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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MeFiT: merging and filtering tool for illumina paired-end reads for 16S rRNA amplicon sequencing
|
|---|---|
| Published in |
BMC Bioinformatics, December 2016
|
| DOI | 10.1186/s12859-016-1358-1 |
| Pubmed ID | |
| Authors |
Hardik I. Parikh, Vishal N. Koparde, Steven P. Bradley, Gregory A. Buck, Nihar U. Sheth |
| Abstract |
Recent advances in next-generation sequencing have revolutionized genomic research. 16S rRNA amplicon sequencing using paired-end sequencing on the MiSeq platform from Illumina, Inc., is being used to characterize the composition and dynamics of extremely complex/diverse microbial communities. For this analysis on the Illumina platform, merging and quality filtering of paired-end reads are essential first steps in data analysis to ensure the accuracy and reliability of downstream analysis. We have developed the Merging and Filtering Tool (MeFiT) to combine these pre-processing steps into one simple, intuitive pipeline. MeFiT invokes CASPER (context-aware scheme for paired-end reads) for merging paired-end reads and provides users the option to quality filter the reads using the traditional average Q-score metric or using a maximum expected error cut-off threshold. MeFiT provides an open-source solution that permits users to merge and filter paired end illumina reads. The tool has been implemented in python and the source-code is freely available at https://github.com/nisheth/MeFiT . |
X Demographics
The data shown below were collected from the profiles of 20 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 20% |
| France | 3 | 15% |
| Netherlands | 1 | 5% |
| Spain | 1 | 5% |
| Australia | 1 | 5% |
| United Kingdom | 1 | 5% |
| Austria | 1 | 5% |
| Unknown | 8 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 14 | 70% |
| Members of the public | 6 | 30% |
Mendeley readers
The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Estonia | 2 | 2% |
| Australia | 1 | 1% |
| Brazil | 1 | 1% |
| France | 1 | 1% |
| United Kingdom | 1 | 1% |
| India | 1 | 1% |
| Spain | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 79 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 25% |
| Student > Ph. D. Student | 12 | 14% |
| Student > Master | 12 | 14% |
| Other | 7 | 8% |
| Student > Bachelor | 5 | 6% |
| Other | 13 | 15% |
| Unknown | 17 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 33 | 38% |
| Biochemistry, Genetics and Molecular Biology | 18 | 20% |
| Computer Science | 4 | 5% |
| Environmental Science | 3 | 3% |
| Immunology and Microbiology | 3 | 3% |
| Other | 7 | 8% |
| Unknown | 20 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 21. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 July 2021.
All research outputs
#1,739,747
of 24,885,505 outputs
Outputs from BMC Bioinformatics
#324
of 7,601 outputs
Outputs of similar age
#34,671
of 427,734 outputs
Outputs of similar age from BMC Bioinformatics
#5
of 121 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,601 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 427,734 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 121 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.