| 181 | Example usage: |
| 182 | |
| 183 | (1) If you have two conditions with at least three replicates: |
| 184 | |
| 185 | |
| 186 | {{{ |
| 187 | sbatch –partition=20 –job-name=NextF_Ribo –output=NextF_Ribo-%j.out –mem=300gb –nodes=1 –ntasks=1 \ |
| 188 | |
| 189 | –cpus-per-task=40 –wrap ” /nfs/BaRC_Public/apps/nextflow/nextflow run nf-core/riboseq \ |
| 190 | |
| 191 | -profile singularity \ |
| 192 | |
| 193 | –input samplesheet.csv \ |
| 194 | |
| 195 | –contrasts contrasts.csv \ |
| 196 | |
| 197 | –email 'your.email@wi.mit.edu' \ |
| 198 | |
| 199 | –multiqc_title 'multiQCReport' \ |
| 200 | |
| 201 | –fasta /nfs/genomes/human_hg38_dec13_no_random/fasta_whole_genome/hg38.fa \ |
| 202 | |
| 203 | –gtf /nfs/genomes/human_hg38_dec13_no_random/gtf/Homo_sapiens.GRCh38.106.canonical.gtf \ |
| 204 | |
| 205 | –outdir ./nextflow_RiboSeq ” |
| 206 | }}} |
| 207 | |
| 208 | |
| 209 | (2) If you have two conditions with less than three replicates: |
| 210 | |
| 211 | |
| 212 | {{{ |
| 213 | sbatch –partition=20 –job-name=NextF_Ribo –output=NextF_Ribo-%j.out –mem=300gb –nodes=1 –ntasks=1 \ |
| 214 | |
| 215 | –cpus-per-task=20 –wrap ” /nfs/BaRC_Public/apps/nextflow/nextflow run nf-core/riboseq \ |
| 216 | |
| 217 | -profile singularity \ |
| 218 | |
| 219 | –input samplesheet.csv \ |
| 220 | |
| 221 | –email 'your.email@wi.mit.edu' \ |
| 222 | |
| 223 | –multiqc_title 'multiQCReport' \ |
| 224 | |
| 225 | –fasta /nfs/genomes/human_hg38_dec13_no_random/fasta_whole_genome/hg38.fa \ |
| 226 | |
| 227 | –gtf /nfs/genomes/human_hg38_dec13_no_random/gtf/Homo_sapiens.GRCh38.106.canonical.gtf \ |
| 228 | |
| 229 | –outdir ./nextflow_RiboSeq” |
| 230 | |
| 231 | }}} |
| 232 | |
| 233 | Note: The difference between (1) and (2) is that the contrast file is not provided in (2). By doing this, we will skip the translational efficiency analysis conducted by the 'anota2seq' package. The reason to skip this step is that, when there are two conditions, the 'anota2seq' can only perform translational efficiency analysis if there are at least three replicates. However, you could calculate the translational efficiency by the ratio between Ribo-seq and RNA-seq signal. |
| 234 | |
| 235 | ---- |
| 236 | |
181 | | |
| 239 | Sample command using a configuration file with the settings we recommend for macs2: |
| 240 | |
| 241 | |
| 242 | {{{ |
| 243 | sbatch –partition=20 –job-name=NextF_ATACmcas2ConfigFull –output=NextF_ATAC_macs2ConfigFull-%j.out –mem=200gb –nodes=1 –ntasks=1 –cpus-per-task=20 –wrap ”/nfs/BaRC_Public/apps/nextflow/nextflow run nf-core/atacseq -profile singularity -c ./macs2Custom.config –input ./atacseq_sampleSheetFullFastq.csv –min_trimmed_reads 0 –aligner bowtie2 –keep_dups TRUE –narrow_peak TRUE –email 'username@wi.mit.edu' –genome mm10 –read_length 50 –outdir ./OutNextF_ATAC” |
| 244 | }}} |
| 245 | |
| 246 | |
| 247 | This is the content of the “macs2Custom.config” file: |
| 248 | |
| 249 | |
| 250 | {{{ |
| 251 | process { withName: '.*:MERGED_LIBRARY_CALL_ANNOTATE_PEAKS:MACS2_CALLPEAK' { ext.args = [ '–keep-dup auto', '–nomodel', '–shift -75', '–extsize 150', '–format BAM', '–bdg ', '–qvalue 0.01' ].join(' ').trim() } } |
| 252 | }}} |
| 253 | |