Release notes and changelog for ASAP versions.
Updated docker. Updated database. New input format: Seurat objects as .rds files.
| Tool | Version |
|---|---|
| java_stats | 1.0 |
| java | 11.0.6 |
| go_db | 2024-11-03 |
| ensembl_vertebrate | 113 |
| ensembl_genomes | 60 |
| hcao | |
| fbbt | |
| panglaodb | 2020 |
{
"name": "fabdavid/asap_run",
"tag": "v8",
"version": 8,
"call": "docker run #host_option --name #container_name --network=asap2_asap_network -e HOST_USER_ID=$(id -u) -e HOST_USER_GID=$(id -g) --entrypoint '/bin/sh' --rm -v /data/asap:/data/asap --env-file .env_asap_run #image_name -c"
}
{
"r": "4.4.3",
"hdf5r": "1.3.12",
"scran": "1.34.0",
"xvector": "0.46.0",
"sc3": "1.34.0",
"scater": "1.34.1",
"cluster": "2.1.8.1",
"limma_voom": "3.62.2",
"deseq2": "1.46.0",
"combat": "3.54.0",
"genefilter": "1.88.0",
"m3drop": "3.10.6",
"rhdf5": "2.51.2",
"seurat": "5.2.1",
"future.apply": "1.11.3",
"plotly": "4.10.4",
"statmod": "1.5.0",
"devtools": "2.4.5",
"datatable": "1.17.0",
"jsonlite": "1.9.1",
"rtsne": "0.17",
"r6": "2.6.1",
"sanon": "1.6",
"reticulate": "1.41.0.1",
"edger": "4.4.2",
"python3": "3.12.7",
"h5py": "3.12.1",
"leidenalg": "0.10.2",
"loompy": "3.0.7",
"matplotlib": "3.10.0",
"numba": "0.60.0",
"numpy": "2.0.2",
"pandas": "2.2.3",
"scikit_learn": "1.6.0",
"scipy": "1.15.0",
"umap_learn": "0.5.7",
"java": "17.0.14"
}
fabdavid/asap_run (v8)
{"tool_versions":{"java_stats":"1.0","java":"11.0.6","go_db":"2024-11-03","ensembl_vertebrate":"113","ensembl_genomes":"60","hcao":null,"fbbt":null,"panglaodb":"2020"},"asap_data_db_version":8,"docker_images":{"asap_run":{"name":"fabdavid/asap_run","tag":"v8","version":8,"call":"docker run #host_option --name #container_name --network=asap2_asap_network -e HOST_USER_ID=$(id -u) -e HOST_USER_GID=$(id -g) --entrypoint '/bin/sh' --rm -v /data/asap:/data/asap --env-file .env_asap_run #image_name -c"}},"time_call":"time -o '#output_dir/exec_run_details.log' -f 'U=%U,S=%S,E=%E,P=%P,X=%X,D=%D,M=%M,K=%K,t=%t,I=%I,O=%O,F=%F,R=%R,W=%W' ","exec_stdout":"#output_dir/exec.out","exec_stderr":"#output_dir/exec.err","hosts":{"localhost":{"nb_cores":80}},"asap_run_java":"ASAP-2.0.jar","types":{"dataset":{"description":"Matrix of values of any dimension and containing any type of data"},"int_matrix":{"description":"Count matrix (the matrix must contain only integer values)"},"num_matrix":{"description":"Numeric matrix (the matrix can contain integer or floating point values)"},"with_mdata_ercc":{"description":"Metadata for ERCC must exist."},"discrete_mdata":{"description":"Categorical metadata"},"numeric_mdata":{"description":"Numerical metadata"},"string_mdata":{"description":"Text metadata"},"col_mdata":{"description":"Cell metadata"},"row_mdata":{"description":"Gene metadata"},"mdata":{"description":"Metadata"}},"dashboards":{"std_runs":{"icon_class":"fa fa-bars"},"dim_reduction":{"icon_class":"scatter_plot-icon"}},"compliance":{"1":[{"name":"scFAIR","version":"7.1.0","source_schema_name":"scFAIR schema","description":"scFAIR validates single-cell transcriptomics datasets against the scFAIR cell metadata schema","source_url":"https://github.com/scFAIR/scFAIR/blob/main/schema/7.1.0/README.md","url":"https://sc-fair.org","compliant_icon":"scfair_badge_compliant.svg","not_compliant_icon":"scfair_badge_noncompliant.svg","if_compliant":["allow_public"]}]},"asap_data_db_name":"asap_data_v8"}
Updated docker. New single-cell specific pipeline using Seurat.
| Tool | Version |
|---|---|
| java_stats | 1.0 |
| java | 11.0.6 |
| go_db | 2020-Jan |
| ensembl_vertebrate | 104 |
| ensembl_genomes | 58 |
| hcao | |
| fbbt |
{
"name": "fabdavid/asap_run",
"tag": "v6",
"version": 6,
"call": "docker run #host_option --name #container_name --network=asap2_asap_network -e HOST_USER_ID=$(id -u) -e HOST_USER_GID=$(id -g) --entrypoint '/bin/sh' --rm -v /data/asap:/data/asap -v /srv/asap_run/srv:/srv #image_name -c"
}
{
"r": "4.3.1",
"hdf5r": "1.3.8",
"scran": "1.28.2",
"xvector": "0.40.0",
"sc3": "1.28.3",
"scater": "1.28.0",
"cluster": "2.1.4",
"limma_voom": "3.56.2",
"deseq2": "1.40.2",
"combat": "3.48.0",
"genefilter": "1.82.1",
"m3drop": "3.10.6",
"rhdf5": "2.45.2",
"seurat": "4.4.0",
"future.apply": "1.11.0",
"plotly": "4.10.2",
"statmod": "1.5.0",
"devtools": "2.4.5",
"datatable": "1.14.8",
"jsonlite": "1.8.7",
"rtsne": "0.16",
"bit64": "4.0.5",
"r6": "2.5.1",
"sanon": "1.6",
"reticulate": "1.34.0",
"edger": "3.42.4",
"python3": "3.11.6",
"h5py": "3.9.0",
"leidenalg": "0.10.1",
"loompy": "3.0.7",
"matplotlib": "3.6.3",
"numba": "0.57.1",
"numpy": "1.24.2",
"pandas": "1.5.3",
"scikit_learn": "1.3.1",
"scipy": "1.10.1",
"umap_learn": "0.5.4",
"java": "17.0.9"
}
fabdavid/asap_run (v6)
{"tool_versions":{"java_stats":"1.0","java":"11.0.6","go_db":"2020-Jan","ensembl_vertebrate":"104","ensembl_genomes":"58","hcao":null,"fbbt":null},"asap_data_db_version":6,"docker_images":{"asap_run":{"name":"fabdavid/asap_run","tag":"v6","version":6,"call":"docker run #host_option --name #container_name --network=asap2_asap_network -e HOST_USER_ID=$(id -u) -e HOST_USER_GID=$(id -g) --entrypoint '/bin/sh' --rm -v /data/asap:/data/asap -v /srv/asap_run/srv:/srv #image_name -c"}},"time_call":"time -o '#output_dir/exec_run_details.log' -f 'U=%U,S=%S,E=%E,P=%P,X=%X,D=%D,M=%M,K=%K,t=%t,I=%I,O=%O,F=%F,R=%R,W=%W' ","exec_stdout":"#output_dir/exec.out","exec_stderr":"#output_dir/exec.err","hosts":{"localhost":{"nb_cores":80}},"asap_run_java":"ASAP-2.0.jar","types":{"dataset":{"description":"Matrix of values of any dimension and containing any type of data"},"int_matrix":{"description":"Count matrix (the matrix must contain only integer values)"},"num_matrix":{"description":"Numeric matrix (the matrix can contain integer or floating point values)"},"with_mdata_ercc":{"description":"Metadata for ERCC must exist."},"discrete_mdata":{"description":"Categorical metadata"},"numeric_mdata":{"description":"Numerical metadata"},"string_mdata":{"description":"Text metadata"},"col_mdata":{"description":"Cell metadata"},"row_mdata":{"description":"Gene metadata"},"mdata":{"description":"Metadata"}},"dashboards":{"std_runs":{"icon_class":"fa fa-bars"},"dim_reduction":{"icon_class":"scatter_plot-icon"}},"compliance":{"1":[{"name":"scFAIR","version":"7.1.0","source_schema_name":"scFAIR schema","description":"scFAIR validates single-cell transcriptomics datasets against the scFAIR cell metadata schema","source_url":"https://github.com/scFAIR/scFAIR/blob/main/schema/7.1.0/README.md","url":"https://sc-fair.org","compliant_icon":"scfair_badge_compliant.svg","not_compliant_icon":"scfair_badge_noncompliant.svg","if_compliant":["allow_public"]}]},"asap_data_db_name":"asap_data_v6"}
Ensembl update.
| Tool | Version |
|---|---|
| java_stats | 1.0 |
| java | 11.0.6 |
| go_db | 2020-Jan |
| ensembl_vertebrate | 104 |
| ensembl_genomes | 58 |
| hcao | 2020-06-01 |
| fbbt | 2021-12-09 |
{
"name": "fabdavid/asap_run",
"tag": "v5",
"version": 5,
"call": "docker run #host_option --name #container_name --network=asap2_asap_network -e HOST_USER_ID=$(id -u) -e HOST_USER_GID=$(id -g) --entrypoint '/bin/sh' --rm -v /data/asap:/data/asap -v /srv/asap_run/srv:/srv #image_name -c"
}
{
"r": "3.6.2",
"hdf5r": "1.3.4",
"scran": "1.14.6",
"xvector": "0.26.0",
"sc3": "1.14.0",
"scater": "1.14.6",
"cluster": "2.1.0",
"limma_voom": "3.42.2",
"deseq2": "1.26.0",
"combat": "3.34.0",
"genefilter": "1.68.0",
"m3drop": "3.10.4",
"rhdf5": "2.31.11",
"seurat": "3.1.5",
"future.apply": "1.5.0",
"plotly": "4.9.2.1",
"statmod": "1.4.34",
"devtools": "2.3.0",
"datatable": "1.12.8",
"jsonlite": "1.6.1",
"rtsne": "0.15",
"r6": "2.4.1",
"sanon": "1.6",
"reticulate": "1.15",
"edger": "3.28.1",
"python3": "3.7.6",
"h5py": "3.1.0",
"leidenalg": "0.8.7",
"loompy": "3.0.6",
"louvain": "0.7.0",
"matplotlib": "3.3.2",
"numba": "0.53.1",
"numpy": "1.20.3",
"pandas": "1.2.4",
"scikit_learn": "0.24.2",
"scipy": "1.6.3",
"umap_learn": "0.5.1",
"java": "11.0.6"
}
fabdavid/asap_run (v5)
{"tool_versions":{"java_stats":"1.0","java":"11.0.6","go_db":"2020-Jan","ensembl_vertebrate":"104","ensembl_genomes":"58","hcao":"2020-06-01","fbbt":"2021-12-09"},"asap_data_db_version":6,"docker_images":{"asap_run":{"name":"fabdavid/asap_run","tag":"v5","version":5,"call":"docker run #host_option --name #container_name --network=asap2_asap_network -e HOST_USER_ID=$(id -u) -e HOST_USER_GID=$(id -g) --entrypoint '/bin/sh' --rm -v /data/asap:/data/asap -v /srv/asap_run/srv:/srv #image_name -c"}},"time_call":"time -o '#output_dir/exec_run_details.log' -f 'U=%U,S=%S,E=%E,P=%P,X=%X,D=%D,M=%M,K=%K,t=%t,I=%I,O=%O,F=%F,R=%R,W=%W' ","exec_stdout":"#output_dir/exec.out","exec_stderr":"#output_dir/exec.err","hosts":{"localhost":{"nb_cores":80}},"asap_run_java":"ASAP-2.0.jar","types":{"dataset":{"description":"Matrix of values of any dimension and containing any type of data"},"int_matrix":{"description":"Count matrix (the matrix must contain only integer values)"},"num_matrix":{"description":"Numeric matrix (the matrix can contain integer or floating point values)"},"with_mdata_ercc":{"description":"Metadata for ERCC must exist."},"discrete_mdata":{"description":"Categorical metadata"},"numeric_mdata":{"description":"Numerical metadata"},"string_mdata":{"description":"Text metadata"},"col_mdata":{"description":"Cell metadata"},"row_mdata":{"description":"Gene metadata"},"mdata":{"description":"Metadata"}},"dashboards":{"std_runs":{"icon_class":"fa fa-bars"},"dim_reduction":{"icon_class":"scatter_plot-icon"}},"compliance":{"1":[{"name":"scFAIR","version":"7.1.0","source_schema_name":"scFAIR schema","description":"scFAIR validates single-cell transcriptomics datasets against the scFAIR cell metadata schema","source_url":"https://github.com/scFAIR/scFAIR/blob/main/schema/7.1.0/README.md","url":"https://sc-fair.org","compliant_icon":"scfair_badge_compliant.svg","not_compliant_icon":"scfair_badge_noncompliant.svg","if_compliant":["allow_public"]}]},"asap_data_db_name":"asap_data_v6"}
Optimized asap_run docker, migration of v.2.7 python scripts to v.3.0. Updated Ensembl data in asap_data database.
| Tool | Version |
|---|---|
| java_stats | 1.0 |
| h5py | 2.10.0 |
| scikits_learn | 0.22.1 |
| numpy | 1.18.1 |
| scipy | 1.4.1 |
| java | 11.0.6 |
| python | 3.7.6 |
| stats | 3.6.0 |
| sc3 | 1.14.0 |
| cluster | 2.1.0 |
| rtsne | 0.15 |
| limma_voom | 3.42.2 |
| deseq2 | 1.26.0 |
| umap-learn | 0.3.10 |
| datatable | 1.12.8 |
| go_db | 2020-Jan |
| ensembl_vertebrate | 101 |
| ensembl_genomes | 58 |
{
"name": "fabdavid/asap_run",
"tag": "v5",
"version": 5,
"call": "docker run #host_option --name #container_name --network=asap2_asap_network -e HOST_USER_ID=$(id -u) -e HOST_USER_GID=$(id -g) --entrypoint '/bin/sh' --rm -v /data/asap:/data/asap -v /srv/asap_run/srv:/srv #image_name -c"
}
{
"r": "3.6.2",
"hdf5r": "1.3.4",
"scran": "1.14.6",
"xvector": "0.26.0",
"sc3": "1.14.0",
"scater": "1.14.6",
"cluster": "2.1.0",
"limma_voom": "3.42.2",
"deseq2": "1.26.0",
"combat": "3.34.0",
"genefilter": "1.68.0",
"m3drop": "3.10.4",
"rhdf5": "2.31.11",
"seurat": "3.1.5",
"future.apply": "1.5.0",
"plotly": "4.9.2.1",
"statmod": "1.4.34",
"devtools": "2.3.0",
"datatable": "1.12.8",
"jsonlite": "1.6.1",
"rtsne": "0.15",
"r6": "2.4.1",
"sanon": "1.6",
"reticulate": "1.15",
"edger": "3.28.1",
"python3": "3.7.6",
"h5py": "3.1.0",
"leidenalg": "0.8.7",
"loompy": "3.0.6",
"louvain": "0.7.0",
"matplotlib": "3.3.2",
"numba": "0.53.1",
"numpy": "1.20.3",
"pandas": "1.2.4",
"scikit_learn": "0.24.2",
"scipy": "1.6.3",
"umap_learn": "0.5.1",
"java": "11.0.6"
}
fabdavid/asap_run (v5)
{"tool_versions":{"java_stats":"1.0","h5py":"2.10.0","scikits_learn":"0.22.1","numpy":"1.18.1","scipy":"1.4.1","java":"11.0.6","python":"3.7.6","stats":"3.6.0","sc3":"1.14.0","cluster":"2.1.0","rtsne":"0.15","limma_voom":"3.42.2","deseq2":"1.26.0","umap-learn":"0.3.10","datatable":"1.12.8","go_db":"2020-Jan","ensembl_vertebrate":"101","ensembl_genomes":"58"},"asap_data_db_version":5,"docker_images":{"asap_run":{"name":"fabdavid/asap_run","tag":"v5","version":5,"call":"docker run #host_option --name #container_name --network=asap2_asap_network -e HOST_USER_ID=$(id -u) -e HOST_USER_GID=$(id -g) --entrypoint '/bin/sh' --rm -v /data/asap:/data/asap -v /srv/asap_run/srv:/srv #image_name -c"}},"time_call":"time -o '#output_dir/exec_run_details.log' -f 'U=%U,S=%S,E=%E,P=%P,X=%X,D=%D,M=%M,K=%K,t=%t,I=%I,O=%O,F=%F,R=%R,W=%W' ","exec_stdout":"#output_dir/exec.out","exec_stderr":"#output_dir/exec.err","hosts":{"localhost":{"nb_cores":80}},"asap_run_java":"ASAP-2.0.jar","types":{"dataset":{"description":"Matrix of values of any dimension and containing any type of data"},"int_matrix":{"description":"Count matrix (the matrix must contain only integer values)"},"num_matrix":{"description":"Numeric matrix (the matrix can contain integer or floating point values)"},"with_mdata_ercc":{"description":"Metadata for ERCC must exist."},"discrete_mdata":{"description":"Categorical metadata"},"numeric_mdata":{"description":"Numerical metadata"},"string_mdata":{"description":"Text metadata"},"col_mdata":{"description":"Cell metadata"},"row_mdata":{"description":"Gene metadata"},"mdata":{"description":"Metadata"}},"dashboards":{"std_runs":{"icon_class":"fa fa-bars"},"dim_reduction":{"icon_class":"scatter_plot-icon"}},"compliance":{"1":[{"name":"scFAIR","version":"7.1.0","source_schema_name":"scFAIR schema","description":"scFAIR validates single-cell transcriptomics datasets against the scFAIR cell metadata schema","source_url":"https://github.com/scFAIR/scFAIR/blob/main/schema/7.1.0/README.md","url":"https://sc-fair.org","compliant_icon":"scfair_badge_compliant.svg","not_compliant_icon":"scfair_badge_noncompliant.svg","if_compliant":["allow_public"]}]},"asap_data_db_name":"asap_data_v5"}
New version with docker, LOOM, HCA binding and more.
| Tool | Version |
|---|---|
| java_stats | 1.0 |
| sclvm | 0.99.3 |
| gpy | 1.5.6 |
| limix | 0.8.0.dev0 |
| h5py | 2.10.0 |
| scikits_learn | 0.21.3 |
| numpy | 1.17.2 |
| scipy | 1.3.1 |
| java | 1.8.0_111 |
| python | 2.7.5 |
| combat | 3.30.1 |
| stats | 3.5.0 |
| sc3 | 1.10.1 |
| mds | 7.3-50 |
| pam | 2.0.7-1 |
| zifa | 0.1 |
| rtsne | 0.15 |
| pagoda_scde | 2.10.1 |
| limma_voom | 3.38.3 |
| edger | 3.24.3 |
| deseq2 | 1.22.2 |
| scan_upc | 2.18.0 |
| datatable | 1.12.0 |
| go_db | 2017-Jun |
| kegg_db | 2016-Nov |
| gsea_db | 2016-Nov |
| gene_atlas_db | 2016-Nov |
| ensembl_vertebrate | 97 |
| ensembl_genomes | 58 |
{
"name": "fabdavid/asap_run",
"tag": "v4",
"version": 4,
"call": "docker run #host_option --name #container_name --network=asap2_asap_network -e HOST_USER_ID=$(id -u) -e HOST_USER_GID=$(id -g) --entrypoint '/bin/sh' --rm -v /data/asap:/data/asap #image_name -c"
}
{
"r": "3.5.0",
"hdf5r": "1.0.1",
"xvector": "0.22.0",
"sc3": "1.10.1",
"scater": "1.10.1",
"limma_voom": "3.38.3",
"deseq2": "1.22.2",
"combat": "3.30.1",
"genefilter": "1.64.0",
"m3drop": "3.10.3",
"rhdf5": "2.31.3",
"seurat": "3.1.3",
"future.apply": "1.3.0",
"plotly": "4.8.0",
"statmod": "1.4.30",
"devtools": "2.0.1",
"datatable": "1.12.0",
"jsonlite": "1.6",
"rtsne": "0.15",
"r6": "2.4.0",
"reticulate": "1.11.1",
"python": "2.7.16",
"h5py": "2.9.0",
"leidenalg": "0.7.0",
"numba": "0.42.0",
"numpy": "1.16.2",
"scikit_learn": "0.20.3",
"scipy": "1.2.1",
"umap_learn": "0.3.7",
"java": "11.0.2"
}
fabdavid/asap_run (v4)
{"tool_versions":{"java_stats":"1.0","sclvm":"0.99.3","gpy":"1.5.6","limix":"0.8.0.dev0","h5py":"2.10.0","scikits_learn":"0.21.3","numpy":"1.17.2","scipy":"1.3.1","java":"1.8.0_111","python":"2.7.5","combat":"3.30.1","stats":"3.5.0","sc3":"1.10.1","mds":"7.3-50","pam":"2.0.7-1","zifa":"0.1","rtsne":"0.15","pagoda_scde":"2.10.1","limma_voom":"3.38.3","edger":"3.24.3","deseq2":"1.22.2","scan_upc":"2.18.0","datatable":"1.12.0","go_db":"2017-Jun","kegg_db":"2016-Nov","gsea_db":"2016-Nov","gene_atlas_db":"2016-Nov","ensembl_vertebrate":"97","ensembl_genomes":"58"},"asap_data_db_version":4,"docker_images":{"asap_run":{"name":"fabdavid/asap_run","tag":"v4","version":4,"call":"docker run #host_option --name #container_name --network=asap2_asap_network -e HOST_USER_ID=$(id -u) -e HOST_USER_GID=$(id -g) --entrypoint '/bin/sh' --rm -v /data/asap:/data/asap #image_name -c"}},"time_call":"time -o '#output_dir/exec_run_details.log' -f 'U=%U,S=%S,E=%E,P=%P,X=%X,D=%D,M=%M,K=%K,t=%t,I=%I,O=%O,F=%F,R=%R,W=%W' ","exec_stdout":"#output_dir/exec.out","exec_stderr":"#output_dir/exec.err","hosts":{"localhost":{"nb_cores":80}},"asap_run_java":"ASAP-2.0.jar","types":{"dataset":{"description":"Matrix of values of any dimension and containing any type of data"},"int_matrix":{"description":"Count matrix (the matrix must contain only integer values)"},"num_matrix":{"description":"Numeric matrix (the matrix can contain integer or floating point values)"},"with_mdata_ercc":{"description":"Metadata for ERCC must exist."},"discrete_mdata":{"description":"Categorical metadata"},"numeric_mdata":{"description":"Numerical metadata"},"string_mdata":{"description":"Text metadata"},"col_mdata":{"description":"Cell metadata"},"row_mdata":{"description":"Gene metadata"},"mdata":{"description":"Metadata"}},"dashboards":{"std_runs":{"icon_class":"fa fa-bars"},"dim_reduction":{"icon_class":"scatter_plot-icon"}},"compliance":{"1":[{"name":"scFAIR","version":"7.1.0","source_schema_name":"scFAIR schema","description":"scFAIR validates single-cell transcriptomics datasets against the scFAIR cell metadata schema","source_url":"https://github.com/scFAIR/scFAIR/blob/main/schema/7.1.0/README.md","url":"https://sc-fair.org","compliant_icon":"scfair_badge_compliant.svg","not_compliant_icon":"scfair_badge_noncompliant.svg","if_compliant":["allow_public"]}]},"asap_data_db_name":"asap_data_v4"}
New version including: -New trajectory visualization (Monocle) -Project sharing -Searchable list of projects / analyses
| Tool | Version |
|---|---|
| java_stats | 1.0 |
| sclvm | 0.99.3 |
| gpy | 1.5.6 |
| limix | 0.8.0.dev0 |
| h5py | 2.6.0 |
| scikits_learn | 0.18.1 |
| numpy | 1.11.2 |
| scipy | 0.18.1 |
| java | 1.8.0_111 |
| python | 2.7.5 |
| combat | 3.24.4 |
| stats | 3.3.1 |
| sc3 | 1.3.11 |
| mds | 7.3-45 |
| pam | 2.0.6 |
| zifa | 0.1 |
| rtsne | 0.13 |
| pagoda_scde | 2.5.0 |
| limma_voom | 3.32.2 |
| edger | 3.18.1 |
| deseq2 | 1.16.1 |
| scan_upc | 2.18.0 |
| datatable | 1.10.4 |
| go_db | 2017-Jun |
| kegg_db | 2016-Nov |
| gsea_db | 2016-Nov |
| gene_atlas_db | 2016-Nov |
| ensembl | 2017-Mar |
{"tool_versions":{"java_stats":"1.0","sclvm":"0.99.3","gpy":"1.5.6","limix":"0.8.0.dev0","h5py":"2.6.0","scikits_learn":"0.18.1","numpy":"1.11.2","scipy":"0.18.1","java":"1.8.0_111","python":"2.7.5","combat":"3.24.4","stats":"3.3.1","sc3":"1.3.11","mds":"7.3-45","pam":"2.0.6","zifa":"0.1","rtsne":"0.13","pagoda_scde":"2.5.0","limma_voom":"3.32.2","edger":"3.18.1","deseq2":"1.16.1","scan_upc":"2.18.0","datatable":"1.10.4","go_db":"2017-Jun","kegg_db":"2016-Nov","gsea_db":"2016-Nov","gene_atlas_db":"2016-Nov","ensembl":"2017-Mar"},"compliance":{"1":[{"name":"scFAIR","version":"7.1.0","source_schema_name":"scFAIR schema","description":"scFAIR validates single-cell transcriptomics datasets against the scFAIR cell metadata schema","source_url":"https://github.com/scFAIR/scFAIR/blob/main/schema/7.1.0/README.md","url":"https://sc-fair.org","compliant_icon":"scfair_badge_compliant.svg","not_compliant_icon":"scfair_badge_noncompliant.svg","if_compliant":["allow_public"]}]}}
New version including: - changing reading and writing methods to the 'data.table' package to speed up processing of big datasets - handling of 69 organisms (from all releases of Ensembl database) - addition of alternative gene names from old Ensembl releases - correction of minor bugs - update of R and Python libraries
| Tool | Version |
|---|---|
| java_stats | 1.0 |
| sclvm | 0.99.3 |
| gpy | 1.5.6 |
| limix | 0.8.0.dev0 |
| h5py | 2.6.0 |
| scikits_learn | 0.18.1 |
| numpy | 1.11.2 |
| scipy | 0.18.1 |
| java | 1.8.0_111 |
| python | 2.7.5 |
| combat | 3.24.4 |
| stats | 3.3.1 |
| sc3 | 1.3.11 |
| mds | 7.3-45 |
| pam | 2.0.6 |
| zifa | 0.1 |
| rtsne | 0.13 |
| pagoda_scde | 2.5.0 |
| limma_voom | 3.32.2 |
| edger | 3.18.1 |
| deseq2 | 1.16.1 |
| scan_upc | 2.18.0 |
| datatable | 1.10.4 |
| go_db | 2017-Jun |
| kegg_db | 2016-Nov |
| gsea_db | 2016-Nov |
| gene_atlas_db | 2016-Nov |
| ensembl | 2017-Mar |
{"tool_versions":{"java_stats":"1.0","sclvm":"0.99.3","gpy":"1.5.6","limix":"0.8.0.dev0","h5py":"2.6.0","scikits_learn":"0.18.1","numpy":"1.11.2","scipy":"0.18.1","java":"1.8.0_111","python":"2.7.5","combat":"3.24.4","stats":"3.3.1","sc3":"1.3.11","mds":"7.3-45","pam":"2.0.6","zifa":"0.1","rtsne":"0.13","pagoda_scde":"2.5.0","limma_voom":"3.32.2","edger":"3.18.1","deseq2":"1.16.1","scan_upc":"2.18.0","datatable":"1.10.4","go_db":"2017-Jun","kegg_db":"2016-Nov","gsea_db":"2016-Nov","gene_atlas_db":"2016-Nov","ensembl":"2017-Mar"},"compliance":{"1":[{"name":"scFAIR","version":"7.1.0","source_schema_name":"scFAIR schema","description":"scFAIR validates single-cell transcriptomics datasets against the scFAIR cell metadata schema","source_url":"https://github.com/scFAIR/scFAIR/blob/main/schema/7.1.0/README.md","url":"https://sc-fair.org","compliant_icon":"scfair_badge_compliant.svg","not_compliant_icon":"scfair_badge_noncompliant.svg","if_compliant":["allow_public"]}]}}
This is the first version!
| Tool | Version |
|---|---|
| java_stats | 1.0 |
| sclvm | 0.99.2 |
| gpy | 1.5.6 |
| limix | 0.8.0.dev0 |
| h5py | 2.6.0 |
| scikits_learn | 0.18.1 |
| numpy | 1.11.2 |
| scipy | 0.18.1 |
| java | 1.8.0_111 |
| python | 2.7.5 |
| combat | 3.18.0 |
| stats | 3.3.1 |
| sc3 | 1.3.11 |
| mds | 7.3-45 |
| pam | 2.0.5 |
| zifa | 0.1 |
| rtsne | 0.11 |
| pagoda_scde | 1.99.4 |
| limma_voom | 3.26.9 |
| edger | 3.12.1 |
| deseq2 | 1.10.1 |
| scan_upc | 2.12.1 |
| go_db | 2016-Nov |
| kegg_db | 2016-Nov |
| gsea_db | 2016-Nov |
| gene_atlas_db | 2016-Nov |
{"tool_versions":{"java_stats":"1.0","sclvm":"0.99.2","gpy":"1.5.6","limix":"0.8.0.dev0","h5py":"2.6.0","scikits_learn":"0.18.1","numpy":"1.11.2","scipy":"0.18.1","java":"1.8.0_111","python":"2.7.5","combat":"3.18.0","stats":"3.3.1","sc3":"1.3.11","mds":"7.3-45","pam":"2.0.5","zifa":"0.1","rtsne":"0.11","pagoda_scde":"1.99.4","limma_voom":"3.26.9","edger":"3.12.1","deseq2":"1.10.1","scan_upc":"2.12.1","go_db":"2016-Nov","kegg_db":"2016-Nov","gsea_db":"2016-Nov","gene_atlas_db":"2016-Nov"},"compliance":{"1":[{"name":"scFAIR","version":"7.1.0","source_schema_name":"scFAIR schema","description":"scFAIR validates single-cell transcriptomics datasets against the scFAIR cell metadata schema","source_url":"https://github.com/scFAIR/scFAIR/blob/main/schema/7.1.0/README.md","url":"https://sc-fair.org","compliant_icon":"scfair_badge_compliant.svg","not_compliant_icon":"scfair_badge_noncompliant.svg","if_compliant":["allow_public"]}]}}