "givenName": "Bruce W", 
        "id": "sg:person.01205530423.53", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01205530423.53"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Channing Laboratory, Brigham and Women\u2019s Hospital, Harvard Medical School, 02115, Boston, MA, USA", 
          "id": "http://www.grid.ac/institutes/grid.38142.3c", 
          "name": [
            "Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA", 
            "Channing Laboratory, Brigham and Women\u2019s Hospital, Harvard Medical School, 02115, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Livny", 
        "givenName": "Jonathan", 
        "id": "sg:person.01213752162.55", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213752162.55"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1186/gb-2011-12-1-r1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045286538", 
          "https://doi.org/10.1186/gb-2011-12-1-r1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.1491", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019899367", 
          "https://doi.org/10.1038/nmeth.1491"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature08756", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050182699", 
          "https://doi.org/10.1038/nature08756"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg2695", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019859466", 
          "https://doi.org/10.1038/nrg2695"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg2484", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030687647", 
          "https://doi.org/10.1038/nrg2484"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.1507", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005850821", 
          "https://doi.org/10.1038/nmeth.1507"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt.1582", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026972767", 
          "https://doi.org/10.1038/nbt.1582"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2010-11-10-r106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031289083", 
          "https://doi.org/10.1186/gb-2010-11-10-r106"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2010-11-2-r15", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013435656", 
          "https://doi.org/10.1186/gb-2010-11-2-r15"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2012-13-3-r23", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036305770", 
          "https://doi.org/10.1186/gb-2012-13-3-r23"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2012-12-27", 
    "datePublishedReg": "2012-12-27", 
    "description": "BackgroundHigh-throughput sequencing of cDNA libraries (RNA-Seq) has proven to be a highly effective approach for studying bacterial transcriptomes. A central challenge in designing RNA-Seq-based experiments is estimating a priori the number of reads per sample needed to detect and quantify thousands of individual transcripts with a large dynamic range of abundance.ResultsWe have conducted a systematic examination of how changes in the number of RNA-Seq reads per sample influences both profiling of a single bacterial transcriptome and the comparison of gene expression among samples. Our findings suggest that the number of reads typically produced in a single lane of the Illumina HiSeq sequencer far exceeds the number needed to saturate the annotated transcriptomes of diverse bacteria growing in monoculture. Moreover, as sequencing depth increases, so too does the detection of cDNAs that likely correspond to spurious transcripts or genomic DNA contamination. Finally, even when dozens of barcoded individual cDNA libraries are sequenced in a single lane, the vast majority of transcripts in each sample can be detected and numerous genes differentially expressed between samples can be identified.ConclusionsOur analysis provides a guide for the many researchers seeking to determine the appropriate sequencing depth for RNA-Seq-based studies of diverse bacterial species.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/1471-2164-13-734", 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.2421947", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2441427", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2346932", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1023790", 
        "issn": [
          "1471-2164"
        ], 
        "name": "BMC Genomics", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "13"
      }
    ], 
    "keywords": [
      "bacterial transcriptomes", 
      "RNA-seq", 
      "number of reads", 
      "cDNA library", 
      "appropriate sequencing depth", 
      "diverse bacterial species", 
      "Illumina HiSeq sequencer", 
      "RNA-seq profiling", 
      "individual cDNA libraries", 
      "spurious transcripts", 
      "diverse bacteria", 
      "numerous genes", 
      "genomic DNA contamination", 
      "individual transcripts", 
      "transcriptome", 
      "gene expression", 
      "sequencing depth", 
      "bacterial species", 
      "DNA contamination", 
      "transcripts", 
      "reads", 
      "profiling", 
      "single lane", 
      "cDNA", 
      "genes", 
      "sequencing", 
      "species", 
      "monoculture", 
      "central challenge", 
      "abundance", 
      "library", 
      "bacteria", 
      "vast majority", 
      "expression", 
      "sequencer", 
      "number", 
      "thousands", 
      "dozens", 
      "detection of cDNA", 
      "ConclusionsOur analysis", 
      "contamination", 
      "changes", 
      "systematic examination", 
      "analysis", 
      "samples", 
      "majority", 
      "effective approach", 
      "ResultsWe", 
      "experiments", 
      "findings", 
      "large dynamic range", 
      "increase", 
      "study", 
      "range", 
      "comparison", 
      "approach", 
      "detection", 
      "depth", 
      "dynamic range", 
      "influence", 
      "challenges", 
      "depth increases", 
      "researchers", 
      "sample influence", 
      "guide", 
      "lanes", 
      "examination"
    ], 
    "name": "How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes?", 
    "pagination": "734", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1018646208"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/1471-2164-13-734"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "23270466"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/1471-2164-13-734", 
      "https://app.dimensions.ai/details/publication/pub.1018646208"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-12-01T06:30", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221201/entities/gbq_results/article/article_565.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/1471-2164-13-734"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-13-734'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-13-734'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-13-734'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-13-734'


 

This table displays all metadata directly associated to this object as RDF triples.

228 TRIPLES      21 PREDICATES      108 URIs      90 LITERALS      13 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/1471-2164-13-734 schema:about N166789fd83194996aad1c37e7cd2f7f2
2 N3cbf197b37b84b7fbed3d91e6df42b18
3 Naca357559aa24484b2785435d41aea40
4 Nc326e77ec1db4742a70a9bd867e313a9
5 Nd0bdd5cf56ad4859b59f26fc929149de
6 Ne6dcd424062e428b9fa39e174eecf126
7 anzsrc-for:06
8 anzsrc-for:0604
9 schema:author N97406dcecf5d4fd19e4c4f4188c03618
10 schema:citation sg:pub.10.1038/nature08756
11 sg:pub.10.1038/nbt.1582
12 sg:pub.10.1038/nmeth.1491
13 sg:pub.10.1038/nmeth.1507
14 sg:pub.10.1038/nrg2484
15 sg:pub.10.1038/nrg2695
16 sg:pub.10.1186/gb-2010-11-10-r106
17 sg:pub.10.1186/gb-2010-11-2-r15
18 sg:pub.10.1186/gb-2011-12-1-r1
19 sg:pub.10.1186/gb-2012-13-3-r23
20 schema:datePublished 2012-12-27
21 schema:datePublishedReg 2012-12-27
22 schema:description BackgroundHigh-throughput sequencing of cDNA libraries (RNA-Seq) has proven to be a highly effective approach for studying bacterial transcriptomes. A central challenge in designing RNA-Seq-based experiments is estimating a priori the number of reads per sample needed to detect and quantify thousands of individual transcripts with a large dynamic range of abundance.ResultsWe have conducted a systematic examination of how changes in the number of RNA-Seq reads per sample influences both profiling of a single bacterial transcriptome and the comparison of gene expression among samples. Our findings suggest that the number of reads typically produced in a single lane of the Illumina HiSeq sequencer far exceeds the number needed to saturate the annotated transcriptomes of diverse bacteria growing in monoculture. Moreover, as sequencing depth increases, so too does the detection of cDNAs that likely correspond to spurious transcripts or genomic DNA contamination. Finally, even when dozens of barcoded individual cDNA libraries are sequenced in a single lane, the vast majority of transcripts in each sample can be detected and numerous genes differentially expressed between samples can be identified.ConclusionsOur analysis provides a guide for the many researchers seeking to determine the appropriate sequencing depth for RNA-Seq-based studies of diverse bacterial species.
23 schema:genre article
24 schema:isAccessibleForFree true
25 schema:isPartOf N5a405a81eebf46309745d8553388bf12
26 N8061e7cd8e68430a93f93e8ceea6c134
27 sg:journal.1023790
28 schema:keywords ConclusionsOur analysis
29 DNA contamination
30 Illumina HiSeq sequencer
31 RNA-seq
32 RNA-seq profiling
33 ResultsWe
34 abundance
35 analysis
36 approach
37 appropriate sequencing depth
38 bacteria
39 bacterial species
40 bacterial transcriptomes
41 cDNA
42 cDNA library
43 central challenge
44 challenges
45 changes
46 comparison
47 contamination
48 depth
49 depth increases
50 detection
51 detection of cDNA
52 diverse bacteria
53 diverse bacterial species
54 dozens
55 dynamic range
56 effective approach
57 examination
58 experiments
59 expression
60 findings
61 gene expression
62 genes
63 genomic DNA contamination
64 guide
65 increase
66 individual cDNA libraries
67 individual transcripts
68 influence
69 lanes
70 large dynamic range
71 library
72 majority
73 monoculture
74 number
75 number of reads
76 numerous genes
77 profiling
78 range
79 reads
80 researchers
81 sample influence
82 samples
83 sequencer
84 sequencing
85 sequencing depth
86 single lane
87 species
88 spurious transcripts
89 study
90 systematic examination
91 thousands
92 transcriptome
93 transcripts
94 vast majority
95 schema:name How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes?
96 schema:pagination 734
97 schema:productId N0fca8cae68694c8a824403195ef0d39b
98 N2742cf4618b1401d816c9cebba6af3b9
99 N9bd2cffabe6844398cf8caf9dce38654
100 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018646208
101 https://doi.org/10.1186/1471-2164-13-734
102 schema:sdDatePublished 2022-12-01T06:30
103 schema:sdLicense https://scigraph.springernature.com/explorer/license/
104 schema:sdPublisher Nbe780925566a456798c9e3324bbf05ee
105 schema:url https://doi.org/10.1186/1471-2164-13-734
106 sgo:license sg:explorer/license/
107 sgo:sdDataset articles
108 rdf:type schema:ScholarlyArticle
109 N0fca8cae68694c8a824403195ef0d39b schema:name doi
110 schema:value 10.1186/1471-2164-13-734
111 rdf:type schema:PropertyValue
112 N166789fd83194996aad1c37e7cd2f7f2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
113 schema:name Escherichia coli
114 rdf:type schema:DefinedTerm
115 N1e19d8f3f25e48668fb22969561df05b rdf:first sg:person.01205530423.53
116 rdf:rest N20791bb519ef4aefa0d716e68bd4245d
117 N20791bb519ef4aefa0d716e68bd4245d rdf:first sg:person.01213752162.55
118 rdf:rest rdf:nil
119 N2742cf4618b1401d816c9cebba6af3b9 schema:name dimensions_id
120 schema:value pub.1018646208
121 rdf:type schema:PropertyValue
122 N3cbf197b37b84b7fbed3d91e6df42b18 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
123 schema:name Open Reading Frames
124 rdf:type schema:DefinedTerm
125 N5a405a81eebf46309745d8553388bf12 schema:volumeNumber 13
126 rdf:type schema:PublicationVolume
127 N7bfd6d89655d4ae5961118f4292a624b rdf:first sg:person.01170225154.35
128 rdf:rest N1e19d8f3f25e48668fb22969561df05b
129 N8061e7cd8e68430a93f93e8ceea6c134 schema:issueNumber 1
130 rdf:type schema:PublicationIssue
131 N97406dcecf5d4fd19e4c4f4188c03618 rdf:first sg:person.01163021216.55
132 rdf:rest Nd3b49dd46f0b4bcbbf826cacd2d21918
133 N9bd2cffabe6844398cf8caf9dce38654 schema:name pubmed_id
134 schema:value 23270466
135 rdf:type schema:PropertyValue
136 Naca357559aa24484b2785435d41aea40 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
137 schema:name Molecular Sequence Annotation
138 rdf:type schema:DefinedTerm
139 Nbe780925566a456798c9e3324bbf05ee schema:name Springer Nature - SN SciGraph project
140 rdf:type schema:Organization
141 Nc326e77ec1db4742a70a9bd867e313a9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
142 schema:name Gene Library
143 rdf:type schema:DefinedTerm
144 Nd0bdd5cf56ad4859b59f26fc929149de schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
145 schema:name High-Throughput Nucleotide Sequencing
146 rdf:type schema:DefinedTerm
147 Nd32a4a542173462d94d3c94e193dbbbc schema:affiliation grid-institutes:grid.66859.34
148 schema:familyName Chin
149 schema:givenName Melissa
150 rdf:type schema:Person
151 Nd3b49dd46f0b4bcbbf826cacd2d21918 rdf:first Nd32a4a542173462d94d3c94e193dbbbc
152 rdf:rest N7bfd6d89655d4ae5961118f4292a624b
153 Ne6dcd424062e428b9fa39e174eecf126 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
154 schema:name Gene Expression Profiling
155 rdf:type schema:DefinedTerm
156 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
157 schema:name Biological Sciences
158 rdf:type schema:DefinedTerm
159 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
160 schema:name Genetics
161 rdf:type schema:DefinedTerm
162 sg:grant.2346932 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2164-13-734
163 rdf:type schema:MonetaryGrant
164 sg:grant.2421947 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2164-13-734
165 rdf:type schema:MonetaryGrant
166 sg:grant.2441427 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2164-13-734
167 rdf:type schema:MonetaryGrant
168 sg:journal.1023790 schema:issn 1471-2164
169 schema:name BMC Genomics
170 schema:publisher Springer Nature
171 rdf:type schema:Periodical
172 sg:person.01163021216.55 schema:affiliation grid-institutes:grid.66859.34
173 schema:familyName Haas
174 schema:givenName Brian J
175 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01163021216.55
176 rdf:type schema:Person
177 sg:person.01170225154.35 schema:affiliation grid-institutes:grid.66859.34
178 schema:familyName Nusbaum
179 schema:givenName Chad
180 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01170225154.35
181 rdf:type schema:Person
182 sg:person.01205530423.53 schema:affiliation grid-institutes:grid.66859.34
183 schema:familyName Birren
184 schema:givenName Bruce W
185 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01205530423.53
186 rdf:type schema:Person
187 sg:person.01213752162.55 schema:affiliation grid-institutes:grid.38142.3c
188 schema:familyName Livny
189 schema:givenName Jonathan
190 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213752162.55
191 rdf:type schema:Person
192 sg:pub.10.1038/nature08756 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050182699
193 https://doi.org/10.1038/nature08756
194 rdf:type schema:CreativeWork
195 sg:pub.10.1038/nbt.1582 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026972767
196 https://doi.org/10.1038/nbt.1582
197 rdf:type schema:CreativeWork
198 sg:pub.10.1038/nmeth.1491 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019899367
199 https://doi.org/10.1038/nmeth.1491
200 rdf:type schema:CreativeWork
201 sg:pub.10.1038/nmeth.1507 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005850821
202 https://doi.org/10.1038/nmeth.1507
203 rdf:type schema:CreativeWork
204 sg:pub.10.1038/nrg2484 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030687647
205 https://doi.org/10.1038/nrg2484
206 rdf:type schema:CreativeWork
207 sg:pub.10.1038/nrg2695 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019859466
208 https://doi.org/10.1038/nrg2695
209 rdf:type schema:CreativeWork
210 sg:pub.10.1186/gb-2010-11-10-r106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031289083
211 https://doi.org/10.1186/gb-2010-11-10-r106
212 rdf:type schema:CreativeWork
213 sg:pub.10.1186/gb-2010-11-2-r15 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013435656
214 https://doi.org/10.1186/gb-2010-11-2-r15
215 rdf:type schema:CreativeWork
216 sg:pub.10.1186/gb-2011-12-1-r1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045286538
217 https://doi.org/10.1186/gb-2011-12-1-r1
218 rdf:type schema:CreativeWork
219 sg:pub.10.1186/gb-2012-13-3-r23 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036305770
220 https://doi.org/10.1186/gb-2012-13-3-r23
221 rdf:type schema:CreativeWork
222 grid-institutes:grid.38142.3c schema:alternateName Channing Laboratory, Brigham and Women’s Hospital, Harvard Medical School, 02115, Boston, MA, USA
223 schema:name Channing Laboratory, Brigham and Women’s Hospital, Harvard Medical School, 02115, Boston, MA, USA
224 Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA
225 rdf:type schema:Organization
226 grid-institutes:grid.66859.34 schema:alternateName Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA
227 schema:name Genome Sequencing and Analysis Program, The Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA
228 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...