Lesson · 40 min · Free
Make & CMake for Science
Lesson: Make & CMake for Science Make & CMake for Science Welcome to this crucial lesson on Make and CMake, essential tools for managing complex software projects, especially in computational genomics and bioinformatics.
Make & CMake for Science
Welcome to this crucial lesson on Make and CMake, essential tools for managing complex software projects, especially in computational genomics and bioinformatics. As you delve deeper into analyzing large biological datasets and developing custom algorithms, you'll inevitably encounter situations where your code consists of multiple files, depends on external libraries, and needs to be compiled efficiently. This is where Make and CMake become invaluable. At an upper-undergraduate level in pharmacy and biotech, you might not be writing full-fledged operating systems, but you will be working with C++ or Python scripts that perform computationally intensive tasks. These scripts often need to be compiled for performance or linked against specialized bioinformatics libraries. Manually compiling each file and linking them together can quickly become tedious, error-prone, and unsustainable as your project grows. Make and CMake automate this process, ensuring reproducibility and streamlining your development workflow. Make is a build automation tool that reads instructions from a file called a Makefile . A Makefile defines a set of rules that specify how to build certain targets (e.g., an executable program, a library, or even a documentation file) from source files. It intelligently determines which files need to be recompiled based on their modification times, saving significant time during development. For example, if you only change one source file, Make will only recompile that file and then relink the entire project, rather than recompiling everything from scratch. Let's look at a simple Makefile for a C++ program that simulates a basic drug-receptor interaction. Imagine you have two source files: main.cpp (containing the main program logic) and receptor.cpp (containing functions related to receptor binding calculations), and a header file receptor.h . # Simple Makefile for a C++ program # Define compiler and flags CXX = g++ CXXFLAGS = -Wall -std=c++11 # Define target executable TARGET = drug_sim # Define source files SRCS = main.cpp receptor.cpp # Define object files OBJS = $(SRCS:.cpp=.o) # Default target: build the executable all: $(TARGET) $(TARGET): $(OBJS) $(CXX) $(CXXFLAGS) $(OBJS) -o $(TARGET) # Rule to compile .cpp files into .o files %.o: %.cpp receptor.h $(CXX) $(CXXFLAGS) -c $ In this Makefile : CXX and CXXFLAGS define the compiler and compilation options. TARGET is the name of our final executable. SRCS lists our source code files. OBJS automatically generates the names of our object files ( .o ) from the source files. The all target is the default and depends on $(TARGET) . The rule $(TARGET): $(OBJS) specifies how to link the object files into the executable. The pattern rule %.o: %.cpp receptor.h tells Make how to compile any .cpp file into a .o file, also indicating a dependency on receptor.h . $< refers to the first prerequisite (the .cpp file), and $@ refers to the target (the .o file). The clean target removes all generated object files and the executable. To build the program, you simply navigate to the directory containing the Makefile and type make . To clean up, type make clean . While Make is powerful, writing complex Makefiles for large, cross-platform projects can become cumbersome. This is where CMake comes into play. CMake is a "meta-build system generator." Instead of directly building your project, CMake generates native build system files (like Makefiles for Unix-like systems, Visual Studio project files for Windows, or Xcode project files for macOS) from a higher-level configuration file called CMakeLists.txt . This abstraction makes your project buildable across different operating systems and compilers without needing to manually write different Makefiles for each platform. For bioinformatics and computational genomics, CMake is especially useful when you're integrating with large, complex libraries like HTSlib (for BAM/CRAM file manipulation), Boost, or custom C++ libraries developed by your lab. These libraries often provide their own CMakeLists.txt files, making integration seamless. Here's a basic CMakeLists.txt for the same drug-receptor simulation project: cmake_minimum_required(VERSION 3.10) # Specify minimum CMake version project(DrugSim CXX) # Define project name and language # Set C++ standard set(CMAKE_CXX_STANDARD 11) set(CMAKE_CXX_STANDARD_REQUIRED TRUE) # Add an executable target add_executable(drug_sim main.cpp receptor.cpp) # (Optional) If you had a header file in a separate include directory: # target_include_directories(drug_sim PUBLIC ${CMAKE_CURRENT_SOURCE_DIR}/include) # (Optional) If you needed to link against an external library: # find_package(SomeLibrary REQUIRED) # target_link_libraries(drug_sim PRIVATE SomeLibrary::SomeLibrary) To build a project using CMake: Create a build directory (it's good practice to build out-of-source): mkdir build && cd build Run CMake to generate the build system files: cmake .. ( .. refers to the parent directory where CMakeLists.txt resides) Run the native build tool (e.g., Make): make The beauty of CMake is that the cmake .. command will generate appropriate build files whether you're on Linux, Windows, or macOS, and then the subsequent make (or msbuild on Windows, or Xcode build on macOS) command will use those generated files to build your project.
Why Make & CMake for Bioinformatics & Computational Genomics?
In your field, you'll be working with tools and developing solutions that often involve: High-performance computing: C++ is frequently used for speed-critical components, requiring compilation. Complex dependencies: Bioinformatics tools often rely on specialized libraries for sequence alignment, variant calling, statistical analysis, etc. Reproducibility: Ensuring that your analysis pipelines can be built and run consistently by others (and yourself in the future) is paramount. Make and CMake enforce a structured build process. Collaboration: When working in a team, a standardized build system ensures everyone compiles the project in the same way. Cross-platform deployment: Bioinformatic tools need to run on various high-performance computing clusters and local machines, which may have different operating systems.
Key Takeaways
Make automates the compilation and linking of multi-file projects using Makefiles . Make intelligently recompiles only changed files, speeding up development. CMake is a meta-build system that generates native build files (like Makefiles ) from CMakeLists.txt . CMake simplifies cross-platform project management and dependency handling. Both tools are crucial for managing complex, high-performance C++/C projects in bioinformatics and computational genomics, ensuring reproducibility and efficient development.
Practice Exercise
Imagine you are developing a C++ program for predicting drug resistance mutations in bacterial genomes. Your project has three source files: main.cpp , mutation_analyzer.cpp , and genome_parser.cpp , and two header files: mutation_analyzer.h and genome_parser.h . Create a simple Makefile that compiles these files into an executable named resistance_predictor . Include rules for compiling individual .cpp files into .o files and a clean target. Then, consider how you would adapt this to a CMakeLists.txt file for cross-platform compatibility.
Watch the full lesson — free
This topic is part of Bioinformatics & Computational Genomics, a complete AI-narrated video course. Press play once and watch the entire lecture like a movie.
Start the course free →