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Merge pull request #49 from dvklopfenstein/dvk
Summarize NIH citation data for a set of PMIDs
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# PubMed ID (PMID) Cite | ||
# PubMedj ID (PMID) Cite | ||
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[![Tweet](https://img.shields.io/twitter/url/http/shields.io.svg?style=social)](https://twitter.com/intent/tweet?text=Python%20library%20to%20download%20pubmed%20citation%20counts%20and%20data,%20given%20a%20PMID&url=https://github.com/dvklopfenstein/pmidcite&via=dvklopfenstein&hashtags=pubmed,pmid,citations,pubmed2cite,writingtips,scientificwriting) | ||
[![build](https://github.com/dvklopfenstein/pmidcite/actions/workflows/build.yml/badge.svg)](https://github.com/dvklopfenstein/pmidcite/actions/workflows/build.yml) | ||
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@@ -20,6 +20,7 @@ Contact: [email protected] | |
* [**1) Download citation counts and data for a research paper**](https://github.com/dvklopfenstein/pmidcite#1-download-citation-counts-and-data-for-a-research-paper) | ||
* [**2) Forward citation search**](https://github.com/dvklopfenstein/pmidcite#2-forward-citation-search): following a paper's *Cited by* links or *Forward snowballing* | ||
* [**3) Backward citation search**](https://github.com/dvklopfenstein/pmidcite#3-backward-citation-search): following the links to a paper's references or *Backward snowballing* | ||
* [**4) Summarize a group of citations**](https://github.com/dvklopfenstein/pmidcite#4-summarize-a-group-of-citations) | ||
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## 1) Download citation counts and data for a research paper | ||
```$ icite -H 26032263``` | ||
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@@ -56,6 +57,57 @@ Also known as following links to a paper's references or *Backward snowballing* | |
or | ||
```$ icite -H; icite 26032263 -r | sort -k6 -r``` | ||
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## 4) Summarize a group of citations | ||
* 4a) Examine a paper with PMID `30022098`. Print the column headers(`-H`): | ||
`icite -H 30022098` | ||
* 4b) Download the details about each paper(`-c`) that cites `30022098` into a file(`-o goatools_cites.txt`): | ||
`icite 30022098 -c -o goatools_cites.txt` | ||
* 4c) Summarize the overall performace of the 300+ citing papers contained in `goatools_cites.txt` | ||
`summarize_papers goatools_cites.txt -p TOP CIT CLI` | ||
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### 4a) Examine a paper with PMID `30022098`. Print the column headers(`-H`): | ||
``` | ||
$ icite -H 30022098 | ||
COL 2 3 4 5 6 7 8 9 10 au[11](authors) | ||
TYP PMID RP HAMCc % G YEAR cit cli ref au[00](authors) title | ||
TOP 30022098 R. .A..c 100 4 2018 318 1 23 au[14](D V Klopfenstein) GOATOOLS: A Python library for Gene Ontology analyses. | ||
``` | ||
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Paper with PMID `30022098` is cited by `318`(`cit`) other research papers and `1`(`cli`) clinical study. It has `23` references(`ref`). | ||
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### 4b) Download the details about each paper(`-c`) that cites `30022098` into a file(`-o goatools_cites.txt`): | ||
``` | ||
$ icite 30022098 -c -o goatools_cites.txt | ||
``` | ||
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The requested paper (PMID=`30022098`) is described in one one line in `goatools_cites.txt`: | ||
``` | ||
$ grep TOP goatools_cites.txt | ||
TOP 30022098 R. .A..c 100 4 2018 318 1 23 au[14](D V Klopfenstein) GOATOOLS: A Python library for Gene Ontology analyses. | ||
``` | ||
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The paper (PMID=`30022098`) is cited by 381(`CIT`) research papers plus 1(`CLI`) clinical study: | ||
``` | ||
$ grep CIT goatools_cites.txt | wc -l | ||
318 | ||
$ grep CLI goatools_cites.txt | wc -l | ||
1 | ||
``` | ||
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### 4c) Summarize all the papers in `goatools_cites.txt` | ||
**NEW FUNCTIONALITY; INPUT REQUESTED: What would you like to see?** [Open an issue](https://github.com/dvklopfenstein/pmidcite/issues) to comment. | ||
``` | ||
$ summarize_papers goatools_cites.txt -p TOP CIT CLI | ||
i=033.4% 4=003.4% 3=020.9% 2=021.9% 1=015.9% 0=004.4% 4 years:2018-2022 320 papers goatools_cites.txt | ||
``` | ||
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* Output is on one line so many files containing sets of PMIDs may be compared. TBD: Add multiline verbose option. | ||
* The groups are from newest(`i`) to top-performing(`4`), great(`3`), very good(`2`), and overlooked(`1` and `0`) | ||
* The percentages of papers in `goatools_citations.txt` in each group follow the group name | ||
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# PubMed vs Google Scholar | ||
<p align="center"> | ||
<img src="https://github.com/dvklopfenstein/pmidcite/raw/main/docs/images/Search_Features_GS_v_PubMed.png" alt="Google Scholar vs PubMed" width="600"/> | ||
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@@ -456,4 +508,4 @@ Fiorini N ... Lu Zhiyong | |
[email protected] | ||
https://orcid.org/0000-0003-0161-7603 | ||
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Copyright (C) 2019-present [pmidcite](https://dvklopfenstein.github.io/pmidcite/), DV Klopfenstein. All rights reserved. | ||
Copyright (C) 2019-present [pmidcite](https://dvklopfenstein.github.io/pmidcite/), DV Klopfenstein, PhD. All rights reserved. |
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from setuptools import setup | ||
# import versioneer | ||
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__copyright__ = 'Copyright (C) 2019, DV Klopfenstein, PhD. All rights reserved' | ||
__author__ = 'DV Klopfenstein, PhD' | ||
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NAME = 'pmidcite' | ||
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@@ -42,7 +44,7 @@ def get_long_description(): | |
setup( | ||
name=NAME, | ||
## version=versioneer.get_version(), | ||
version='0.0.41', | ||
version='0.0.42', | ||
author='DV Klopfenstein, PhD', | ||
author_email='[email protected]', | ||
## cmdclass=versioneer.get_cmdclass(), | ||
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@@ -55,6 +57,7 @@ def get_long_description(): | |
entry_points={ | ||
'console_scripts':[ | ||
'icite=pmidcite.scripts.icite:main', | ||
'summarize_papers=pmidcite.scripts.icite:summarize_papers', | ||
], | ||
}, | ||
# https://pypi.org/classifiers/ | ||
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'Topic :: Scientific/Engineering :: Information Analysis', | ||
], | ||
url='http://github.com/dvklopfenstein/pmidcite', | ||
description="Augment's a PubMed literature search with citation data from NIH-OCC's iCite.", | ||
description="Turbocharge a PubMed literature search using citation data from the NIH", | ||
# https://packaging.python.org/guides/making-a-pypi-friendly-readme/ | ||
long_description=get_long_description(), | ||
long_description_content_type='text/markdown', | ||
# install_requires=['docopt'], | ||
install_requires=['requests'], | ||
) | ||
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# Copyright (C) 2019, DV Klopfenstein, PhD. All rights reserved |
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"""Version of pmidcite project""" | ||
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__version__ = '0.0.41' | ||
__version__ = '0.0.42' |
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