Commit e4e81fc2 authored by Sarah Peter's avatar Sarah Peter

More formatting fixes...

parent bb8d1f45
......@@ -114,26 +114,28 @@
Atac-seq is similar to ChIP-seq an epigenomics NGS technique to identify open chromatin. Since the sequencing is in a paired-end mode (instead of single-end like we had in the previous data set from the tutorial) other parameters are needed for the alignment with `bowtie2`.
* `-1` indicates the forward read
* `-1` indicates the forward read,
* while `-2` indicates the reverse read.
`Genrich` has an advantage over `MACS2` since it is offering to do the necessary filtering steps during peak calling.
* `-e` allows to exclude chromosomes that are specified. In this case the mitochondrial chromosome (chrM).
* `-m` filters low quality reads.
* `-j` specifies that it has to run in the atac-seq mode.
* `-a` is the minimum AUC for a peak.
* `-r` removes PCR duplicates.
* `-k` creates a bedgraph-ish file for pileups.
2. Write the script into a Snakefile.
* Create a new directory `atac-seq` in your home directory for this (see the code below)
$ cd
$ mkdir atac-seq
$ cd atac-seq
* The peak caller `Genrich` is available from the `bioconda` conda channel
3. How can you improve the workflow in the context of data management? Think about data structures and log files.
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