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This workflow is a CWL version of a Python pipeline from BioWardrobe (Kartashov and Barski, 2015). It starts by extracting input FASTQ file (if it was compressed). Next step runs BowTie (Langmead et al., 2009) to perform alignment to a reference genome, resulting in an unsorted SAM file. The SAM file is then sorted and indexed with Samtools (Li et al., 2009) to obtain a BAM file and a BAI index. Next MACS2 (Zhang et al., 2008) is used to call peaks and to estimate fragment size. In the last few steps, the coverage by estimated fragments is calculated from the BAM file and is reported in bigWig format. The pipeline also reports statistics, such as read quality, peak number and base frequency, and other troubleshooting information using tools such as Fastx-toolkit and Bamtools.
cwltool, cwl-airflow, workflow, pipeline, cwl, ga4gh-challenge, cwl-workflow, biowardrobe, dream-challenge
cwltool, cwl-airflow, workflow, pipeline, cwl, ga4gh-challenge, cwl-workflow, biowardrobe, dream-challenge
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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