1.1.0

• A wide number of bug fixes to scRNA-seq and other pipelines. In particular, many memory limits were updated.
• An optional email can be sent upon pipeline completion.
• The RNA-seq pipeline can now produce a fuller report upon completion if you are performing differential expression.
• Sample merging in HiC works properly.
• GTF files are now handled more generically, which means that they no longer need to have "_gencode" and "_ensembl" in their path.
• WGBS: * Merging data from WGBS replicates is now an independent step so that dependent rules don't have to wait for successful completion of single CpG stats but can go ahead instead. * Filtering of differential methylation test results is now subject to two user-modifiable parameters minAbsDiff (default 0.2) and FDR (0.02) stored in defaults.yaml. * Metilene commandline parameters are now available in defaults.yaml. Defaults are used apart from requesting output intervals with any methylation difference (minMethDiff 0). * Additional diagnostic plots are generated - p value distribution before and after BH adjustment as well as a volcano plot. * Automatic reports are generated in every folder containing results of statistical analysis (single CpG stats, metilene DMR stats, user interval aggregate stats), as long as sample sheet is provided. * R sessionInfo() is now printed at the end of the statistical analysis.
• scRNAseq: * An extention to the pipeline now takes the processed csv file from Results folder as input and runs cell filtering with a range of total transcript thresholds using monocle and subsequently runs clustering, produces tsne visualizations, calculates top 2 and top10 markers per cluster and produces heatmap visualizations for these using monocle/seurat. If the skipRaceID flag is set to False (default), all of the above are also executed using RaceID. * Stats reports were implemented for RaceID and Monocle/Seurat so that folders Filtered_cells_RaceID and Filtered_cells_monocle now contain a Stats_report.html. * User can select a metric to maximize during cell filtering (cell_filter_metric, default: gene_universe). * For calculating median GPC, RaceID counts are multiplied by the TPC threshold applied (similar to 'downscaling' in RaceID2).
• all sample sheets now need to have a "name" and a "condition" column, that was not consistent before
  consistent --sampleSheet [FILE] cmdl option to invoke differential analysis mode (RNA-seq, ChIP-seq, ATAC-seq), --DE/--DB were dropped