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cfDNAPro

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cfDNAPro specializes in standardized and robust cfDNA fragmentomic analysis

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# cfDNAPro <img src="vignettes/logo.png" width="150" align="right"/>

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## Official tutorials

This landing page aims to provide a quick start. For in-depth documentation, please visit: https://cfdnapro.readthedocs.io/en/latest/

## Declaration

cfDNAPro is designed for research only.

## Why cfDNAPro?

Unlike genomic DNA, cfDNA has specific fragmentation patterns. The ambiguous definition of "fragment length" by various alignment software is raising concerns: see page 9 footnote in SAM file format spec: https://samtools.github.io/hts-specs/SAMv1.pdf\
cell-free DNA data fragmentomic analysis requires single-molecule level resolution, emphasising the importance of accurate/unbiased feature extraction. The traditional tools built for solid tissue sequencing do not consider the specific properties of cfDNA sequencing data (e.g., cfDNAs are naturally fragmented with a modal fragment size of 167bp, and di-/tri-nucleotide peaks in the length distributions). Researchers might inadvertently extract the features using a sub-optimised method.

`cfDNAPro` is designed to resolve this issue and standardize the cfDNA fragmentomic analysis, complying with the existing building blocks in the bioconductor R ecosystem. **We wish cfDNAPro to provide a catalyst for further improvements in the implementation and development of cfDNA biomarkers and multi-modal AI for various health conditions.**

## Input

A paired-end sequencing bam file, with duplicates marked. (e.g., using the MarkDuplicates function from Picard).\
Please do not impose any filtering on the bam files; For example, do not filter by the proper-pairs flag.\
`cfDNAPro` filters the reads by following default criteria (You can toggle those criteria using parameters built-in `readBam()` function):\
(1) Reads mapping qualities less than 30 were discarded;\
(2) Reads must be paired. Of note, by default, cfDNAPro doesn’t impose filtration by “proper pair”;\
(3) No duplicate;\
(4) No secondary alignment;\
(5) No supplementary alignment;\
(6) No unmapped reads.

Note: remember to choose the correct `genome_label`, a parameter in `readBam()` function, based on the ref genome you used for alignment. At the moment, it supports three different ref genomes, hg19, hg38 and hg38-NCBI, For details see readBam() R documentation by typing `?readBam` in the R console or see source code:https://github.com/hw538/cfDNAPro/blob/master/R/readBam.R

## Output

`cfDNAPro` can extract (i.e., "quantify in a standandised and robust way") these features/bio-markers: - fragment length - fragment start/end/upstream/downstream motifs - copy number variation - single nucleotide mutation - more...

Feature extraction depends on essential data objects/R packages in the *Bioconductor* ecosystem, such as `Rsamtools`, `plyranges`, `GenomicAlignments`, `GenomeInfoDb` and `Biostrings`.\
Data engineering depends on packges in the *tidyverse* ecosystem, such as `dplyr`, and `stringr`.\
All plots depend on `ggplot2` R packge.

For issues/inquiries, please contact:\
Generic enquiry: **Nitzan Rosenfeld Lab admin mailbox**: bci-nrlab-admin\@qmul.ac.uk\
Fragment length, motif and CNV related questions: Haichao Wang: wanghaichao2014\@gmail.com\
SNV/SNP related questions: Paulius D. Mennea: paulius.mennea\@cruk.cam.ac.uk

## Installation

### Option 1 (recommended): Use Docker or Singularity:

Thanks zetian-jia for building the docker image,\
please refer to [github.com/zetian-jia/cfDNAPro_docker](https://github.com/zetian-jia/cfDNAPro_docker/)

#### Docker

``` bash
#Step 1: Pull the Docker Image
docker pull zetianjia/cfdnapro:1.7.3

#Step 2: Launch R inside the Container
docker run -it zetianjia/cfdnapro:1.7.3 R --no-save
```

#### Singularity

``` bash
#Step 1: Pull the Docker Image
singularity pull docker://zetianjia/cfdnapro:1.7.3

#Step 2: Launch R inside the Container
singularity exec -e cfdnapro_1.7.3.sif R --no-save
```

### Option 2: Your can try to install in your local R console:

In R console (tested using R 4.5.2 locally), you can try to install with following methods: 
```R
options(timeout = 3600)
if (!requireNamespace("devtools", quietly = TRUE)) {
  install.packages("devtools", repos = "https://cloud.r-project.org")
}

# Install cfDNAPro from GitHub
devtools::install_github("hw538/cfDNAPro", build_vignettes = FALSE, force = TRUE)

```

## Quick Start 1

Read bam file, return the fragment name (i.e. read name in bam file) and alignment coordinates in GRanges object in R. If needed, you can convert the GRanges into a dataframe and the fragment length is stored in the "width" column.

``` r

library(cfDNAPro)

# read bam file, do alignment curation
 frags <- readBam(bamfile = "/path/to/bamfile.bam")
# convert GRanges object to a dataframe in R
 frag_df <- as.data.frame(frags)

# You can calculate fragment length and motifs from the frags object (i.e., the output of readBam() function)

frag_length <- callLength(frags)
frag_motif <- callMotif(frags)
```

A screenshot of the output:

## Quick Start 2

Read in bam file, return the fragment length counts. A straightforward and frequent user case: calculate the fragment size of a bam file, use the following code:

``` r

# install cfDNAPro newest version

if (!require(devtools)) install.packages("devtools")
devtools::install_github("hw538/cfDNAPro", build_vignettes = FALSE)

# calculate insert size of a bam file

library(cfDNAPro)
 frag_lengths <- read_bam_insert_metrics(bamfile = "/path/to/bamfile.bam")
```

The returned dataframe contains two columns, i.e., "insert_size" (fragment length) and "All_Reads.fr_count" (the count of the fragment length). A screenshot of the output:\
<img src="https://github.com/hw538/cfDNAPro/assets/15274940/cba6709d-c49c-4c0d-8ae3-4ee7e82884f0" alt="image" width="298"/>

## News

### cfDNAPro paper is published on Genome Biology (May 2025)!

-   [Link to the paper](https://doi.org/10.1186/s13059-025-03607-5) \### cfDNAPro 1.7.3 (Jan 2025)
-   Updated various functions for mutational analysis \### cfDNAPro 1.7.2 (Jan 2025)
-   Improved various function for mutation annotation analysis etc \### cfDNAPro 1.7.1 (Jan 2025)
-   Improved the information and layout of this markdown quick start landing page \### cfDNAPro 1.7.1 (Aug 2024)
-   multiple updates \### cfDNAPro 1.7.1 (May 2023)
-   Resolved issues when building vignette
-   Various updates
-   Added/Updated readBam() functions \### cfDNAPro 1.5.4 (Nov 2022)
-   In addition to "bam" and "picard" files as the input, now we accept "cfdnapro" as input_type to various functions, this 'cfdnapro' input is exactly the output of `read_bam_insert_metrics` function in cfDNAPro package. It is a tsv file containing two columns, i.e., "insert_size" (fragment length) and "All_Reads.fr_count" (the count of the fragment length). \### cfDNAPro 1.5.3 (Oct 2022)
-   added support for hg38-NCBI version, i.e. GRCh38 \### cfDNAPro 0.99.3 (July 2021)
-   Modified vignette. \### cfDNAPro 0.99.2 (July 2021)
-   Modified vignette. \### cfDNAPro 0.99.1 (May 2021)
-   Added 'cfDNAPro' into the "watched tag". \### cfDNAPro 0.99.0 (May 2021)
-   Now cfDNAPro supports bam file as input for data characterisation.
-   Coding style improvements.
-   Documentation improvements.
-   Submitted to Bioconductor.

## Citation

Please cite this paper:

Wang, H., Mennea, P.D., Chan, Y.K.E., Cheng, Z. et al. A standardized framework for robust fragmentomic feature extraction from cell-free DNA sequencing data. Genome Biol 26, 141 (2025). https://doi.org/10.1186/s13059-025-03607-5

cfDNAPro

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