A method for determining a fraction of cell-free nucleic acids from a predetermined source in a biological sample, comprising: performing sequencing on cell-free nucleic acids contained in the biological sample, so as to obtain a sequencing result consisting of a plurality of sequencing reads; aligning the sequencing result to a reference sequence, so as to determine the number of sequencing reads falling into a predetermined window in the sequencing result, wherein the reference sequence is a reference genome sequence, wherein the predetermined window is obtained by sequential division of a predetermined chromosome of the reference genome sequence; and determining the fraction of the cell-free nucleic acids from the predetermined source in the biological sample based on the number of the sequencing reads falling into the predetermined window, wherein the fraction of the cell-free nucleic acids from the predetermined source in the biological sample is determined by a weight of each predetermined window, wherein the weight of each predetermined window is predetermined with training samples and is determined by at least one of a ridge regression statistical model and a neural network model, wherein the training sample is a peripheral blood sample with a known fraction of cell-free fetal nucleic acids from a pregnant woman, wherein the training sample is a peripheral blood sample with a known fraction of cell-free fetal nucleic acids from a pregnant woman with a normal male fetus, where the normal male fetus refers to a male fetus with normal chromosomes, wherein the biological sample is a peripheral blood sample, wherein the cell-free nucleic acid from the predetermined source is at least one selected from the followings: cell-free fetal nucleic acids in a peripheral blood sample that has been obtained from a pregnant woman; and cell-free maternal nucleic acids in a peripheral blood sample that has been obtained from a pregnant woman. performing sequencing on cell-free nucleic acids contained in the biological sample, so as to obtain a sequencing result consisting of a plurality of sequencing reads; aligning the sequencing result to a reference sequence, so as to determine the number of sequencing reads falling into a predetermined window in the sequencing result, wherein the reference sequence is a reference genome sequence, wherein the predetermined window is obtained by sequential division of a predetermined chromosome of the reference genome sequence; and wherein the reference sequence is a reference genome sequence, wherein the predetermined window is obtained by sequential division of a predetermined chromosome of the reference genome sequence; and determining the fraction of the cell-free nucleic acids from the predetermined source in the biological sample based on the number of the sequencing reads falling into the predetermined window, wherein the fraction of the cell-free nucleic acids from the predetermined source in the biological sample is determined by a weight of each predetermined window, wherein the weight of each predetermined window is predetermined with training samples and is determined by at least one of a ridge regression statistical model and a neural network model, wherein the training sample is a peripheral blood sample with a known fraction of cell-free fetal nucleic acids from a pregnant woman, wherein the training sample is a peripheral blood sample with a known fraction of cell-free fetal nucleic acids from a pregnant woman with a normal male fetus, where the normal male fetus refers to a male fetus with normal chromosomes, wherein the biological sample is a peripheral blood sample, wherein the cell-free nucleic acid from the predetermined source is at least one selected from the followings: cell-free fetal nucleic acids in a peripheral blood sample that has been obtained from a pregnant woman; and cell-free maternal nucleic acids in a peripheral blood sample that has been obtained from a pregnant woman. wherein the weight of each predetermined window is predetermined with training samples and is determined by at least one of a ridge regression statistical model and a neural network model, wherein the training sample is a peripheral blood sample with a known fraction of cell-free fetal nucleic acids from a pregnant woman, wherein the training sample is a peripheral blood sample with a known fraction of cell-free fetal nucleic acids from a pregnant woman with a normal male fetus, where the normal male fetus refers to a male fetus with normal chromosomes, wherein the biological sample is a peripheral blood sample, wherein the cell-free nucleic acid from the predetermined source is at least one selected from the followings: cell-free fetal nucleic acids in a peripheral blood sample that has been obtained from a pregnant woman; and cell-free maternal nucleic acids in a peripheral blood sample that has been obtained from a pregnant woman. cell-free fetal nucleic acids in a peripheral blood sample that has been obtained from a pregnant woman; and cell-free maternal nucleic acids in a peripheral blood sample that has been obtained from a pregnant woman.