| 107 | | * If you have human (hg38, hg19) and mouse (mm10, mm9) samples with biological replicates, you run [[https://github.com/ENCODE-DCC/atac-seq-pipeline|ENCODE ATAC-seq Pipeline]]. The pipeline takes fastq files, cleans and maps the reads, filters aligned reads and does peak calls. Here is the [[https://www.encodeproject.org/pipelines/ENCPL787FUN/|schema of the workflow]]. In addition, it does quality controls. Here is a [[http://barc.wi.mit.edu/education/hot_topics/ChIPseq_ATACseq_2021/qc.html | sample QC report]]. The steps below shows you how to run it on our Whitehead server. |
| | 107 | * If you have human (hg38, hg19) and mouse (mm10, mm9) samples with biological replicates, you run [[https://github.com/ENCODE-DCC/atac-seq-pipeline|ENCODE ATAC-seq Pipeline]]. The pipeline takes fastq files, cleans and maps the reads, filters aligned reads and does peak calls. Here is the [[https://www.encodeproject.org/pipelines/ENCPL787FUN/|schema of the workflow]]. In addition, it does quality controls. Here is a [[http://barc.wi.mit.edu/education/hot_topics/ChIPseq_ATACseq_2021/qc.html | sample QC report]]. The steps below shows you how to run it on our Whitehead server. Note: It only works on python2. |
