Class "Abstracts" Abstract Class

Description

S4 Class with three slots Journal, Abstract, PMID to store abstracts from PubMed

Objects from the Class

Objects can be created by calls of the form new("Abstracts", ...).

Slots

Journal:

Object of class "character"to store Journals of the abstracts from PubMed

Abstract:

Object of class "character"to store Abstracts from the PubMed

PMID:

Object of class "numeric"to store PMIDs of abstracts from PubMed

Methods

No methods defined with class "Abstracts" in the signature.

Author(s)

S.Ramachandran, Ab Rauf Shah

See Also

searchabsL getabs contextSearch Genewise Yearwise combineabs subabs subsetabs readabs

Examples

showClass("Abstracts")

To obtain the Buzz Word Index of terms from the Abstracts.

Description

This function is used to obtain the Buzz word index value for the terms.

Usage

BWI(current, previous, n, N)

Arguments

Value

It returns a list containing BWI value for the given word.

Author(s)

S.Ramachandran

References

Jensen, Lars Juhl, Jasmin Saric, and Peer Bork. "Literature mining for the biologist: from information retrieval to biological discovery." Nature reviews genetics 7.2 (2006): 119-129.

See Also

genes_BWI

Examples

## Not run: result = BWI(mycurrentabs, mypreviousabs, "insulin", "inflammation")
## BWI for the term "insulin" and the theme is inflammation. 
## Note that in the previous, years are starting one before the current year 2015; 
## current is an S4 object containing the output from currentabs_fn()
## previous is an S4 object containing the output from previousabs_fn().
## 'n' and 'N' are query terms whose BWI is sought and the theme respectively

To find the conclusion from the abstract(s).

Description

This function is designed for the user convinience, so that user can get the conclusion from the abstract(s) with out reading the whole abstract(s).

Usage

Find_conclusion(y)

Arguments

Value

A list containing conclusions of given abstract(s)

Author(s)

S.Ramachandran, Jyoti Rani

Examples

## Not run: res1 = Find_conclusion(y)
##  here 'y' is an S4 object of class Abstract.

Data containing Entrez Ids

Description

This dataset is used in DAVID_info function of the package, and it contains the Entrez Ids for the respective genes and these Entrez Ids will be used to get information about human genes.

Usage

data(GeneToEntrez)

Format

The format is: chr "GeneToEntrez"

Examples

data(GeneToEntrez)

To Search the number of abstracts for Genes

Description

Genewise reports the number of abstracts for given gene(s) name(s)

Usage

Genewise(object, gene)

Arguments

Details

This function will report the number of abstracts containing the query gene term(s) [HGNC approved symbols], and the result is saved in a text file "dataout.txt". Genewise() will report numbers of abstracts only. The abstracts themselves for corresponding gene names can be obtained using searchabsL() and searchabsT.

Value

Genewise will return an R object containing the abstracts for given gene, and a text file named "dataout.txt" containing the number of abstracts

Author(s)

S. Ramachandran, Jyoti Rani

Examples

## Not run: Genewise(x, "TLR4")
## here 'x' contains the S4 object of Abstracts.

method to find the abstracts for the given gene.

Description

Genewise The method Genewise will automatically report the numbers of abstracts for a given gene. It will write the result in the text file named "dataout.txt"

Methods

signature(object = "Abstracts")

This method will search in an S4 object, containiing abstracts. It will write a text file named "dataout.txt", containing the number of abstracts for the query gene terms

To extract sentences from the Abstracts

Description

Give_Sentences will help to extract the sentence containing query term/s from the large corpus.

Usage

Give_Sentences(m, abs)

Arguments

Value

It will return a list object containing sentences

Author(s)

S.Ramachandran

See Also

Give_Sentences_PMC

Examples

## Not run: Give_Sentences("diabetes", Abstracts)

To fetch the sentence from the PMC full text article

Description

Give_Sentences_PMC is used to extract the sentences from the full text article of given PMC id/s.

Usage

Give_Sentences_PMC(PMCID, term)

Arguments

Value

It will return a list object containing the sentences for query term from the given article.

Author(s)

S.Ramachandran

Examples

## Not run: Give_Sentences_PMC(PMC4039032, "atherosclerosis")

HGNC Class for package.

Description

"HGNC"

Objects from the Class

Objects can be created by calls of the form new("HGNC", ...).

Slots

HGNCID:

Object of class "character"

ApprovedSymbol:

Object of class "character"

ApprovedName:

Object of class "character"

Status:

Object of class "character"

PreviousSymbols:

Object of class "character"

Aliases:

Object of class "character"

Chromosome:

Object of class "character"

AccessionNumbers:

Object of class "character"

RefSeqIDs:

Object of class "character"

Author(s)

Dr.S.Ramachandran, Ab Rauf Shah

See Also

Abstracts

Examples

showClass("HGNC")

R Data containing HGNC2UniprotID data mapping.

Description

This dataset contains HGNC2UniprotID from Uniprot and is used in uniprotfn() function of this package, to get the information of a gene from the Uniprot.

Usage

data(HGNC2UniprotID)

Format

The format is: chr "HGNC2UniprotID"

Details

The dataset contains HGNC2UniprotID

References

UniProt Consortium. "The universal protein resource (UniProt)." Nucleic acids research 36.suppl 1 (2008): D190-D195. http://www.uniprot.org/

Examples

data(HGNC2UniprotID)

R Data containing HGNC data.

Description

This dataset contains data from Human Gene Nomenclature Committe i.e HGNC ID, HGNC approved symbol, approved name, gene synonyms, chromosome no., accession numbers and RefSeq ids.

Usage

data(HGNCdata)

Format

The format is: chr "HGNCdata"

Details

The dataset contains HGNCdata

References

Povey, Sue, et al. "The HUGO gene nomenclature committee (HGNC)." Human genetics 109.6 (2001): 678-680. http://www.genenames.org/

Examples

data(HGNCdata)

To Tokenize the sentences

Description

SentenceToken will tokenize abstracts into individual sentences.

Usage

SentenceToken(x)

Arguments

Details

This function is necessary for extracting sentences from abstracts, used by contextSearch function. The tokenization principle follows the overall strategy as described in contextSearch

Value

A character vector of sentences

Author(s)

S.Ramachandran

Examples

## Not run: SentenceToken(x)

To Search abstracts Year wise

Description

Yearwise reports the no. of abstracts in a year.

Usage

Yearwise(object, year)

Arguments

Details

Yearwise() is useful to find the no. of abstracts for the given year.

Value

A text file containing the no. of abstracts for given Year(s)

Author(s)

Dr.S.Ramachandran

Examples

## Not run: Yearwise(myabs, "2011") or
Yearwise(myabs, c("2011", "2013", "2009")
## End(Not run)
## Here myabs is the object containing  PubMed abstracts.

Yearwise Year wise extraction of Abstracts

Description

Yearwise will report the abstracts for given year(s).

Methods

signature(object = "Abstracts")

This method "Yearwise" is written to fetch the abstracts yearly.

To extract sentences with nultiple keywords from Abstracts

Description

additional_info will help to extract the sentences containing multiple query term(s) from a large corpus of multiple abstracts.

Usage

additional_info(abs, pmid, keywords)

Arguments

Value

It will return a matrix object containing PMID, keywords and sentences

Author(s)

Surabhi Seth

See Also

Give_Sentences

Examples

## Not run: additional_info(abs = Abstract, pmid = "26564970"", keywords = "text-mining" )

To extract sentences containing Alias of the Human Genes from Pubmed abstracts.

Description

alias_fn This function returns the sentences containing alias of gene and the user given terms from the Abstracts using HGNC gee data table. In this sense this function is a 2 Dimensional search.

Usage

alias_fn(genes, data, abs, filename, terms)

Arguments

Value

An output file containing sentences with aliases of genes.For convenience both the official symbol and the corresponding alias are written in the output. The PMID of the corresponding Abstract containing the extracted sentence also appears just before the sentence. Note that multiple sentences from different abstracts are clubbed together under one gene alias that appears in those sentences.

Author(s)

S.Ramachandran

See Also

prevsymbol_fn

Examples

## Not run: alias_fn(genes,data,myabs,"nephro_",c("diabetic nephropathy","kidney disease"))

## genes output of gene_atomization()

To Get Alternative names of Genes

Description

This function is used to retrieve the Alternative names of genes from UniProt using HGNC gene symbol.

Usage

altnamesfun(m)

Arguments

Value

It returns a list of alternative names of given Gene symbols.

Author(s)

S.Ramachandran

References

UniProt Consortium. "The universal protein resource (UniProt)." Nucleic acids research 36.suppl 1 (2008): D190-D195. http://www.uniprot.org/

See Also

uniprotfun, ~~~

Examples

## Not run: test = altnamesfun(c("ADIPOQ","BDNF"))
## here "ADIPOQ" is the HGNC gene symbol for which alternative name(s) is required.

To clean the result of searchabsL

Description

It will remove the 'NONE' abstracts from the result of searchabsL.

Usage

cleanabs(object)

Arguments

Value

an S4 object of class Abstracts.

Author(s)

Jyoti Rani

See Also

searchabsL

Examples

## Not run: test1 = searchabsL(abs, include=c("term1", "term2"));
test2 = cleanabs(test1)
## End(Not run)
## here 'abs' is an S4 object of class Abstracts
## 'term1', 'term2' are the searchterms
## test1 is an S4 object containing abstracts for given terms
## and test2 is an S4 object of class Abstracts containing clean abstracts of searchabsL

Methods for Function cleanabs

Description

To clean 'NONE' part of searchabsL output.

Methods

signature(object = "Abstracts")

From an S4 object of class 'Abstracts' the cleanabs function is able to clean the output of searchabsL by removing the 'NONE' part of resultant abstracts.

To Find the highest frequency of words within clusters

Description

Function for finding the word (term) of highest frequency within clusters.

Usage

cluster_words(wordscluster, n)

Arguments

Value

a list containing cluster and its highest frequency word

Author(s)

S. Ramachandran

See Also

wordscluster

Examples

## Not run: test = cluster_words(wordscluster, 5)
## wordscluster is an R object of wordscluster
## 5 is number of cluster
## End(Not run)

Extracts multiple sentence with co-occurrence of two sets of terms)

Description

Extracts single or multiple sentences with co-occurrence of given terms

Usage

co_occurrence_advance(abstract, term1, term2, n)

Arguments

Details

Sentences with co-occurrence of two terms will be extracted along with the corresponding PMIDs. The output will be a data frame. In regard to the argument n, when the value is 0 then the co-occurrence is sought in the same sentence. When the value is 1, then the co-occurrence is sought in two consecutive sentences, namely, first term in the first sentence and second term in the next sentence. When the value is 2, then the co-occurrence is sought in two sentences separated by a sentence without either term1 or term2.

Value

It will return a data frame object containing PMID,sentences and the terms pairs.

Author(s)

Shashwat Badoni Surabhi Seth

See Also

co_occurrence_fn

Examples

## Not run: co_occurrence_advance(myabs,"resistance", c("genes","genetic"), 2

Extracts sentences with co-occurrence of two sets of terms

Description

co_occurrence_fn will automatically extract sentences with co-occurrence of two sets of terms.

Usage

co_occurrence_fn(terms1, abs, filename, terms2)

Arguments

Details

Sentences with co-occurrence of two terms will be extracted along with the corresponding PMIDs. The data will be written in a text file with the user given filename and the word co_occurrence will be suffixed to it.

Value

A text file.

Author(s)

S.Ramachandran

Examples

## Not run: co_occurrence_fn("resistance",myabs,"resistance_genetic",c("genes","genetic")
##

To combine the abstracts

Description

combineabs will automatically combine two abtracts of two objects.

Usage

combineabs(object1, object2)

Arguments

Details

Two objects of class 'Abstracts' are combined to return non-redundant combined abstracts. It can be used sequentially to combine many objects of class 'Abstracts'. It will also write the number of combined abstracts into a text file named "data_out.txt"

Value

An R object containing the combined abstracts, and a text file named "data_out.txt" containing the number of abstracts combined together

Author(s)

S.Ramachandran, Jyoti Rani

Examples

## Not run: res1 = combineabs(x,y)
## here 'x', 'y' are the S4 objects of class 'Abstracts'.

Abstracts Method to Combine Abstracts

Description

combineabs method to combine the abstracts. object1 and object2 are from Abstracts class.

Methods

signature(object1 = "Abstracts")

An S4 object of class "Abstracts"

signature(object2 = "Abstracts")

An S4 object of class "Abstracts"

R Data containing words which frequently in text

Description

This dataset is used to remove common words from the abstracts. This step is used for size reduction for further data mining.

Usage

data(common_words_new)

Format

The format is: chr "common_words_new"

Details

The dataset containing common words used to remove them from the text for size reduction.

References

https://en.wikipedia.org/wiki/Most_common_words_in_English

Examples

data(common_words_new)

For Context Search

Description

contextSearch is a method to extract the sentences containing a given query term

Usage

contextSearch(object, y)

Arguments

Details

It takes object of class Abstracts and query term(s) as arguments and returns a text and latex file of the sentences containing query term. The latex file can be further converted into PDF by using the system command in R i.e. system("pdflatex filename.tex"). pdflatex is a shell command in Linux to convert the latex file into PDF. In the pdf file the terms are written in bold face type to enable ease of reading

Value

contextSearch() will write two files one is a text file named "companion.txt", and other is a Latex file. If the single term is given in query then file name comes with the term name. If multiple terms are used then the file name will be "combined.tex"

Author(s)

Dr.S.Ramachandran, Jyoti Rani

Examples

## Not run: contextSearch(x, "diabetes")
## here 'x' is S4 object of class 'Abstracts', and query term is 'diabetes'.

Method for Context Search

Description

contextSearch will search the sentence for the given term(s).

Methods

signature(object = "Abstracts")

The object from where it will search should be an S4 object of class Abstracts

To calculate the cosine similarity between terms.

Description

cos_sim_calc calculates the cosine measure of similarity between pairs of terms from a corpus.

Usage

cos_sim_calc(nummatrix)

Arguments

Details

The term document matrix is taken as input and cosine meausures of similarity between all pairs of terms are calculated.

Value

A tab delimited text file containing the similarity values between all pairs of terms.

Note

This file can be input to cytoscape directly.

Author(s)

S. Ramachandran

References

https://en.wikipedia.org/wiki/Cosine_similarity

See Also

tdm_for_lsa

Examples

## Not run: x = cos_sim_calc(nummatrix)
## here nummatrix is the 'Term Document Matrix' generated from tdm_for_lsa()

Cosine Similarity Calculation by Boot Strapping

Description

cos_sim_calc_boot allows boot strap analysis. This function should be used as argument for 'statistic' in the boot function of 'boot' package.

Usage

cos_sim_calc_boot(data, indices)

Arguments

Details

while calling this function we need to transpose the input tdm and can also set the number of replicates. boot package is required to call this function.

Value

It will return a matrix containing the cosine similarity of pairs of terms in the abstracts. This object is in same format as returned by the 'boot' function of 'boot' package.

Author(s)

Dr.S.Ramachandran

See Also

tdm_for_lsa

Examples

## Not run: test_boot = boot(data = t(nummatrix), statistic = cos_sim_calc_boot, R = 2)
## here 'nummatrix' is a Term Document Matrix, boot inbuilt function of boot package, 
## R is number of replicates here it is 2. User can extend this number.

To Retrive the Abstracts for year.

Description

This function is used to extract the abstracts for year we want to study. Its output is used as input in other functions like BWI() and genes_BWI()

Usage

currentabs_fn(yr_to_include, theme, parentabs)

Arguments

Value

It returns an S4 object containing the abstracts of the given year.

Author(s)

S.Ramachandran

See Also

previousabs_fn

Examples

## Not run: test = currentabs_fn("2015", "atherosclerosis", diabetesabs)
## here "2015" is the year for which, we wish to extract the abstracts on theme"Atherosclerosis" 
## from the large corpus of diabetes i.e. diabetesabs.

To find the introduction and conclusion from the abstracts.

Description

it helps to fetch the introduction and conclusion part from the abstracts.

Usage

find_intro_conc_html(y, themes, all)

Arguments

Details

find_intro_conc_htmlprovides an HTML file containing space separated introduction and conclusion part from the abstracts of given query term as well as gives a link directly to PubMed for the resulting PMID.

Value

an HTML file.

Author(s)

S.Ramachandran, Jyoti Rani

See Also

input_for_find_intro_conc_html

Examples

## Not run: test = find_intro_conc_html(abs, "diet", all=FALSE)
## here 'abs' is an S4 object of class Abstracts
## and 'diet' is a term to be search from the abstracts
## this function works for small size of corpus, say about 30-40 abstracts

To Extract Genes from the Abstracts

Description

gene_atomization will automatically fetch the genes (HGNC approved Symbol) from the text and report their frequencies. presently only HGNC approved symbols are used.

Usage

gene_atomization(m)

Arguments

Details

The function writes a text file with file name "data_table.txt". The function gene_atomization() is used to obtain the name of genes along with their frequencies of occurence.

Value

A tab delimited table containing gene name and their frequencies of occurrence.

Author(s)

S.Ramachandran, Jyoti Rani

Examples

## Not run: gene_atomization(myabs)
## here myabs is an S4 object of class 'Abstracts'containing the abstracts
## uses older version of HGNC data (https://www.genenames.org/) by default. 
## users may also use other functions such as official_fn and related 
## family of functions for deeper data mining.

Function to obtain the Buzz Word Index of Genes from the abstracts.

Description

This function provides the Buzz word index for each gene. The theme is the context in which the gene is studied for e.g. atherosclerosis. Using this function user can identify abstracts with emphasis on a given gene.

Usage

genes_BWI(currentabs, previousabs, theme, genes)

Arguments

Value

It returns a dataframe containig Genes with their corresponding BWI values.

Author(s)

S.Ramachandran

See Also

BWI

Examples

## Not run: test = genes_BWI(currentabs, previousabs, theme, genes)
## currentabs is an S4 object contaning the Abtracts for the year we want to study.
## previousabs is an S4 object contaning the Abtracts for the years previous 
## than our query year for e.g. before 2015
## theme is a character value specifying the search.
## genes is a character vector of gene symbols.

function for extracting Digital Object Identifier (DOIs) of papers

Description

get_DOIs is used to extract DOIs of papers.

Usage

get_DOIs(abs)

Arguments

Details

get_DOIs allow users to get DOIs for individual papers.

Value

It returns a list object containing DOIs. This is useful for further extraction of papers

Author(s)

S.Ramachandran

Examples

## Not run: test = get_DOIs(vitiligoabs)
## 

To Get MedLinePlus Summary

Description

This function is to get the summary from MedLinePlus.

Usage

get_MedlinePlus(x)

Arguments

Value

It returns a HTML file with name result_Medline_plus.html to be opened with any browser

Author(s)

S.Ramachandran

References

www.medlineplus.gov, Conuel T. Finding answers in a beauty shop. NIH MedlinePlus: the magazine [Internet]. 2012 Fall [cited 2013 Feb 9]; 7(3):24-26. Available from: https://medlineplus.gov/magazine/issues/fall12/articles/fall12pg24-26.html

Examples

## Not run: get_MedlinePlus("malaria")

To extract NM ids from NCBI.

Description

get_NMids is to fetch the NM ids from the NCBI for corresponding gene/s to further fetch the sequence of that gene/s.

Usage

get_NMids(x)

Arguments

Value

It returns a list object containing corresponding NM id from NCBI.

Author(s)

S.Ramachandran

References

http://www.ncbi.nlm.nih.gov/gene

See Also

get_Sequences

Examples

## Not run: getNMids("5950")
## 5950 is Locus id of RBP4 gene.

To extract the PMC Ids of the abstracts.

Description

get_PMCIDs is used to fetch the PMC Ids of the abstracts from the corpus.

Usage

get_PMCIDS(abs)

Arguments

Value

It returns a list containing PMC Ids.

Author(s)

S.Ramachandran

Examples

## Not run: get_PMCIDS(abstracts)

To fetch the given PMC article tables. Deprecated

Description

get_PMCtable is used to extract the full texr article by giving query PMC Id. Deprecated.

Usage

get_PMCtable(url)

Arguments

Value

It will return a full text artcle.

Author(s)

S.Ramachandran

References

http://www.ncbi.nlm.nih.gov/pmc/

See Also

get_PMCIDS

Examples

## Not run: get_PMCtable("http://www.ncbi.nlm.nih.gov/pmc/?term=4039032")

To extract the Gene sequence from the NCBI.

Description

get_Sequences is used to fetch the sequences of genes using NM ids.

Usage

get_Sequences(x, filename)

Arguments

Value

It will return a text file containing sequence.

Author(s)

S.Ramachandran

See Also

get_NMids, ~~~

Examples

## Not run: get_Sequences("NM_012238.4", "SIRT1")

To extract the sentences for genes from the corpus.

Description

get_gene_sentences is used to extract the exact sentence in which query gene is discussed.

Usage

get_gene_sentences(genes, abs, filename)

Arguments

Value

an output file containing the sentences for given gene.

Author(s)

S.Ramachandran

Examples

## Not run: get_gene_sentences("RBP4", abstracts, "RBP4_sentence.txt")

To get the original terms from the corpus. deprecated

Description

get_original_term is used to get the exact term as it is present in corpus. This function is not recommended anymore.

Usage

get_original_term(m, n)

Arguments

Value

a list object contatining the terms.

Author(s)

S.Ramachandran, Jyoti Rani

See Also

wordscluster

Examples

## Not run: test = get_original_term(abs, words)
## here abs is an S4 object of class Abstracts
## words is the output object of cluster_words()

To get the original terms from the corpus.

Description

get_original_term2 is used to get the exact term as it is present in corpus. It takes one term at a time. For multiple terms we can use lapply.

Usage

get_original_term2(x, y)

Arguments

Value

It returns a list object containing accurate term.

Author(s)

Jyoti Rani, S.Ramachandran.

See Also

get_original_term

Examples

## Not run: test = get_original_term("hba1c", diababs)
## here it will return accurate formation of hba1c i.e. HbA1c from diababs.

To get Abstracts for a given term.

Description

getabs will automatically fetch the abstracts containing the query term. A base function of the package pubmed.mineR.

Usage

getabs(object, x, y)

Arguments

Details

getabs() is used to find and exctract the abstracts for any given term, from the large a large corpus of abstracts. It uses regexpr based search strategy.

Value

An S4 object of class 'Abstracts', containing the result abstracts for the given term.

Author(s)

Dr.S.Ramachandran

Examples

## Not run: getabs(x, "term")
## x is an S4 obeject of class abstracts containing the abstracts.

getabs To Get abstracts for a term

Description

getabs will search for the abstracts of a given term. It is case sensitive.

Methods

signature(object = "Abstracts")

This method takes three arguments, first 'object' containing data to be search, 'x', the term to be search, 'y' is logical if set "YES" will consider the case of text.

To get Abstracts for a given term.

Description

getabsT will automatically fetch the abstracts containing the query term.

Usage

getabsT(object, x, y)

Arguments

Details

getabsT() is similar to getabs(), but it performs more specific search.

Value

An object of class 'Abstracts', containing the resulted abstracts for term.

Author(s)

S.Ramachandran

Examples

## Not run: getabsT(diabdata, "term")

To Get Abstracts

Description

getabsT will automatically return the abstracts of a term from the data.

Methods

signature(object = "Abstracts")

getabsT will search for the abstracts of a term in the data, and will automatically write the number of abstracts into a text file named "dataout.txt".

To extract the abbreviated term.

Description

head_abbrev is used to find expansion for which abbreviation is used. It will help to find the falsely matching abbreviations from the abstracts.

Usage

head_abbrev(limits, term, pmid, abs)

Arguments

Value

It will return a list.

Author(s)

S.Ramachandran

Examples

## Not run: head_abbrev(50, "AR", "16893912", myabs)

fetch the abstracts using E-utilities.

Description

it helps in searching and fetching the abstracts from E-utilities using PMIDs.

Usage

input_for_find_intro_conc_html(y, all)

Arguments

Details

it takes an S4 object as input and uses its PMIDs to fetch the abstracts from E-utilities. The output will be used as input for find_intro_conc_html as it contains neat data i.e. abstracts only.

Value

a list containing abstracts and PMID

Author(s)

S.Ramachandran, Jyoti Rani

References

literature/http:/eutils.ncbi.nlm.nih.gov/

See Also

find_intro_conc_html

Examples

## Not run: test=input_for_find_intro_conc_html(abs)
## here 'abs' is an S4 object of class Abstracts.

To Get Information from Uniprot.

Description

It is an auxiliary function for altnamesfun.

Usage

local_uniprotfun(y)

Arguments

Value

It writes an output file named "x.txt" which will be used as input in altnamesfun().

Author(s)

S.Ramachandran, Jyoti Rani

See Also

uniprotfun

Examples

## Not run: local_uniprotfun("TLR4")
## here it will generate an output file named "x.txt" containing 
## result for TLR4.

To extract the sentences in asbtracts containing gene names from HGNC.

Description

names_fn matches the gene symbols to gene names and extract from HGNC.

Usage

names_fn(genes, data, abs, filename, terms)

Arguments

Value

It returns an output file containing genes with their corresponding gene names and sentences with co-occurrences if any.

Author(s)

S.Ramachandran

Examples

## Not run: 
names_fn(genes, data, diabetes_abs, "names", c("diabetic nephropathy", "DN"))

## End(Not run)
## genes output of gene_atomization()

To read the abstracts from the PubMed saved in XML format.

Description

new_xmlreadabs is modified form of xmlreadabs as it reads the abstracts downloaded or saved in XML format from PubMed. This function should be used for recent XML format from PubMed.

Usage

new_xmlreadabs(file)

Arguments

Value

an S4 object of class Abstracts containing journals, abstracts and PMID.

Note

This function is useful with recent format of XML files from PubMed. The older xmlreadabs will not work with recent format.

Author(s)

S.Ramachandran

See Also

readabsnew readabs

Examples

## Not run: xmlabs = new_xmlreadabs("easyPubMed_00001.txt")
## here "easyPubMed_00001.txt" is an xml file from PubMed using package easyPubMed

To extract the sentences containing official gene symbol from abstracts.

Description

official_fn is used to fetch the sentences containing official gene symbol from HGNC.

Usage

official_fn(genes, abs, filename, terms)

Arguments

Value

It will return a text file containing corresponding official gene symbol.

Author(s)

S.Ramachandran

Examples

## Not run: 
official_fn(genes, diabetes_abs, "genes", c("diabetic nephropathy", "DN"))

## End(Not run)
## genes output of gene_atomization()

To Find and match the PMIDs to the abstracts.

Description

pmids_to_abstracts is used to extract the abstract/s of query PMID/s.

Usage

pmids_to_abstracts(x, abs)

Arguments

Value

It will return an S4 object of class abstracts containing abstracts for query PMIDs.

Author(s)

S.Ramachandran

Examples

## Not run: pmids_to_abstracts(26878666,abs)

To Retrieve the Abstracts from the large corpus for given years.

Description

This function is used to extract the abstracts from the large corpus excluding the years and under a given theme. Its output is used in other functions like BWI and genes_BWI

Usage

previousabs_fn(yrs_to_exclude, theme, parentabs)

Arguments

Value

It returns an S4 object containing the abstracts of the given year.

Author(s)

S.Ramachandran

See Also

currentabs_fn

Examples

## Not run: test = previousabs_fn(as.character(2015:2010), "atherosclerosis", diabetesabs
## here we will get the abstracts before 2010 for 'atherosclerosis'
## from the large corpus diabetesabs.

To extract the sentences containing Previous symbols of HGNC genes.

Description

prevsymbol_fn will return the sentences containing previous symbols of the genes from the abstracts using HGNC data.

Usage

prevsymbol_fn(genes, data, abs, filename, terms)

Arguments

Value

It returns a text file containing gene symbol with corresponding previous symbols.

Author(s)

S.Ramachandran

See Also

names_fn, official_fn

Examples

## Not run: 
prevsymbol_fn(genes, data, diabetes_abs, "prevsym", c("diabetic nephropathy", "DN"))

## End(Not run)

To prind the total number of abstracts in an S4 object of class Abstracts , its start and end

Description

It gives overview of the abstracts in an S4 object of class Abstracts.

Usage

printabs(object)

Arguments

Value

prints the total number of abstracts in an S4 object with additional information.

Author(s)

S.Ramachandran

Examples

## Not run: printabs(myabs)
## here myabs is an S4 object of class Abstracts.

function for text annotation using PubTator

Description

pubtator_function is used to extract specific information from an abstract like Gene, chemical, and diseases etc.

Usage

pubtator3_function(x)

Arguments

Details

pubtator_function allow users to get information about 'Gene', 'Chemical' and 'Disease' for given PMID. It uses online tool PubTator on R plateform. It also removes redundancy from the output. It takes one PMID at once, for multiple PMIDs user can use lapply() function.

Value

It returns a list object containing Gene, Chemical, Disease and PMID. The corresponding concept id numbers are joined by a '>' character. This is useful for further data mining

Author(s)

S.Ramachandran, Jyoti Rani

References

Wei, Chih-Hsuan, et al. "PubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge." Nucleic Acids Research (2024): gkae235.

Wei CH et. al., PubTator: a Web-based text mining tool for assisting Biocuration, Nucleic acids research, 2013, 41 (W1): W518-W522. doi: 10.1093/nar/gkt44

Wei CH et. al., Accelerating literature curation with text-mining tools: a case study of using PubTator to curate genes in PubMed abstracts, Database (Oxford), bas041, 2012

Wei CH et. al., PubTator: A PubMed-like interactive curation system for document triage and literature curation, in Proceedings of BioCreative 2012 workshop, Washington DC, USA, 145-150, 2012

Examples

## Not run: test = pubtator3_function(17922911)
## here pubtator_function() will extract the information from this given pmid.

function for text annotation using PubTator.Deprecated.

Description

pubtator_function is used to extract specific information from an abstract like Gene, chemical, and diseases etc.Deprecated.

Usage

pubtator_function(x)

Arguments

Details

pubtator_function allow users to get information about 'Gene', 'Chemical' and 'Disease' for given PMID. It uses online tool PubTator on R plateform. It also removes redundancy from the output. It takes one PMID at once, for multiple PMIDs user can use lapply() function.

Value

It returns a list object containing Gene, Chemical, Disease and PMID. The corresponding concept id numbers are joined by a '>' character. This is useful for further data mining

Author(s)

S.Ramachandran, Jyoti Rani

References

Wei CH et. al., PubTator: a Web-based text mining tool for assisting Biocuration, Nucleic acids research, 2013, 41 (W1): W518-W522. doi: 10.1093/nar/gkt44

Wei CH et. al., Accelerating literature curation with text-mining tools: a case study of using PubTator to curate genes in PubMed abstracts, Database (Oxford), bas041, 2012

Wei CH et. al., PubTator: A PubMed-like interactive curation system for document triage and literature curation, in Proceedings of BioCreative 2012 workshop, Washington DC, USA, 145-150, 2012

Examples

## Not run: test = pubtator_function(17922911)
## here pubtator_function() will extract the information from this given pmid.

function for text annotation using PubTator

Description

pubtator_function is used to extract specific information from an abstract like Gene, chemical, and diseases etc.

Usage

pubtator_function_JSON(x)

Arguments

Details

pubtator_function_JSON allow users to get information about 'Gene', 'Chemical' and 'Disease' for given PMID. It uses online tool PubTator on R plateform. It also removes redundancy from the output. It takes one PMID at once, for multiple PMIDs user can use lapply() function.

Value

It returns a list object containing Gene, Chemical, Disease and PMID. The corresponding concept id numbers are joined by a '>' character. This is useful for further data mining

Author(s)

S.Ramachandran, Jyoti Rani

References

Wei CH et. al., PubTator: a Web-based text mining tool for assisting Biocuration, Nucleic acids research, 2013, 41 (W1): W518-W522. doi: 10.1093/nar/gkt44

Wei CH et. al., Accelerating literature curation with text-mining tools: a case study of using PubTator to curate genes in PubMed abstracts, Database (Oxford), bas041, 2012

Wei CH et. al., PubTator: A PubMed-like interactive curation system for document triage and literature curation, in Proceedings of BioCreative 2012 workshop, Washington DC, USA, 145-150, 2012

See Also

pubtator_function()

Examples

## Not run: test = pubtator_function_JSON(17922911)
## here pubtator_function_JSON() will extract the information from 
## this given pmid.

Function to Convert Pubtator result from list into Table

Description

This function is used to collect the outputs of pubtator_function() after using lapply over multiple PMIDs. This function enables to convert it into table for easy reading and further analysis.

Usage

pubtator_result_list_to_table(x)

Arguments

Value

It returns table for pubtator_function output.

Author(s)

S.Ramachandran, Jyoti Rani

See Also

pubtator_function

Examples

## Not run: test = pubtator_result_list_to_table(x)
##here x is the output of pubtator_function

To read Abstracts

Description

readabs will automatically read the abstracts from the pubmed file.

Usage

readabs(x)

Arguments

Details

The saved file from a general pubmed search as text file is read via readabs().

Value

An S4 object of class "Abstracts", and a text file with tab delimited headers Journal, Abstract, PMID written with file name "newabs.txt".

Author(s)

S.Ramachandran

Examples

## Not run: readabs("pubmed_result.txt")
##here pubmed_result.txt is the text file of abstracts saved from PubMed.

To read Abstracts

Description

readabsnew will automatically read the abstracts from the pubmed text file.

Usage

readabsnew(x)

Arguments

Details

The saved file from a general pubmed search as text file is read via readabsnew().

Value

An S4 object of class "Abstracts" and a text file with tab delimited headers Journal, Abstract, PMID written with file name "newabs.txt".

Author(s)

S.Ramachandran

Examples

## Not run: readabsnew("pubmed_result.txt")
##here pubmed_result.txt is the text file of abstracts saved from PubMed.

To Initiate the Classes.

Description

ready will initiate the classes neccessary for other functions.

Usage

ready()

Details

This function is neccessary to initiate the classes which are needed for the implementation of other functions.

Value

classes

Author(s)

S. Ramachandran

Examples

## Not run: ready()

To remove abstracts for the query term.

Description

removeabswill remove the abstracts from a corpus for a given term.

Usage

removeabs(object, x, y)

Arguments

Details

removeabs() finds the abstracts for the given term and remove them from the large set of abstracts.A text file of file name "dataout.txt" will be written containing the number of abstracts removed.

Value

An S4 object of class Abstracts and a text file named "dataout.txt"

Author(s)

S.Ramachandran, Jyoti Rani

Examples

## Not run: removeabs(myabs, "atherosclerosis", TRUE)

removeabs To remove abstracts of a term from the data.

Description

removeabs This function will search for the abstracts containing the given term to remove them from the data.

Methods

signature(object = "Abstracts")

This method depicts its function, it will remove the abstracts from the data, and the number of abstracts removed will be written the text file named "dataout.txt"

To Search the abstracts of term(s) in a combination mode.

Description

searchabsL will search for abstracts for the given term(s). Multiple combinations are allowed.

Usage

searchabsL(object, yr, include, restrict, exclude)

Arguments

Details

In the arguments except for the object all other arguments have "NONE" as default. To export or write the result of searchabsL() we use sendabs() function.

Value

An object of class Abstracts satisfying the term combinations, In addition a text file named "out.txt" reporting the number of abstracts for given query term combinations.

Author(s)

S.Ramachandran

See Also

searchabsT

Examples

## Not run: searchabsL(myabs, include="term")
searchabsL(myabs, yr="2013")
searchabsL(myabs, restrict="term")
searchabsL(myabs, exclude="term")
searchabsL(myabs, include="term", exclude="term2")
## End(Not run)
## Here myabs is the object of class Abstracts containing data,
## "term" is the query term to be search.

Searching Abstracts

Description

searchabsL will automatically search the abstracts from the data for the given terms or their combination of several terms.

Methods

signature(object = "Abstracts")

searchabsL will search the abstracts for the given term or combinations of several terms. In this method the argument "include" uses the boolean operator 'OR' and is liberal whereas the 'restrict' and 'exclude' use the boolean operator 'AND' to specify additional filters. If the restriction to individual terms are desired then they can be individually searched and then the multiple abstracts can be combined using combineasb() function.

To Search Abstracts

Description

searchabsTIt is similar to searchabsL() but performs more specific search. It performs case sensitive search.

Usage

searchabsT(object, yr, include, restrict, exclude)

Arguments

Details

In the arguments except the object all arguments have "NONE" as default. Use sendabs() function to write the results in a tab delimited text file.

Value

An object of class Abstracts meeting the term and the term combinations. A text file reporting the number of abstracts for the query terms and their combinations is als written with the filename "out.txt".

Author(s)

Dr.S.Ramachandran

See Also

searchabsL

Examples

## Not run: searchabsT(myabs,yr="2013")
searchabsT(myabs,include="term")
searchabsT(myabs,restrict="term")
searchabsT(myabs,exclude="term")
searchabsT(myabs,yr="2013", include="term")
## End(Not run)
## Here myabs is an S4 object of class Abstracts containing the abstracts to search,
## "term" is the query term to be search. 

searchabsT Searching abstracts

Description

searchabsT will perform a specific search for the given term.

Methods

signature(object = "Abstracts")

It is similar to the searchabsL method, but it is more specific than searchabsL, it is case sensitive, however searchabsL is not.

To send abstracts

Description

sendabs will send the abstracts into a tab delimited text file with the fields Journal, Abstract, and PMID.

Usage

sendabs(object, x)

Arguments

Details

A general writing function for object of class 'Abstracts'

Value

A tab delimited text file with headers Journal, Abstract, PMID.

Author(s)

S.Ramachandran, Jyoti Rani

Examples

## Not run: sendabs(myabs,"myabs.txt")
## here myabs is the S4 object of class 'Abstracts' and 
## 'abs.txt' is the file where abstracts will be written.

To send the Data into a File

Description

sendabs will write the data of an object of class 'Abstracts' into a tab delimited text file with header Journal, Abstract, and PMID

Methods

signature(object = "Abstracts")

sendabs will send the data into a text file. It writes a tab delimited text file for PubMed abstracts containing Journal, Abstract, and PMID.

Removes extra spaces between words.

Description

space_quasher will automatically remove extra spaces between words. Therefore only one space between any pair of words will be left

Usage

space_quasher(x)

Arguments

Details

The extra spaces between words in sentences is quashed to one via space_quasher().

Value

Sentences(s) in which extra spaces between any pair of words are quashed to one.

Author(s)

S.Ramachandran

Examples

## Not run: space_quasher("I am       a ghostbuster. I have the tools    required to  hunt ghosts")
##here pubmed_result.txt is the text file of abstracts saved from PubMed.

To find sub-abstracts

Description

subabs will automatically extract the sub-abstracts from large set of abstracts.

Usage

subabs(object, start, end)

Arguments

Details

From a large number of asbtracts wish to extract a subset of abstracts into a separate object.

Value

An R object of class 'Abstracts' containing the extracted abstracts meeting a given range.

Author(s)

Jyoti Rani, S.Ramachandran

Examples

## Not run: subabs(myabs,1,5)
## Here 'myabs is an S4 object of class 'Abstracts', 
## 1 and 5 are the start and end respectively.

Getting subabstracts

Description

subabs subabs will extract the sub abstracts corresponding to a given range, from the whole data.

Methods

signature(object = "Abstracts")

From an S4 object of class 'Abstracts' the subabs function is able to extract the abstracts corresponding to a given range.

To make subsets of large corpus.

Description

It is used to divide the large corpus into a given range.

Usage

subsetabs(object, indices)

Arguments

Value

It returns an S4 obejct of extracted Abstracts.

Author(s)

S. Ramachandran.

Examples

## Not run: test = subsetabs(diabetesabs, 1:50)
## here we want to extract the Abstacts ranges from 1 to 50 
## from the large corpus of diabetes. 

To make subset of Abstracts.

Description

subsetabs is used to subset of Abstracts from the large corpus. Its output is used in other functions like currentabs_fn and previousabs_fn

Methods

signature(object = "Abstracts")

subsetabs will divide the large corpus into subset.

create Term Document Matrix for lsa analysis

Description

lsa package take "Term Document Matrix" as input, so it is needed to create a 'tdm' for Abstracts and tdm_for_lsa do the same as it find out the frequency of given term in each abstract and each abstract is considered as separate document. It prepares term document matrix of terms in the 'abstracts' corpus

Usage

tdm_for_lsa(object, y)

Arguments

Value

a Term Document Matrix (Numerical matrix) containing the raw frequencies of given terms in each abstract.

Author(s)

Jyoti Rani

Examples

## Not run: y = c("insulin", "inflammation", "obesity")
tdm_for_lsa(myabs,y)
## End(Not run)

To get information about gene from the UniProt.Deprecated.

Description

uniprotfun will access the UniProt data for a given gene as per HGNC approved gene symbols. Deprecated.

Usage

uniprotfun(y)

Arguments

Details

This function retrieves data from the UniProt. At present uniprotfun() works with only HGNC approved gene symbols.

Value

A text file written with filename as the 'query' name suffixed with .txt

Author(s)

S.Ramachandran

Examples

## Not run: uniprotfun("SIRT1")

To fetch the cluster for words

Description

whichcluster is used to get the cluster in which a given word (term) occurs.

Usage

whichcluster(clusterobject, y)

Arguments

Value

a list containing the number of cluster under which given term occurs.

Author(s)

S.Ramachandran

See Also

wordscluster

Examples

## Not run: test<-whichcluster(x, "diabetes")
## here x is an R object output form wordscluster function.
## and "diabetes" is the term for which cluster number is to be searched. 
## End(Not run)

Extracts the words associated (to the left and to the right) with a given word

Description

word_associationswill automatically extract associated words for a given word, namely the words immediately to teh left and to the right. The given word is usually in the middle except for those cases, where the given word occurrs either at the start or the end of the sentence.

Usage

word_associations(term, abs)

Arguments

Details

Certain words are qualified by authors in various ways. For example, physical therapy, gene therapy etc. This functions is useful in extracting these qualified words in the form of available associated words. Useful for preparing terms to be given in co_occurrence_fn (). There could be other uses also.

Value

Author(s)

S. Ramachandran

References

Rani J, Shah AB, Ramachandran S. pubmed.mineR: an R package with text-mining algorithms to analyse PubMed abstracts. J Biosci. 2015 Oct;40(4):671-82. PubMed PMID: 26564970.

See Also

Give_Sentences

Examples

## Not run: word_associations("therapy",myabs
##

Atomization of words

Description

word_atomizations will automatically break the whole text into words nd rank them according to their frequency of occurence.

Usage

word_atomizations(m)

Arguments

Details

word_atomizations() will break down the whole text into words after removing the extra white space, punctuation marks and very common english words.

Value

A text file containing words with their frequencies

Author(s)

S. Ramachandran, Jyoti Sharma

Examples

## Not run: word_atomizations(myabs)
## here myabs is the object containing abstracts.

To cluster the words

Description

wordscluster is used to cluster the words, using the levenshtein distance concept, which are coming together in combination with either 'prefixes' or 'suffixes' or other compound words. The first word, usually of lowest length, could be 'stemmed' word in many cases drastically so, is considered as representative for that cluster.

Usage

wordscluster(lower, upper)

Arguments

Details

This function is usefull for dampening the 'explotion' of words output from word_atomizations. This step enables easy examination of the terms.

Value

a list object of words clustered together and a text filenamed "resulttable.txt" with the columns cluster number, cluster size and representatives of clusters.

Note

The function may run faster when the lower limits are reduced but 'risks' producing plenty of 'decoy' situations. Their frequencies are very rare. Decoy situations: Some 'words' with part identity to other smaller words will runaway with smaller words. This event creates an unfavorable situation whereby the generated 'clusters' of words become difficult to interpret. This situation can be minimized by increasing the lower limit of word length, however at the cost of lowering computational speed. An example is: the word hypercholesterolemia runsaway with the smaller word 'lester' which could be another name.In this instance increasing the lower limit will be more usefull. Words longer than 30 characters are usually names of chemical comnpunds in IUPAC system of nomenclature.

Author(s)

S.Ramachandran, Jyoti Rani

See Also

whichcluster word_atomizations

Examples

## Not run: 
test=wordscluster(5, 10)
## here it will start making cluster of words of length with minimum of 5 characters 
## and maximum of 10 characters.  

## End(Not run)

To view the words in cluster

Description

wordsclusterview is used to view the words comes in cluster formed by wordscluster function.

Usage

wordsclusterview(words_cluster, all)

Arguments

Details

The first 5 words and 5 words near the median nd 5 words at the tail end are shown for clusters with more than 15 members. In case of cluster size less than 15, all the words are written in output.

Value

It returns a text file named word_cluster_view.txt

Author(s)

S.Ramachandran, Jyoti Rani

See Also

wordscluster

Examples

## Not run: test= wordsclusterview(cluster)
# here cluster is output from wordscluster
## End(Not run)

Gene atomization of xml abstracts.Deprecated.

Description

xmlgene_atomizations is used to fetch the list of genes from the xml abstracts.Deprecated.

Usage

xmlgene_atomizations(m)

Arguments

Value

a list containing genes from the text with their frquency of occurence.

Author(s)

S.Ramachandran, Jyoti Sharma

See Also

xmlreadabs

Examples

## Not run: test = xmlgene_atomizations(xmlabs)
## xmlabs is an S4 object of class Abstracts i.e. output of xmlreadabs

Gene atomization of xml abstracts.

Description

xmlgene_atomizations_new is used to fetch the list of genes from the xml abstracts

Usage

xmlgene_atomizations_new(m)

Arguments

Value

a list containing genes from the text with their frquency of occurrence.

Author(s)

S.Ramachandran, Jyoti Sharma

See Also

new_xmlreadabs

Examples

## Not run: test = xmlgene_atomizations(xmlabs)
## xmlabs is an S4 object of class Abstracts i.e. output of xmlreadabs

To read the abstracts from the PubMed saved in XML format.

Description

xmlreadabs is modified form of readabs as it reads the abstracts downloaded/saved in XML format from PubMed. This is helpful to give clean and better result after preprocessing i.e. word_atomizations, wordscluster etc.

Usage

xmlreadabs(file)

Arguments

Value

an S4 object of class Abstracts containing journals, abstracts and PMID.

Author(s)

S.Ramachandran

See Also

readabs

Examples

## Not run: xmlabs = xmlreadabs("pubmed_result.xml")
## here "pubmed_result.xml" is an xml format file downloaded from PubMed.

Word atomizations of abstracts from xml format.

Description

xmlword_atomizations is used to process the abstracts from PubMed in XML format.

Usage

xmlword_atomizations(m)

Arguments

Value

a list containing words from the text with their frequencies.

Note

xmlword_atomizations cannot work on output of readabs.

Author(s)

S. Ramachandran

See Also

xmlreadabs

Examples

## Not run: test = xmlword_atomizations(xmlabs)
## here xmlabs is an S4 object i.e. output of xmlreadabs