SECEDO (SinglE CEll Data tumOr clusterer)

SECEDO is able to cluster cells and perform variant calling based on information obtained from single-cell DNA sequencing. SECEDO takes as input BAM files containing the aligned data for each cell and provides as output a clustering of the cells and, optionally, VCF files pinpointing the changes relative to a reference genome.

SECEDO is descirbed in detail in the following paper: [Clustering cells based on single-cell DNA-sequencing data withultra-low coverage](coming soon)

Installation

Using bioconda

If you don't have conda/bioconda installed on your system yet, follow [these instructions](https://bioconda.github. io/user/install.html) to set it up. You can then install secedo using:

conda install -c conda-forge -c bioconda secedo

Building from source (Mac or Linux)

Prerequisites

• GNU GCC with C++17 (gcc-8.0.1 or higher), LLVM Clang (clang-7 or higher), or AppleClang
• cmake 3.13 or newer
• omp
• openblas

Clone the latest version of the code from the git repository:

git clone https://github.com/ratschlab/secedo.git

• sudo apt-get install libblas-dev (Linux) or brew install cmake gcc@9 libomp openblas (for Mac, for M1 Macs remove gcc@9)
• mkdir secedo/build; cd secedo/build
• cmake .. -DCMAKE_BUILD_TYPE=Release (Linux and M1 Macs) or cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_C_COMPILER=/usr/local/bin/gcc-9 -DCMAKE_CXX_COMPILER=/usr/local/bin/g++-9 .. (for Intel-based Macs)
• make -j
• ./tests

Usage examples

Creating the input pileup files

If you have a bunch of BAM files, the first step is to create a pileup (a file that contains all the sequenced bases for each locus) file. You can either split the BAM files by chromosome and then distribute the pileup creation to 23 jobs, or you can just go the easy way and pile up all the data in one go. This step doesn't require much RAM, as the pileup is streamed to disk while being created - 35GB should suffice even when processing 8000 cells at coverage 0.5x (~1.4TB of data):

./pileup -i <BAM_DIR> -o <OUT_DIR>/chromosome --chromosomes 1 --num_threads 20 --log_level=trace --min_base_quality 30 --max_coverage 1000

The command above will create a pileup for the first chromosome. If you ommit the --chromosome parameter, pileup will create 24 pileup files, one for each chromosome.

The pileup files are created in SECEDO's binary format (extension .bin) and in the samtools compatible textual format (extension .txt), which is useful for debugging and manual inspection.

Clustering and variant calling

./secedo -i <PILEUP_DIR> -o <OUT_DIR> --num_threads 20 --log_level=trace \
             --homozygous_filtered_rate=0.5 --seq_error_rate=0.01 \
             --reference_genome=OPTIONAL_REFERENCE_GENOME_FASTA \
             --max_coverage 1000 --min_cluster_size 500

This will run the clustering and variant calling on the pileup files available in PILEUP_DIR and write the clustering information to OUT_DIR/clustering. If a reference genome was provided via --reference_genome, the VCF files for each cluster will be written to OUT_DIR/cluster_<cluster_no>.vcf. Make sure that the chromosomes in your reference genome are ordered from 1,2,3, to 22, X, Y (some grch37 reference genomes come ordered lexicographically by chromosome!, e.g. 1, 10, 11, etc.).

You will need enough RAM to fit the pileups and a bit of extra - we were able to process 8K cells in 32GB of RAM, so this shouldn't be an issue.

Take a look at breast_cancer/variant_call.sh for inspiration on how to use SECEDO.

Evaluation

SECEDO was evaluated on synthetic and real datasets. This repository () contains all the evaluation results.

FAQ

Installation

1. Error at compilation: filesystem not available:

/secedo/./util/util.hpp:7:10: fatal error: filesystem: No such file or directory

Please make sure you have gcc > 8.0.1 or clang > 7. Filesystem is a relatively recent addition to the C++ standard (introduced in C++17, so earlier compilers don't have it at all, or have it part of experimental)