Table 1.
Properties of 4C-seq algorithms chosen for the benchmarking
| Algorithm | Analysis | Region | Input format | Source code | Language |
|---|---|---|---|---|---|
| 4C-ker | Differential | All | Tab-delimited count files | https://github.com/rr1859/R.4Cker | R |
| FourCSeq | Differential | All | Binary alignment/map (.bam) | https://bioconductor.org/packages/release/bioc/ html/FourCSeq.html | R |
| peakC | Single sample/ groups | Near-cis focus | Wiggle track format (.wig) | https://github.com/deWitLab/peakC | R |
| r3Cseq | Single sample | All | Binary alignment/map (.bam) | https://bioconductor.org/packages/release/bioc/html/ r3Cseq.html | R |
| fourSig | Single sample | All | Sequence alignment/map (.sam) | https://sourceforge.net/projects/foursig/ | R, Perl |
| Splinter | Single sample | No near-cis | Wiggle track format (.wig) | Publication supplement (Splinter et al., 2012) | R |
Note: Single-sample exclusive algorithms were combined with the differential expression algorithm DESeq2 to provide differential results.