PINTS is available on PyPI and bioconda, which means you can install PINTS easily with:

pip install pyPINTS

or

conda install bioconda::pypints

Alternatively, you can clone this repo to a local directory, then run the following command in that directory:

python setup.py install

PINTS can call peaks from either bigWig or BAM files. If you have signals for the forward and reverse strands in two separate bigWig files (path_to_pl.bw and path_to_mn.bw), you can use command like the following to get the peaks:

pints_caller --save-to output_dir --file-prefix output_prefix --bw-pl path_to_pl.bw --bw-mn path_to_mn.bw --thread 16

To call peaks from BAM files: you'll need to provide PINTS a path to the BAM file and what kind of experiment it was from. If it's from a standard protocol, like PROcap, then you can set --exp-type PROcap. Other supported experiments including GROcap/ CoPRO/ csRNAseq/ NETCAGE/ CAGE/ RAMPAGE/ STRIPEseq. For a comprehensive list of directly supported assays, please run

pints_caller --help

If the data was generated by other methods, you need to tell PINTS where it can find ends of RNAs you are interested in. For example, --exp-type R_5 tells the tool that:

1. this alignment is from a single-end library;
2. the tool should look at 5' of reads. Other supported values are R_3, R1_5, R1_3, R2_5, R2_3.

If reads represent the reverse complement of original RNAs, like PROseq, then you need to use --reverse-complement (not necessary for standard protocols).

One example for calling peaks from BAM file:

pints_caller --bam-file input.bam --save-to output_dir --file-prefix output_prefix --thread 16 --exp-type PROcap

We have prepared several case studies demonstrating steps from processing the raw fastq files to calling peaks/TREs for your reference.

• prefix _{SID}_divergent_peaks.bed: Divergent TREs;
• prefix _{SID}_bidirectional_peaks.bed: Bidirectional TREs (divergent convergent);
• prefix _{SID}_unidirectional_peaks.bed: Unidirectional TREs, maybe lncRNAs transcribed from enhancers (e-lncRNAs) as suggested here.

{SID} will be replaced with the number of samples that peaks are called from, if you only provide PINTS with one sample, then {SID} will be replaced with 1, if you try to use PINTS with three replicates (--bam-file A.bam B.bam C.bam), then {SID} for peaks identified from A.bam will be replaced with 1.

For divergent or bidirectional TREs, there will be 6 columns in the outputs:

1. Chromosome
2. Start site: 0-based
3. End site: 0-based
4. Confidence about the peak pair. Can be:
   • Stringent(qval), which means the two peaks on both forward and reverse strands are significant based on their q-values;
   • Stringent(pval), which means one peak is significant according to q-value while the other one is significant according to p-value;
   • Relaxed, which means only one peak is significant in the pair.
   • A combination of the three types above, because of overlap for nearby elements.
   • If epigenomic annotation is enabled by --epig-annotation <biosample>, then peaks that are less significant (--relaxed-fdr-target, default is 2*fdr_target), but overlap with epigenomic annotations from PINTS web server, will be listed with the confidence level: Marginal.
5. Major TSSs on the forward strand, if there are multiple major TSSs, they will be separated by comma ,
6. Major TSSs on the reverse strand, if there are multiple major TSSs, they will be separated by comma ,

For unidirectional TREs, there will be 9 columns in the output:

1. Chromosome
2. Start
3. End
4. Peak ID
5. Q-value
6. Strand
7. Read counts
8. Position of the summit TSS
9. Height of the summit

For all three types of TREs, if a valid biosample name for --epig-annotation is provided, then an additional column with epigenomic annotation for each TRE will show up in the final output.

• If you want to use BAM files as inputs:
  • --bam-file: input bam file(s);
  • --exp-type: Type of experiment. If the experiment is not listed as a choice, or you know the position of RNA ends on the reads and you want to override the defaults, you can specify:
    • R_5 (5' of the read for single-end lib),
    • R_3 (3' of the read for single-end lib),
    • R1_5 (5' of the read1 for paired-end lib),
    • R1_3 (3' of the read1 for paired-end lib),
    • R2_5 (5' of the read2 for paired-end lib),
    • or R2_3 (3' of the read2 for paired-end lib)
  • --reverse-complement: Set this switch if 1) exp-type is Rx_x and 2) reads in this library represent the reverse complement of RNAs, like PROseq;
  • --ct-bam: Bam file for input/control (optional);
• If you want to use bigwig files as inputs:
  • --bw-pl: Bigwig for signals on the forward strand;
  • --bw-mn: Bigwig for signals on the reverse strand;
  • --ct-bw-pl: Bigwig for input/control signals on the forward strand (optional);
  • --ct-bw-mn: Bigwig for input/control signals on the reverse strand (optional);
• --save-to: save peaks to this path (a folder), by default, current folder
• --file-prefix: prefix to all outputs

• --epig-annotation <biosample>: Use this option together with the name of the biosample that the library was derived from, for example K562; then epigenomic annotations will be downloaded from the PINTS web server and used for annotating and augmenting TREs identified by PINTS (for hg38 only);
• --relaxed-fdr-target <relaxed fdr>: In the presence of --epig-annotation, peaks that do not pass the original FDR cutoff but pass this relaxed cutoff and have support from DNase-seq and H3K27ac ChIP-seq will also be included in final outputs. By default, 2*fdr;
• --mapq-threshold <min mapq>: Minimum mapping quality, by default: 30 or None;
• --close-threshold <close distance>: Distance threshold for two peaks (on opposite strands) to be merged, by default: 300;
• --fdr-target <fdr>: FDR target for multiple testing, by default: 0.1;
• --chromosome-start-with <chromosome prefix>: Only keep reads mapped to chromosomes with this prefix, if it's set to None, then all reads will be analyzed;
• --thread <n thread>: Max number of threads the tool can create;
• --borrow-info-reps: Borrow information from reps to refine calling of divergent elements;
• --output-diagnostic-plot: Save diagnostic plots (independent filtering and pval dist) to local folder

More parameters can be seen by running pints_caller -h.

• pints_visualizer: Generate bigwig files for the inputs.
• pints_counter: Generate a count matrix for downstream usages (e.g. differential expression analysis).
• pints_boundary_extender: Extend peaks from summits.
• pints_normalizer: Normalize inputs.

Please submit an issue with any questions or if you experience any issues/bugs. If you use PINTS in your work, please cite: https://www.nature.com/articles/s41587-022-01211-7.