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What is MAnorm? -------------- MAnorm is a robust model for quantitative comparison of ChIP-Seq data sets of TFs (transcription factors) or epigenetic modifications and you can use it for: * Normalization of two ChIP-seq samples * Quantitative comparison (differential analysis) of two ChIP-seq samples * Evaluating the overlap enrichment of the protein binding sites(peaks) * Elucidating underlying mechanisms of cell-type specific gene regulation How MAnorm works? ---------------- MAnorm uses common peaks of two samples as a reference to build the rescaling model for normalization, which is based on the empirical assumption that if a chromatin-associated protein has a substantial number of peaks shared in two conditions, the binding at these common regions will tend to be determined by similar mechanisms, and thus should exhibit similar global binding intensities across samples. The observed differences on common peaks are presumed to reflect the scaling relationship of ChIP-Seq signals between two samples, which can be applied to all peaks. What do the inputs mean? ---------------- ### General **Experiment short name/Alias** * short name for you experiment to identify among the others **ChIP-Seq PE sample 1** * previously analyzed ChIP-Seq paired-end experiment to be used as Sample 1 **ChIP-Seq PE sample 2** * previously analyzed ChIP-Seq paired-end experiment to be used as Sample 2 **Genome** * Reference genome to be used for gene assigning ### Advanced **Reads shift size for sample 1** * This value is used to shift reads towards 3' direction to determine the precise binding site. Set as half of the fragment length. Default 100 **Reads shift size for sample 2** * This value is used to shift reads towards 5' direction to determine the precise binding site. Set as half of the fragment length. Default 100 **M-value (log2-ratio) cutoff** * Absolute M-value (log2-ratio) cutoff to define biased (differential binding) peaks. Default: 1.0 **P-value cutoff** * P-value cutoff to define biased peaks. Default: 0.01 **Window size** * Window size to count reads and calculate read densities. 2000 is recommended for sharp histone marks like H3K4me3 and H3K27ac, and 1000 for TFs or DNase-seq. Default: 2000

https://github.com/datirium/workflows.git

Path: workflows/manorm-pe.cwl

Branch/Commit ID: 17a4a68b20e0af656e09714c1f39fe761b518686

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/downsampled_alignment.cwl

Branch/Commit ID: 74647cc0f1abac4ee22950cfa89c44cf2ca3cffd

Comvert BAM to BEDPE and compress the output

https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/File-formats/bamtobedpe-gzip.cwl

Branch/Commit ID: bab73c25f2358d9d76ffff13eeb39a5ece38a795

https://github.com/ncbi/pgap.git

Path: task_types/tt_kmer_ref_compare_wnode.cwl

Branch/Commit ID: bb2f26dfe630179737ec2ff08a8614f1f47abcaf

https://github.com/uc-cdis/genomel_pipelines.git

Path: genomel/cwl/workflows/variant_calling/genotypegvcfs.cwl

Branch/Commit ID: 0f8f97e6173085500b688ca8c601b1ce966dce33

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/bam_to_trimmed_fastq_and_hisat_alignments.cwl

Branch/Commit ID: 2decd55996b912feb48be5db1b052aa3274ee405

https://github.com/ncbi/pgap.git

Path: task_types/tt_assm_assm_blastn_wnode.cwl

Branch/Commit ID: b12ec8c8e832151033b9e6c0a76a3c3df18d45da

https://github.com/ProteinsWebTeam/ebi-metagenomics-cwl.git

Path: tools/tRNA_selection.cwl

Branch/Commit ID: 9a72f76a5c8c874278205fcdeb93362a0d8a5152

https://github.com/CompEpigen/ChIPseq_workflows.git

Path: CWL/workflows/ChIPmentation.cwl

Branch/Commit ID: 8526687739a6802eeb08e97b27c20010225d5eb5

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/joint_genotype.cwl

Branch/Commit ID: 0b6e8fd8ead7644cf5398395b76af5cf4011686f