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X Demographics
Mendeley readers
Attention Score in Context
| Title |
cljam: a library for handling DNA sequence alignment/map (SAM) with parallel processing
|
|---|---|
| Published in |
Source Code for Biology and Medicine, August 2016
|
| DOI | 10.1186/s13029-016-0058-6 |
| Pubmed ID | |
| Authors |
Toshiki Takeuchi, Atsuo Yamada, Takashi Aoki, Kunihiro Nishimura |
| Abstract |
Next-generation sequencing can determine DNA bases and the results of sequence alignments are generally stored in files in the Sequence Alignment/Map (SAM) format and the compressed binary version (BAM) of it. SAMtools is a typical tool for dealing with files in the SAM/BAM format. SAMtools has various functions, including detection of variants, visualization of alignments, indexing, extraction of parts of the data and loci, and conversion of file formats. It is written in C and can execute fast. However, SAMtools requires an additional implementation to be used in parallel with, for example, OpenMP (Open Multi-Processing) libraries. For the accumulation of next-generation sequencing data, a simple parallelization program, which can support cloud and PC cluster environments, is required. We have developed cljam using the Clojure programming language, which simplifies parallel programming, to handle SAM/BAM data. Cljam can run in a Java runtime environment (e.g., Windows, Linux, Mac OS X) with Clojure. Cljam can process and analyze SAM/BAM files in parallel and at high speed. The execution time with cljam is almost the same as with SAMtools. The cljam code is written in Clojure and has fewer lines than other similar tools. |
X Demographics
The data shown below were collected from the profiles of 24 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 7 | 29% |
| United Kingdom | 2 | 8% |
| Canada | 2 | 8% |
| United States | 1 | 4% |
| Italy | 1 | 4% |
| Ecuador | 1 | 4% |
| China | 1 | 4% |
| Unknown | 9 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 20 | 83% |
| Scientists | 4 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 5% |
| France | 1 | 5% |
| Unknown | 19 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 29% |
| Student > Bachelor | 4 | 19% |
| Student > Ph. D. Student | 3 | 14% |
| Student > Master | 3 | 14% |
| Other | 2 | 10% |
| Other | 2 | 10% |
| Unknown | 1 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 7 | 33% |
| Biochemistry, Genetics and Molecular Biology | 5 | 24% |
| Medicine and Dentistry | 3 | 14% |
| Agricultural and Biological Sciences | 3 | 14% |
| Veterinary Science and Veterinary Medicine | 1 | 5% |
| Other | 2 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 15 December 2021.
All research outputs
#1,851,183
of 24,860,845 outputs
Outputs from Source Code for Biology and Medicine
#8
of 127 outputs
Outputs of similar age
#32,409
of 350,420 outputs
Outputs of similar age from Source Code for Biology and Medicine
#2
of 2 outputs
Altmetric has tracked 24,860,845 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done particularly well, scoring higher than 94% 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 350,420 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 90% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.