
These are two processed datasets comparing 4sU induced dropout in SLAM-seq versus TUC-seq and SLAM-seq in fixed cells compared to normal SLAM-seq. The zip files contain the full output from the processing pipeline (including the mapped reads, the scripts to run the pipeline and the output). The json file is required if you want to start from scratch. The *.tsv.gz files are the GRAND-SLAM output tables. To generate the GRAND-SLAM output yourself, first prepare the mouse genome. Then run the following command with the respective cit-files, prefixes (*.cit) and genome: gedi -e Slam -trim5p 15 -reads *.cit -genomic m.ens102 -prefix grandslam_t15/* -plot -D -modelall To generate the cit file you have to modify the first lines in start.bash to match the paths on your file system, and then run it. You can also start from scratch (i.e., the json file): Prepare the mouse genome and their rRNA sequence Run: gedi -e Pipeline -r parallel -j *.json rnaseq_mapping.sh report.sh grandslam.sh Software versions: gedi toolkit 1.0.5 GRAND-SLAM 2.0.7 STAR version 2.7.10b
| 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 |
