Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation.
<p>Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation.</p>
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2025
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| _version_ | 1852014361839665152 |
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| author | Siyi Huang (8562174) |
| author2 | Linfeng Jiang (2416375) Ming Yi (15051) Yuan Zhu (148570) |
| author2_role | author author author |
| author_facet | Siyi Huang (8562174) Linfeng Jiang (2416375) Ming Yi (15051) Yuan Zhu (148570) |
| author_role | author |
| dc.creator.none.fl_str_mv | Siyi Huang (8562174) Linfeng Jiang (2416375) Ming Yi (15051) Yuan Zhu (148570) |
| dc.date.none.fl_str_mv | 2025-12-01T18:50:32Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pcbi.1013744.s033 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Skewness_coefficients_of_total_expression_distributions_across_six_datasets_before_imputation_after_data_transformation_and_after_imputation_/30756043 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Genetics Molecular Biology Plant Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> single uses bulk rna recovers expression values providing clear guidelines including cell clustering false measurements caused extensive practical evaluation essential downstream analyses differential expression detection cell rna sequencing cell &# 8217 three key innovations guided imputation engine distort biological signals aware normalization step d3impute demonstrates consistent accurately identify non true biological zeros seq data analysis biological zeros true transcriptome key hurdle guide imputation biological reference aware modeling aware discrimination seq data inflated data data recovery trajectory inference technical limitations specific characteristics significant improvements oriented solution optimal application network discriminator major challenge introduce d3impute handling zero genuinely absent generalizable framework fundamental issue computational methods comprehensive benchmarking cellular heterogeneity biologically informed also offers 12 state |
| dc.title.none.fl_str_mv | Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_02b3e9d3ffbcade5f811fbbdecad0df6 |
| identifier_str_mv | 10.1371/journal.pcbi.1013744.s033 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30756043 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation.Siyi Huang (8562174)Linfeng Jiang (2416375)Ming Yi (15051)Yuan Zhu (148570)GeneticsMolecular BiologyPlant BiologyBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedxlink "> singleuses bulk rnarecovers expression valuesproviding clear guidelinesincluding cell clusteringfalse measurements causedextensive practical evaluationessential downstream analysesdifferential expression detectioncell rna sequencingcell &# 8217three key innovationsguided imputation enginedistort biological signalsaware normalization stepd3impute demonstrates consistentaccurately identify nontrue biological zerosseq data analysisbiological zerostrue transcriptomekey hurdleguide imputationbiological referenceaware modelingaware discriminationseq datainflated datadata recoverytrajectory inferencetechnical limitationsspecific characteristicssignificant improvementsoriented solutionoptimal applicationnetwork discriminatormajor challengeintroduce d3imputehandling zerogenuinely absentgeneralizable frameworkfundamental issuecomputational methodscomprehensive benchmarkingcellular heterogeneitybiologically informedalso offers12 state<p>Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation.</p>2025-12-01T18:50:32ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pcbi.1013744.s033https://figshare.com/articles/dataset/Skewness_coefficients_of_total_expression_distributions_across_six_datasets_before_imputation_after_data_transformation_and_after_imputation_/30756043CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/307560432025-12-01T18:50:32Z |
| spellingShingle | Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation. Siyi Huang (8562174) Genetics Molecular Biology Plant Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> single uses bulk rna recovers expression values providing clear guidelines including cell clustering false measurements caused extensive practical evaluation essential downstream analyses differential expression detection cell rna sequencing cell &# 8217 three key innovations guided imputation engine distort biological signals aware normalization step d3impute demonstrates consistent accurately identify non true biological zeros seq data analysis biological zeros true transcriptome key hurdle guide imputation biological reference aware modeling aware discrimination seq data inflated data data recovery trajectory inference technical limitations specific characteristics significant improvements oriented solution optimal application network discriminator major challenge introduce d3impute handling zero genuinely absent generalizable framework fundamental issue computational methods comprehensive benchmarking cellular heterogeneity biologically informed also offers 12 state |
| status_str | publishedVersion |
| title | Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation. |
| title_full | Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation. |
| title_fullStr | Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation. |
| title_full_unstemmed | Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation. |
| title_short | Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation. |
| title_sort | Skewness coefficients of total expression distributions across six datasets before imputation, after data transformation, and after imputation. |
| topic | Genetics Molecular Biology Plant Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> single uses bulk rna recovers expression values providing clear guidelines including cell clustering false measurements caused extensive practical evaluation essential downstream analyses differential expression detection cell rna sequencing cell &# 8217 three key innovations guided imputation engine distort biological signals aware normalization step d3impute demonstrates consistent accurately identify non true biological zeros seq data analysis biological zeros true transcriptome key hurdle guide imputation biological reference aware modeling aware discrimination seq data inflated data data recovery trajectory inference technical limitations specific characteristics significant improvements oriented solution optimal application network discriminator major challenge introduce d3impute handling zero genuinely absent generalizable framework fundamental issue computational methods comprehensive benchmarking cellular heterogeneity biologically informed also offers 12 state |