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Table of Contents

Requirements

Basic Requirements

Dip-C was tested on Python v2.7.13 (macOS and CentOS), with the following basic requirements:

  • NumPy (tested on v1.12.1)
  • SciPy (tested on v0.13.3)

Additional Requirements

Some Dip-C commands have additional requirements:

  • Read preprocessing for META: LIANTI (patch needed), which requires seqtk for paired-end reads
  • Read alignment: BWA (tested on v0.7.15), SAMtools (tested on v1.3), and Sambamba (tested on v0.6.3)
  • seg: pysam (tested on v0.11.1)
  • 3D reconstruction: nuc_dynamics (patch needed)
  • vis and other mmCIF scripts: PDBx Python Parser
  • mmCIF viewing: PyMol
  • align: rmsd

Patching LIANTI

For META read preprocessing, LIANTI needs a patch to replace the LIANTI adapters with the META ones:

  1. Download the LIANTI source code.
  2. Replace LIANTI's trim.c with Dip-C's patch/trim.c.
  3. Compile LIANTI.

Patching nuc_dynamics

For 3D reconstruction, nuc_dynamics needs a patch to (1) change the backbone energy function, (2) skip the removal of isolated contacts, and (3) output in the 3D Genome (3DG) format instead of the original PDB format (which has a 99,999-atom limit):

  1. Download the nuc_dynamics source code.
  2. Replace nuc_dynamics' nuc_dynamics.py with Dip-C's patch/nuc_dynamics.py.
  3. Compile nuc_dynamics.

The above was tested in May 2017. In Jun 2017, nuc_dynamics also changed its output format, along with other improvements. We have yet to update our patch.

Typical Workflow

Below is a typical workflow starting from paired-end META data (FASTQ), part of which is also included in dip-c.sh:

# read preprocessing and alignment
seqtk mergepe R1.fq.gz R2.fq.gz | lianti trim - | bwa mem -Cp hs37m.fa - | samtools view -uS | sambamba sort -o aln.bam /dev/stdin

# identify genomic contacts
dip-c seg -v snp.txt.gz aln.bam | gzip -c > phased.seg.gz
dip-c con phased.seg.gz | gzip -c > raw.con.gz
dip-c dedup raw.con.gz | gzip -c > dedup.con.gz
dip-c reg -p hf dedup.con.gz | gzip -c > reg.con.gz
#dip-c reg -p hf -e bad.reg -h hap.reg dedup.con.gz | gzip -c > reg.con.gz # deal with CNVs
dip-c clean reg.con.gz | gzip -c > clean.con.gz

# initial imputation of haplotypes
dip-c impute clean.con.gz | gzip -c > impute.con.gz

# further imputation and 3d reconstruction
con_to_ncc.sh impute.con.gz
nuc_dynamics.sh impute.ncc 0.1
dip-c impute3 -3 impute.3dg clean.con.gz | gzip -c > impute3.round1.con.gz
dip-c clean3 -c impute.con.gz impute.3dg > impute.clean.3dg

con_to_ncc.sh impute3.round1.con.gz
nuc_dynamics.sh impute3.round1.ncc 0.1
dip-c impute3 -3 impute3.round1.3dg clean.con.gz | gzip -c > impute3.round2.con.gz
dip-c clean3 -c impute3.round1.con.gz impute3.round1.3dg > impute3.round1.clean.3dg

con_to_ncc.sh impute3.round2.con.gz
nuc_dynamics.sh impute3.round2.ncc 0.1
dip-c impute3 -3 impute3.round2.3dg clean.con.gz | gzip -c > impute3.round3.con.gz
dip-c clean3 -c impute3.round2.con.gz impute3.round2.3dg > impute3.round2.clean.3dg

con_to_ncc.sh impute3.round3.con.gz
nuc_dynamics.sh impute3.round3.ncc 0.02
dip-c impute3 -3 impute3.round3.3dg clean.con.gz | gzip -c > impute3.round4.con.gz
dip-c clean3 -c impute3.round3.con.gz impute3.round3.3dg > impute3.round3.clean.3dg

con_to_ncc.sh impute3.round4.con.gz
nuc_dynamics.sh impute3.round4.ncc 0.02
dip-c clean3 -c impute3.round4.con.gz impute3.round4.3dg > impute3.round4.clean.3dg

# color by chromosome number and visualize as mmCIF
dip-c color -n color/hg19.chr.txt impute3.round4.clean.3dg | dip-c vis -c /dev/stdin impute3.round4.clean.3dg > impute3.round4.clean.n.cif