This is the README:
Fermi is a de novo assembler with a particular focus on assembling Illumina
short sequence reads from a mammal-sized genome. In addition to the role of a
typical assembler, fermi also aims to preserve heterozygotes which are often
collapsed by other assemblers. Its ultimate goal is to find a minimal set of
unitigs to represent all the information in raw reads.
Fermi follows the overlap-layout-consensus paradigm and uses the FM-DNA-index
(FMD-index) as the key data structure. It is inspired by the string graph
assembler (Simpson and Durbin, 2010 and 2012) and has a similar workflow.
As a typical de novo assembler, fermi tends to produce contigs with slightly
longer N50. However, the major weakness of fermi is the high misassembly rate.
Although fermi provides a tool to fix misassemblies by using paired-end reads
to achieve an accuracy comparable to other assemblers, this is not a favorable
solution.
Fermi is designed to be used on a multi-core Linux machine with large shared
memory. The easiest way to run fermi is to use the run-fermi.pl script. It
generates a Makefile. The actual assembly is done by invoking make. Premature
assembly processes can be resumed. Here is an example:
run-fermi.pl -dAPe ./fermi -p NA12878 -t16 -f18 reads*.fq.gz > NA12878.mak
make -f NA12878.mak -j16
This asks fermi to use 16 CPUs to assemble paired-end reads and will produce
raw unitigs in file "NA12878.ext.mag.gz". Graph cleaning and misassembly fixing
need to be applied manually. Future version of fermi will integrate these
steps into the run-fermi.pl script. It takes about a wall-clock week and a peak
memory of 85GB to assemble 35X human reads with 16 CPUs.
If you have any questions, ask me at
short sequence reads from a mammal-sized genome. In addition to the role of a
typical assembler, fermi also aims to preserve heterozygotes which are often
collapsed by other assemblers. Its ultimate goal is to find a minimal set of
unitigs to represent all the information in raw reads.
Fermi follows the overlap-layout-consensus paradigm and uses the FM-DNA-index
(FMD-index) as the key data structure. It is inspired by the string graph
assembler (Simpson and Durbin, 2010 and 2012) and has a similar workflow.
As a typical de novo assembler, fermi tends to produce contigs with slightly
longer N50. However, the major weakness of fermi is the high misassembly rate.
Although fermi provides a tool to fix misassemblies by using paired-end reads
to achieve an accuracy comparable to other assemblers, this is not a favorable
solution.
Fermi is designed to be used on a multi-core Linux machine with large shared
memory. The easiest way to run fermi is to use the run-fermi.pl script. It
generates a Makefile. The actual assembly is done by invoking make. Premature
assembly processes can be resumed. Here is an example:
run-fermi.pl -dAPe ./fermi -p NA12878 -t16 -f18 reads*.fq.gz > NA12878.mak
make -f NA12878.mak -j16
This asks fermi to use 16 CPUs to assemble paired-end reads and will produce
raw unitigs in file "NA12878.ext.mag.gz". Graph cleaning and misassembly fixing
need to be applied manually. Future version of fermi will integrate these
steps into the run-fermi.pl script. It takes about a wall-clock week and a peak
memory of 85GB to assemble 35X human reads with 16 CPUs.
If you have any questions, ask me at
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