RepliSeq

Analysis of Repli-Seq data to study DNA replication timing program in R.

Description:

An R package that features a set of functions to conduct Repli-seq data analysis.

We propose this package to analyze Repli-seq data within data.frames, which lets you easily complete your analysis with dplyr, calculate intersections with tidygenomics and plot your results with ggplot vizualizations.

RepliSeq functions include loading multi-fractions (from 2 to N fractions defined by your experiment dessign and your hardware capabilities) Repli-seq assay data as count matrices; rescaling profiles; smoothing profiles; calculting metrics such as Replication timing (calculated as the S50, on a scale from 0, early, to 1, late, which is the moment in S phase when a sequence has been replicated in 50% of cells replication timing) and URI (Under replication index got from two repliseq assays comparison).

Installation:

You can install this package by entering the following within R:

devtools::install_github("CL-CHEN-Lab/RepliSeq")

Requirements:

This package depends on:

• R version >= 3.4.4 (2018-03-15)

As mentionned in the DESCRIPTION, this packages imports:

• dplyr (>= 0.8.3)
• magrittr (>= 1.5)

In addition, the function writeBigWig() requires UCSC's wigToBigWig application to be installed on the computer. It can be found at encodeproject

Authors:

Sami EL HILALI and Chunlong CHEN (Institut Curie)

Don't hesitate to contact the authors or open an issue for a question or if you wish to see new features to be added to this package.

References:

Brison O., El-Hilali S., Azar, D., Koundrioukoff1 S., Schmidt M., Naehse-Kumpf V., Jaszczyszyn Y., Lachages A.M., Dutrillaux B., Thermes C., Debatisse M. and Chen C.L. (2019) Transcription-Mediated Organization of the Replication Initiation Program Across Large Genes Sets Up Common Fragile Sites Genome-Wide. Nat. Commun. 10, 5693

Chen C.L., Rappailles A., Duquenne L., Huvet M., Guilbaud G., Farinelli L, Audit B, d'Aubenton-Carafa Y., Arneodo A., Hyrien O. and Thermes C. (2010) Impact of replication timing on non-CpG and CpG substitution rates in mammalian genomes. Genome. Res. 20, 447-457.

Usage examples:

We propose an overview of some function usage. For extended documentation, please refer to the Vignette how-to-use.

readRS(path_data,fractions):

This function reads Repli-seq assays from multiple files (one file for one fraction) and outputs a dataframe from it.
It requires bedgraph inputs (see bedgraph spec) with a one line header but no other comments such as:

track type=bedGraph name=NT_chr22-s1 description=50kbprofile
chr22 0 50000 0
chr22 50000 100000 0

### args :
temp_paths <- c("../inst/extdata/NT_chr22-s1.bdg","../inst/extdata/NT_chr22-s2.bdg",
                "../inst/extdata/NT_chr22-s3.bdg","../inst/extdata/NT_chr22-s4.bdg",
                "../inst/extdata/NT_chr22-s5.bdg","../inst/extdata/NT_chr22-s6.bdg")
temp_fractions <- c("S1","S2","S3","S4","S5","S6")

### 2 fractions RepliSeq
# apply function :
RS_early <- readRS(temp_paths[1:2],temp_fractions[1:2])

### 6 fractions RepliSeq
# apply function :
RS_all <- readRS(temp_paths,temp_fractions)

### 1 fraction RepliSeq ( for S0 controls )
# apply function : 
RS_S0 <- readRS("../inst/extdata/NT_chr22-s0.bdg","S0")

### Result :

tail(RS_early)

chr	start	stop	S1	S2
chr22	51000000	51050000	12.392	4.929
chr22	51050000	51100000	11.604	5.887
chr22	51100000	51150000	12.568	7.941
chr22	51150000	51200000	9.853	5.887
chr22	51200000	51250000	2.584	1.711
chr22	51250000	51300000	0.000	0.000

calculateS50(rs_assay):

This function returns a dataframe composed of genomic coordinates associated with replication timing as an S50 value comprised within 0 (early replicating) and 1 (late replicating).

temp_rs <- data.frame(chr = rep("chr1",7),
                      start = seq(0,6000,1000),
                      stop = seq(1000,7000,1000),
                      S1 = c(0,0,0,1,1,1,1),
                      S2 = c(0,0,1,1,1,1,0),
                      S3 = c(0,1,1,1,1,0,0),
                      S4 = c(1,1,1,1,0,0,0))


temp_S50 <- RepliSeq::calculateS50(temp_rs)

# Result :

print(temp_S50)

chr	start	stop	S50
chr1	0	1000	0.875
chr1	1000	2000	0.750
chr1	2000	3000	0.625
chr1	3000	4000	0.500
chr1	4000	5000	0.375
chr1	5000	6000	0.250
chr1	6000	7000	0.125

calculateURI(rs_x, rs_y):

This function calculates URI between two Repli-seq assays. It returns a dataframe with the following columns:
chr,start,stop,sum_x,sum_y,mean_xy,URI

####### load second Repli-seq assay for comparison 
####### 6 fractions RepliSeq

# args :

aph_paths <- c("../inst/extdata/Aph_chr22-s1.bdg","../inst/extdata/Aph_chr22-s2.bdg",
               "../inst/extdata/Aph_chr22-s3.bdg","../inst/extdata/Aph_chr22-s4.bdg",
               "../inst/extdata/Aph_chr22-s5.bdg","../inst/extdata/Aph_chr22-s6.bdg")
aph_fractions <- temp_fractions

# read :

RS_aph_all <- readRS(aph_paths,aph_fractions)

# apply function :

aph_nt_uri <- calculateURI(RS_aph_all,RS_all)

# Result :

tail(aph_nt_uri)

chr	start	stop	sum_x	sum_y	mean_xy	URI
chr22	51000000	51050000	27.581	30.869	29.225	-1.37048107
chr22	51050000	51100000	30.556	31.274	30.915	-0.66372243
chr22	51100000	51150000	38.770	36.226	37.498	0.05718338
chr22	51150000	51200000	32.394	26.028	29.211	1.24529116
chr22	51200000	51250000	10.063	8.533	9.298	0.82273039
chr22	51250000	51300000	0.000	0.000	0.000	NaN