Difference between revisions of "Textpresso-based automated extraction of concise descriptions"
Line 62: | Line 62: | ||
*Caltech and non-caltech data? | *Caltech and non-caltech data? | ||
*Source 1: GO data | *Source 1: GO data | ||
− | **Download gene_association.wb.gz from GO consortium | + | **Download gene_association.wb.gz from GO consortium: http://www.geneontology.org/GO.current.annotations.shtml?all |
+ | **All rows with column 15 (assigned by) with 'WB' are WormBase annotations, those with 'UniProtKB' or 'InterPro' are from those databases | ||
+ | **Need data from those rows where column 9 has value 'F' (Molecular Function), the associated genes are from column 2 (UniProt ID), column 3 (DB_Object symbol), eg, wht-7, GO terms are from column 5. | ||
+ | *Source 2: Homology data, see #2 | ||
'''2. Orthology, Homology and Paralog data''' | '''2. Orthology, Homology and Paralog data''' | ||
Line 70: | Line 73: | ||
'''3. Processes''' | '''3. Processes''' | ||
*Caltech data | *Caltech data | ||
− | *Source 1: GO data in postgres | + | *GO data |
+ | *Source 1: Download gene_association.wb.gz from GO consortium: http://www.geneontology.org/GO.current.annotations.shtml?all | ||
+ | **All rows with column 15 (assigned by) with 'WB' are WormBase annotations, those with 'UniProtKB' or 'InterPro' are from those databases | ||
+ | **Need data from those rows where column 9 has value 'P' (Process), the associated genes are from column 2 (UniProt ID), column 3 (DB_Object symbol), eg, wht-7, GO terms are from column 5. | ||
+ | *GO data in postgres | ||
**Paper -- gop_paper | **Paper -- gop_paper | ||
**WBGene -- gop_wbgene | **WBGene -- gop_wbgene | ||
**GO -- gop_goontology | **GO -- gop_goontology | ||
**GO Term -- gop_goid | **GO Term -- gop_goid | ||
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− | |||
− | |||
− | |||
− | |||
− | |||
*Contact Person: Kimberly, Ranjana | *Contact Person: Kimberly, Ranjana | ||
− | *Source | + | *Source 2: Topic data |
**OA field: Gene, PG table name:pro_wbgene | **OA field: Gene, PG table name:pro_wbgene | ||
**OA field:WBPaper, PG table name:pro_paper | **OA field:WBPaper, PG table name:pro_paper | ||
Line 97: | Line 98: | ||
**File name:phenotype_association.WS243.wb | **File name:phenotype_association.WS243.wb | ||
**Rows with 'NOT' should be ignored for this search. | **Rows with 'NOT' should be ignored for this search. | ||
+ | ** | ||
*Contact Person: Karen | *Contact Person: Karen | ||
Revision as of 21:51, 2 June 2014
Contents
- 1 Generating gene sets with and without concise descriptions
- 2 Location of project-related files on Textpresso
- 3 Semantic categories in a Concise Description
- 4 Template for a Concise Description
- 5 Data mining (mining data from Postgres and/or Acedb) for the semantic categories
- 6 Publications related to Text-mining methods
Generating gene sets with and without concise descriptions
Set of genes with a concise description
Query for all genes with a concise description from Postgres: Relevant postgres table names:
- con_wbgene: Stores the WBGene ID and gene names
- con_desctype: Type of description (relevant for us: Concise_description)
- con_desctext: Text of the concise description
Query for all WBGenes that have a concise description (in con_desctext AND con_desctype):
SELECT DISTINCT(con_wbgene) FROM con_wbgene WHERE joinkey IN (SELECT joinkey FROM con_desctext WHERE con_desctext IS NOT NULL) AND joinkey IN (SELECT joinkey FROM con_desctype WHERE con_desctype IS NOT NULL) ORDER BY con_wbgene;
- Number of genes with a concise description (as of 05.07.2014)=6,624
Set of genes with no concise description
Set of genes with no concise description and at least one published paper
http://textpresso-dev.caltech.edu/concise_descriptions/
Semantic categories in a Concise Description
1. Molecular identity
2. Orthology/Similarity
3. Mutant Phenotypes
4. Processes
5. Pathways
6. Genetic Interaction
7. Physical Interaction
8. Gene regulation data
9. Molecular Function
10. Tissue expression (may include life-stage)
11. Sub-cellular localization (may include life-stage)
Template for a Concise Description
Molecular identity <Gene> encodes a <molecular identity>; Orthology/Similarity <Gene> is (orthologous, similar) to .....; Phenotypes <Gene> mutants exhibit the following phenotypes, <phenotypes>. Process/Pathway <Gene> is (required, functions, regulates, is involved in, is part of) ....., as mutants of <gene> exhibit <phenotypes>; Genetic interaction with respect to Process or Pathway <Gene> interacts genetically with <gene1, gene2> ..... in <Process, Pathway>; Physical interaction <Protein> physically interacts with (protein, DNA, RNA) .....; Molecular Function <Protein> has ..... activity in (in vitro, in vivo) assays; Tissue Expression <Gene/Protein> is expressed in ..... and expression in ..... is (positively, negatively) regulated by <Gene/Protein>.....; Sub-cellular localization <Protein> is localized to <cellular component> and expression in <cellular component> is <positively, negatively> regulated by .....
Note: Not all descriptions may follow the exact order or choice of words.
Data mining (mining data from Postgres and/or Acedb) for the semantic categories
1. Molecular identity
- Caltech and non-caltech data?
- Source 1: GO data
- Download gene_association.wb.gz from GO consortium: http://www.geneontology.org/GO.current.annotations.shtml?all
- All rows with column 15 (assigned by) with 'WB' are WormBase annotations, those with 'UniProtKB' or 'InterPro' are from those databases
- Need data from those rows where column 9 has value 'F' (Molecular Function), the associated genes are from column 2 (UniProt ID), column 3 (DB_Object symbol), eg, wht-7, GO terms are from column 5.
- Source 2: Homology data, see #2
2. Orthology, Homology and Paralog data
- Ace tags: ?Gene Ortholog_other, Paralog
- Contact: Michael Paulini
3. Processes
- Caltech data
- GO data
- Source 1: Download gene_association.wb.gz from GO consortium: http://www.geneontology.org/GO.current.annotations.shtml?all
- All rows with column 15 (assigned by) with 'WB' are WormBase annotations, those with 'UniProtKB' or 'InterPro' are from those databases
- Need data from those rows where column 9 has value 'P' (Process), the associated genes are from column 2 (UniProt ID), column 3 (DB_Object symbol), eg, wht-7, GO terms are from column 5.
- GO data in postgres
- Paper -- gop_paper
- WBGene -- gop_wbgene
- GO -- gop_goontology
- GO Term -- gop_goid
- Contact Person: Kimberly, Ranjana
- Source 2: Topic data
- OA field: Gene, PG table name:pro_wbgene
- OA field:WBPaper, PG table name:pro_paper
- Contact Person: Karen
4. Pathway (No database source for now?)
5. Mutant Phenotypes
- Caltech data
- Source 1: Phenotype OA, PG table name:(Phenotypes are added to variation and not genes)
- Source 2: Acedb tag: Under ?Gene, Reference_allele ?Variation and Allele ?Variation and Under ?Variation Phenotype
- Source 3: phenotype_association file:ftp://ftp.wormbase.org/pub/wormbase/releases/WS243/ONTOLOGY/
- File name:phenotype_association.WS243.wb
- Rows with 'NOT' should be ignored for this search.
- Contact Person: Karen
6. Genetic Interaction and 7. Physical Interaction
- Caltech data
- Source 1: gene_association.wb
- ftp://ftp.wormbase.org/pub/wormbase/releases/WS243/ONTOLOGY/
- File name:gene_association.WS243.wb.c_elegans
- Rows with a 'IGI' in column 7 indicate a genetic interaction between the WBgenes in column 2/3 and column 8
- Rows with a 'IPI" in column 7 indicate a physical interaction between the WBgenes in column 2/3 and column 8
- Source 2: Interaction OA and tables
- "Field Name" = Postgres Table:
- "Paper" = int_paper
- "Interaction Type" = int_type
- "Bait overlapping gene" = int_genebait
- "Target overlapping gene" = int_genetarget
- "Non-directional Gene(s)" = int_genenondir
- "Effector Gene(s)" = int_geneone
- "Affected Gene(s)" = int_genetwo
Example statements:
If int_type = "Physical"
<int_genebait> interacts physically with <int_genetarget> (and vice versa)
If int_type = "Genetic - Synthetic ( Synthetic )"
<int_genenondir> interacts with <other int_genenondir(s)> in a synthetic genetic interaction
If int_type = "Genetic - Suppression ( Suppression )"
<int_geneone> genetically suppresses <int_genetwo>
8. Gene regulation
- Caltech data
- Source: Gene regulation data in genereg OA
- Positive_regulate Anatomy_term "<grg_pos_anatomy>"
- Positive_regulate Life_stage "<grg_pos_lifestage>"
- Positive_regulate Subcellular_localization "<grg_pos_scl>"
- Positive_regulate Subcellular_localization_text "<grg_pos_scltext>"
- Negative_regulate Anatomy_term "<grg_neg_anatomy>"
- Negative_regulate Life_stage "<grg_neg_lifestage>"
- Negative_regulate Subcellular_localization "<grg_neg_scl>"
- Negative_regulate Subcellular_localization_text "<grg_neg_scltext>"
- Does_not_regulate Anatomy_term "<grg_not_anatomy>"
- Does_not_regulate Life_stage "<grg_not_lifestage>"
- Does_not_regulate Subcellular_localization "<grg_subcellloc>"
- Does_not_regulate Subcellular_localization_text "<grg_not_scltext>"
- Trans_regulated_gene "<grg_transregulated>"
- Trans_regulator_gene "<grg_transregulator>"
- No Subdata Result "<grg_result>"
9. Molecular Function
- Caltech data: GO Molecular Function
- Source 1: GO OA, PG table name:
- Source 3: gene_association.WSXXX.c_elegans file:
- ftp://ftp.wormbase.org/pub/wormbase/releases/WS243/ONTOLOGY/
- Rows with a 'F' in column 9 indicates GO molecular function associated with a gene.
- Contact Person: Kimberly, Ranjana
10. Tissue expression and life stage
- Caltech data
- Source 1: Expression data
- OA (exprpat), PG table names:
- exp_anatomy for anatomy terms
- exp_goid for subcell localization
- exp_lifestage for life stage
- exp_paper for paper
- exp_gene for gene
- Contact Person: Daniela
11. Sub-cellular localization
- Caltech data
- Source 1: GO cellular component
- Source 2: gene_association file
- ftp://ftp.wormbase.org/pub/wormbase/releases/WS243/ONTOLOGY/
- File name:gene_association.WS243.wb.c_elegans
- Automatically generating gene summaries from biomedical literature.
Ling X, Jiang J, He X, Mei Q, Zhai C, Schatz B.
Pac Symp Biocomput. 2006:40-51.
PMID:17094226
- Generating gene summaries from biomedical literature: A study of semi-structured summarization
Xu Ling *, Jing Jiang, Xin He, Qiaozhu Mei, Chengxiang Zhai, Bruce Schatz
Information Processing and Management 43 (2007) 1777–1791
Back To Concise Descriptions