MS-DIAL is an open-source software pipeline for data-independent MS/MS deconvolution in comprehensive metabolome analysis. It improves simultaneous identification and quantification of small molecules by mass spectral deconvolution. The software is designed for liquid chromatography tandem mass spectrometry (LC-MS/MS) and uses an enriched LipidBlast library to identify 1,023 lipid compounds from nine algal strains, highlighting their chemotaxonomic relationships. Data-independent acquisition (DIA) in LC-MS/MS provides more comprehensive untargeted molecular data acquisition. Unlike traditional data-dependent MS/MS, DIA can obtain all fragment ions for all precursors simultaneously, increasing molecular coverage and reducing false negatives. However, DIA spectra are prone to contamination due to a wider isolation window. MS-DIAL addresses this by mathematically deconvolving fragment ions to extract original spectra and re-associate precursor-fragment links. MS-DIAL uses a two-step process: precursor-peak spotting and MS/MS-level deconvolution. It converts raw data into 'Analysis Base File' (ABF) format for rapid retrieval. Precursor ion peaks are efficiently spotted using retention time and accurate mass. The MS² Dec algorithm is applied to each spot to deconvolute spectra in the respective precursor ion range. The algorithm extracts product spectra for each precursor peak, recovering precursor-product links through deconvolution. MS-DIAL also implements additional functions for untargeted metabolomics, such as peak alignment, filtering, and missing value interpolation. It supports various data formats, including mzML and major MS vendor formats. The software is intended for large-scale analyses, such as cohort studies, and processes data efficiently, with an average processing time of less than 1.2 minutes for 600 MB files. MS-DIAL was validated using sequential window acquisition of all theoretical mass spectra (SWATH) compared to traditional data-dependent acquisition (DDA). It successfully identified and quantified metabolites, including metoclopramide and norcocaine, with improved similarity scores after deconvolution. The software also performed lipidomic analysis of nine algal species, identifying 1,023 lipids, with SWATH acquisition covering >90% of them. MS-DIAL provides high efficacy and accuracy for metabolome coverage by resolving entangled MS/MS spectra in SWATH acquisition. It combines information from four sources: accurate mass, isotope ratios, retention time prediction, and MS/MS fragment matching, exceeding the two orthogonal parameters required by the Metabolomics Standards Initiative. The software is available on Windows and supports various data formats, making it a major step forward in solving the bottleneck in metabolomics: compound identification and annotation.MS-DIAL is an open-source software pipeline for data-independent MS/MS deconvolution in comprehensive metabolome analysis. It improves simultaneous identification and quantification of small molecules by mass spectral deconvolution. The software is designed for liquid chromatography tandem mass spectrometry (LC-MS/MS) and uses an enriched LipidBlast library to identify 1,023 lipid compounds from nine algal strains, highlighting their chemotaxonomic relationships. Data-independent acquisition (DIA) in LC-MS/MS provides more comprehensive untargeted molecular data acquisition. Unlike traditional data-dependent MS/MS, DIA can obtain all fragment ions for all precursors simultaneously, increasing molecular coverage and reducing false negatives. However, DIA spectra are prone to contamination due to a wider isolation window. MS-DIAL addresses this by mathematically deconvolving fragment ions to extract original spectra and re-associate precursor-fragment links. MS-DIAL uses a two-step process: precursor-peak spotting and MS/MS-level deconvolution. It converts raw data into 'Analysis Base File' (ABF) format for rapid retrieval. Precursor ion peaks are efficiently spotted using retention time and accurate mass. The MS² Dec algorithm is applied to each spot to deconvolute spectra in the respective precursor ion range. The algorithm extracts product spectra for each precursor peak, recovering precursor-product links through deconvolution. MS-DIAL also implements additional functions for untargeted metabolomics, such as peak alignment, filtering, and missing value interpolation. It supports various data formats, including mzML and major MS vendor formats. The software is intended for large-scale analyses, such as cohort studies, and processes data efficiently, with an average processing time of less than 1.2 minutes for 600 MB files. MS-DIAL was validated using sequential window acquisition of all theoretical mass spectra (SWATH) compared to traditional data-dependent acquisition (DDA). It successfully identified and quantified metabolites, including metoclopramide and norcocaine, with improved similarity scores after deconvolution. The software also performed lipidomic analysis of nine algal species, identifying 1,023 lipids, with SWATH acquisition covering >90% of them. MS-DIAL provides high efficacy and accuracy for metabolome coverage by resolving entangled MS/MS spectra in SWATH acquisition. It combines information from four sources: accurate mass, isotope ratios, retention time prediction, and MS/MS fragment matching, exceeding the two orthogonal parameters required by the Metabolomics Standards Initiative. The software is available on Windows and supports various data formats, making it a major step forward in solving the bottleneck in metabolomics: compound identification and annotation.