Advanced Search
Display options
Filter resources
Text Availability
Article type
Publication date
Species
Language
Sex
Age
Showing 1 to 12 of 25 entries
Sorted by: Best Match Show Resources per page
Single-cell RNA-Seq: a next generation sequencing tool for a high-resolution view of the individual cell.

Journal of biomolecular structure & dynamics

Stevenson K, Uversky VN.
PMID: 31524088
J Biomol Struct Dyn. 2020 Aug;38(12):3730-3735. doi: 10.1080/07391102.2019.1659859. Epub 2019 Sep 15.

Communicated by Ramaswamy H. Sarma.

Cite
Stevenson K, Uversky VN. Single-cell RNA-Seq: a next generation sequencing tool for a high-resolution view of the individual cell. J Biomol Struct Dyn. 2019;38(12):3730-3735doi: 10.1080/07391102.2019.1659859.
Stevenson, K., & Uversky, V. N. (2020). Single-cell RNA-Seq: a next generation sequencing tool for a high-resolution view of the individual cell. Journal of biomolecular structure & dynamics, 38(12), 3730-3735. https://doi.org/10.1080/07391102.2019.1659859
Stevenson, Kevin, and Uversky, Vladimir N. "Single-cell RNA-Seq: a next generation sequencing tool for a high-resolution view of the individual cell." Journal of biomolecular structure & dynamics vol. 38,12 (2020): 3730-3735. doi: https://doi.org/10.1080/07391102.2019.1659859
Stevenson K, Uversky VN. Single-cell RNA-Seq: a next generation sequencing tool for a high-resolution view of the individual cell. J Biomol Struct Dyn. 2020 Aug;38(12):3730-3735. doi: 10.1080/07391102.2019.1659859. Epub 2019 Sep 15. PMID: 31524088.
Copy Download .nbib Format: NLM
GPress: a framework for querying general feature format (GFF) files and expression files in a compressed form.

Bioinformatics (Oxford, England)

Meng Q, Ochoa I, Hernaez M.
PMID: 32609343
Bioinformatics. 2020 Sep 15;36(18):4810-4812. doi: 10.1093/bioinformatics/btaa604.

MOTIVATION: Sequencing data are often summarized at different annotation levels for further analysis, generally using the general feature format (GFF) or its descendants, gene transfer format (GTF) and GFF3. Existing utilities for accessing these files, like gffutils and gffread,...

Cite
Meng Q, Ochoa I, Hernaez M. GPress: a framework for querying general feature format (GFF) files and expression files in a compressed form. Bioinformatics. 2020;36(18):4810-4812doi: 10.1093/bioinformatics/btaa604.
Meng, Q., Ochoa, I., & Hernaez, M. (2020). GPress: a framework for querying general feature format (GFF) files and expression files in a compressed form. Bioinformatics (Oxford, England), 36(18), 4810-4812. https://doi.org/10.1093/bioinformatics/btaa604
Meng, Qingxi, et al. "GPress: a framework for querying general feature format (GFF) files and expression files in a compressed form." Bioinformatics (Oxford, England) vol. 36,18 (2020): 4810-4812. doi: https://doi.org/10.1093/bioinformatics/btaa604
Meng Q, Ochoa I, Hernaez M. GPress: a framework for querying general feature format (GFF) files and expression files in a compressed form. Bioinformatics. 2020 Sep 15;36(18):4810-4812. doi: 10.1093/bioinformatics/btaa604. PMID: 32609343.
Copy Download .nbib Format: NLM
RNAIndel: discovering somatic coding indels from tumor RNA-Seq data.

Bioinformatics (Oxford, England)

Hagiwara K, Ding L, Edmonson MN, Rice SV, Newman S, Easton J, Dai J, Meshinchi S, Ries RE, Rusch M, Zhang J.
PMID: 31593214
Bioinformatics. 2020 Mar 01;36(5):1382-1390. doi: 10.1093/bioinformatics/btz753.

MOTIVATION: Reliable identification of expressed somatic insertions/deletions (indels) is an unmet need due to artifacts generated in PCR-based RNA-Seq library preparation and the lack of normal RNA-Seq data, presenting analytical challenges for discovery of somatic indels in tumor transcriptome.RESULTS:...

Cite
Hagiwara K, Ding L, Edmonson MN, et al. RNAIndel: discovering somatic coding indels from tumor RNA-Seq data. Bioinformatics. 2020;36(5):1382-1390doi: 10.1093/bioinformatics/btz753.
Hagiwara, K., Ding, L., Edmonson, M. N., Rice, S. V., Newman, S., Easton, J., Dai, J., Meshinchi, S., Ries, R. E., Rusch, M., & Zhang, J. (2020). RNAIndel: discovering somatic coding indels from tumor RNA-Seq data. Bioinformatics (Oxford, England), 36(5), 1382-1390. https://doi.org/10.1093/bioinformatics/btz753
Hagiwara, Kohei, et al. "RNAIndel: discovering somatic coding indels from tumor RNA-Seq data." Bioinformatics (Oxford, England) vol. 36,5 (2020): 1382-1390. doi: https://doi.org/10.1093/bioinformatics/btz753
Hagiwara K, Ding L, Edmonson MN, Rice SV, Newman S, Easton J, Dai J, Meshinchi S, Ries RE, Rusch M, Zhang J. RNAIndel: discovering somatic coding indels from tumor RNA-Seq data. Bioinformatics. 2020 Mar 01;36(5):1382-1390. doi: 10.1093/bioinformatics/btz753. PMID: 31593214; PMCID: PMC7523641.
Copy Download .nbib Format: NLM
Aggregating transcript-level analyses for single-cell differential gene expression.

Nature methods

Becht E, Zhao E, Amezquita R, Gottardo R.
PMID: 32483334
Nat Methods. 2020 Jun;17(6):583-585. doi: 10.1038/s41592-020-0854-4. Epub 2020 Jun 01.

No abstract available.

Cite
Becht E, Zhao E, Amezquita R, et al. Aggregating transcript-level analyses for single-cell differential gene expression. Nat Methods. 2020;17(6):583-585doi: 10.1038/s41592-020-0854-4.
Becht, E., Zhao, E., Amezquita, R., & Gottardo, R. (2020). Aggregating transcript-level analyses for single-cell differential gene expression. Nature methods, 17(6), 583-585. https://doi.org/10.1038/s41592-020-0854-4
Becht, Etienne, et al. "Aggregating transcript-level analyses for single-cell differential gene expression." Nature methods vol. 17,6 (2020): 583-585. doi: https://doi.org/10.1038/s41592-020-0854-4
Becht E, Zhao E, Amezquita R, Gottardo R. Aggregating transcript-level analyses for single-cell differential gene expression. Nat Methods. 2020 Jun;17(6):583-585. doi: 10.1038/s41592-020-0854-4. Epub 2020 Jun 01. PMID: 32483334.
Copy Download .nbib Format: NLM
Guidelines for reporting single-cell RNA-seq experiments.

Nature biotechnology

Füllgrabe A, George N, Green M, Nejad P, Aronow B, Fexova SK, Fischer C, Freeberg MA, Huerta L, Morrison N, Scheuermann RH, Taylor D, Vasilevsky N, Clarke L, Gehlenborg N, Kent J, Marioni J, Teichmann S, Brazma A, Papatheodorou I.
PMID: 33188371
Nat Biotechnol. 2020 Dec;38(12):1384-1386. doi: 10.1038/s41587-020-00744-z.

No abstract available.

Cite
Füllgrabe A, George N, Green M, et al. Guidelines for reporting single-cell RNA-seq experiments. Nat Biotechnol. 2020;38(12):1384-1386doi: 10.1038/s41587-020-00744-z.
Füllgrabe, A., George, N., Green, M., Nejad, P., Aronow, B., Fexova, S. K., Fischer, C., Freeberg, M. A., Huerta, L., Morrison, N., Scheuermann, R. H., Taylor, D., Vasilevsky, N., Clarke, L., Gehlenborg, N., Kent, J., Marioni, J., Teichmann, S., Brazma, A., & Papatheodorou, I. (2020). Guidelines for reporting single-cell RNA-seq experiments. Nature biotechnology, 38(12), 1384-1386. https://doi.org/10.1038/s41587-020-00744-z
Füllgrabe, Anja, et al. "Guidelines for reporting single-cell RNA-seq experiments." Nature biotechnology vol. 38,12 (2020): 1384-1386. doi: https://doi.org/10.1038/s41587-020-00744-z
Füllgrabe A, George N, Green M, Nejad P, Aronow B, Fexova SK, Fischer C, Freeberg MA, Huerta L, Morrison N, Scheuermann RH, Taylor D, Vasilevsky N, Clarke L, Gehlenborg N, Kent J, Marioni J, Teichmann S, Brazma A, Papatheodorou I. Guidelines for reporting single-cell RNA-seq experiments. Nat Biotechnol. 2020 Dec;38(12):1384-1386. doi: 10.1038/s41587-020-00744-z. PMID: 33188371.
Copy Download .nbib Format: NLM
MapMan Visualization of RNA-Seq Data Using Mercator4 Functional Annotations.

Methods in molecular biology (Clifton, N.J.)

Bolger M, Schwacke R, Usadel B.
PMID: 34448161
Methods Mol Biol. 2021;2354:195-212. doi: 10.1007/978-1-0716-1609-3_9.

Plant omics research has advanced to the stage where it is feasible to generate data from multiple samples and multiple time points to gain insight into biological processes. This impressive array of data can prove challenging to interpret. In...

Cite
Bolger M, Schwacke R, Usadel B. MapMan Visualization of RNA-Seq Data Using Mercator4 Functional Annotations. Methods Mol Biol. 2021;2354:195-212doi: 10.1007/978-1-0716-1609-3_9.
Bolger, M., Schwacke, R., & Usadel, B. (2021). MapMan Visualization of RNA-Seq Data Using Mercator4 Functional Annotations. Methods in molecular biology (Clifton, N.J.), 2354195-212. https://doi.org/10.1007/978-1-0716-1609-3_9
Bolger, Marie, et al. "MapMan Visualization of RNA-Seq Data Using Mercator4 Functional Annotations." Methods in molecular biology (Clifton, N.J.) vol. 2354 (2021): 195-212. doi: https://doi.org/10.1007/978-1-0716-1609-3_9
Bolger M, Schwacke R, Usadel B. MapMan Visualization of RNA-Seq Data Using Mercator4 Functional Annotations. Methods Mol Biol. 2021;2354:195-212. doi: 10.1007/978-1-0716-1609-3_9. PMID: 34448161.
Copy Download .nbib Format: NLM
ArrayExpress update - from bulk to single-cell expression data.

Nucleic acids research

Athar A, Füllgrabe A, George N, Iqbal H, Huerta L, Ali A, Snow C, Fonseca NA, Petryszak R, Papatheodorou I, Sarkans U, Brazma A.
PMID: 30357387
Nucleic Acids Res. 2019 Jan 08;47:D711-D715. doi: 10.1093/nar/gky964.

ArrayExpress (https://www.ebi.ac.uk/arrayexpress) is an archive of functional genomics data from a variety of technologies assaying functional modalities of a genome, such as gene expression or promoter occupancy. The number of experiments based on sequencing technologies, in particular RNA-seq experiments,...

Cite
Athar A, Füllgrabe A, George N, et al. ArrayExpress update - from bulk to single-cell expression data. Nucleic Acids Res. 2019;47:D711-D715doi: 10.1093/nar/gky964.
Athar, A., Füllgrabe, A., George, N., Iqbal, H., Huerta, L., Ali, A., Snow, C., Fonseca, N. A., Petryszak, R., Papatheodorou, I., Sarkans, U., & Brazma, A. (2019). ArrayExpress update - from bulk to single-cell expression data. Nucleic acids research, 47D711-D715. https://doi.org/10.1093/nar/gky964
Athar, Awais, et al. "ArrayExpress update - from bulk to single-cell expression data." Nucleic acids research vol. 47 (2019): D711-D715. doi: https://doi.org/10.1093/nar/gky964
Athar A, Füllgrabe A, George N, Iqbal H, Huerta L, Ali A, Snow C, Fonseca NA, Petryszak R, Papatheodorou I, Sarkans U, Brazma A. ArrayExpress update - from bulk to single-cell expression data. Nucleic Acids Res. 2019 Jan 08;47:D711-D715. doi: 10.1093/nar/gky964. PMID: 30357387; PMCID: PMC6323929.
Copy Download .nbib Format: NLM
intePareto: an R package for integrative analyses of RNA-Seq and ChIP-Seq data.

BMC genomics

Cao Y, Kitanovski S, Hoffmann D.
PMID: 33372591
BMC Genomics. 2020 Dec 29;21:802. doi: 10.1186/s12864-020-07205-6.

BACKGROUND: RNA-Seq, the high-throughput sequencing (HT-Seq) of mRNAs, has become an essential tool for characterizing gene expression differences between different cell types and conditions. Gene expression is regulated by several mechanisms, including epigenetically by post-translational histone modifications which can...

Cite
Cao Y, Kitanovski S, Hoffmann D. intePareto: an R package for integrative analyses of RNA-Seq and ChIP-Seq data. BMC Genomics. 2020;21:802doi: 10.1186/s12864-020-07205-6.
Cao, Y., Kitanovski, S., & Hoffmann, D. (2020). intePareto: an R package for integrative analyses of RNA-Seq and ChIP-Seq data. BMC genomics, 21802. https://doi.org/10.1186/s12864-020-07205-6
Cao, Yingying, et al. "intePareto: an R package for integrative analyses of RNA-Seq and ChIP-Seq data." BMC genomics vol. 21 (2020): 802. doi: https://doi.org/10.1186/s12864-020-07205-6
Cao Y, Kitanovski S, Hoffmann D. intePareto: an R package for integrative analyses of RNA-Seq and ChIP-Seq data. BMC Genomics. 2020 Dec 29;21:802. doi: 10.1186/s12864-020-07205-6. PMID: 33372591; PMCID: PMC7771091.
Copy Download .nbib Format: NLM
ASAP 2020 update: an open, scalable and interactive web-based portal for (single-cell) omics analyses.

Nucleic acids research

David FPA, Litovchenko M, Deplancke B, Gardeux V.
PMID: 32449934
Nucleic Acids Res. 2020 Jul 02;48:W403-W414. doi: 10.1093/nar/gkaa412.

Single-cell omics enables researchers to dissect biological systems at a resolution that was unthinkable just 10 years ago. However, this analytical revolution also triggered new demands in 'big data' management, forcing researchers to stay up to speed with increasingly...

Cite
David FPA, Litovchenko M, Deplancke B, et al. ASAP 2020 update: an open, scalable and interactive web-based portal for (single-cell) omics analyses. Nucleic Acids Res. 2020;48:W403-W414doi: 10.1093/nar/gkaa412.
David, F. P. A., Litovchenko, M., Deplancke, B., & Gardeux, V. (2020). ASAP 2020 update: an open, scalable and interactive web-based portal for (single-cell) omics analyses. Nucleic acids research, 48W403-W414. https://doi.org/10.1093/nar/gkaa412
David, Fabrice P A, et al. "ASAP 2020 update: an open, scalable and interactive web-based portal for (single-cell) omics analyses." Nucleic acids research vol. 48 (2020): W403-W414. doi: https://doi.org/10.1093/nar/gkaa412
David FPA, Litovchenko M, Deplancke B, Gardeux V. ASAP 2020 update: an open, scalable and interactive web-based portal for (single-cell) omics analyses. Nucleic Acids Res. 2020 Jul 02;48:W403-W414. doi: 10.1093/nar/gkaa412. PMID: 32449934; PMCID: PMC7319583.
Copy Download .nbib Format: NLM
Characterizing RNA stability genome-wide through combined analysis of PRO-seq and RNA-seq data.

BMC biology

Blumberg A, Zhao Y, Huang YF, Dukler N, Rice EJ, Chivu AG, Krumholz K, Danko CG, Siepel A.
PMID: 33588838
BMC Biol. 2021 Feb 15;19(1):30. doi: 10.1186/s12915-021-00949-x.

BACKGROUND: The concentrations of distinct types of RNA in cells result from a dynamic equilibrium between RNA synthesis and decay. Despite the critical importance of RNA decay rates, current approaches for measuring them are generally labor-intensive, limited in sensitivity,...

Cite
Blumberg A, Zhao Y, Huang YF, et al. Characterizing RNA stability genome-wide through combined analysis of PRO-seq and RNA-seq data. BMC Biol. 2021;19(1):30doi: 10.1186/s12915-021-00949-x.
Blumberg, A., Zhao, Y., Huang, Y. F., Dukler, N., Rice, E. J., Chivu, A. G., Krumholz, K., Danko, C. G., & Siepel, A. (2021). Characterizing RNA stability genome-wide through combined analysis of PRO-seq and RNA-seq data. BMC biology, 19(1), 30. https://doi.org/10.1186/s12915-021-00949-x
Blumberg, Amit, et al. "Characterizing RNA stability genome-wide through combined analysis of PRO-seq and RNA-seq data." BMC biology vol. 19,1 (2021): 30. doi: https://doi.org/10.1186/s12915-021-00949-x
Blumberg A, Zhao Y, Huang YF, Dukler N, Rice EJ, Chivu AG, Krumholz K, Danko CG, Siepel A. Characterizing RNA stability genome-wide through combined analysis of PRO-seq and RNA-seq data. BMC Biol. 2021 Feb 15;19(1):30. doi: 10.1186/s12915-021-00949-x. PMID: 33588838; PMCID: PMC7885420.
Copy Download .nbib Format: NLM
Editorial for the special issue "RNA-Seq: Methods and applications".

Methods (San Diego, Calif.)

Xia X, Moriyama EN, Gu X.
PMID: 32151669
Methods. 2020 Apr 01;176:1-3. doi: 10.1016/j.ymeth.2020.03.003. Epub 2020 Mar 06.

No abstract available.

Cite
Xia X, Moriyama EN, Gu X. Editorial for the special issue "RNA-Seq: Methods and applications". Methods. 2020;176:1-3doi: 10.1016/j.ymeth.2020.03.003.
Xia, X., Moriyama, E. N., & Gu, X. (2020). Editorial for the special issue "RNA-Seq: Methods and applications". Methods (San Diego, Calif.), 1761-3. https://doi.org/10.1016/j.ymeth.2020.03.003
Xia, Xuhua, et al. "Editorial for the special issue "RNA-Seq: Methods and applications"." Methods (San Diego, Calif.) vol. 176 (2020): 1-3. doi: https://doi.org/10.1016/j.ymeth.2020.03.003
Xia X, Moriyama EN, Gu X. Editorial for the special issue "RNA-Seq: Methods and applications". Methods. 2020 Apr 01;176:1-3. doi: 10.1016/j.ymeth.2020.03.003. Epub 2020 Mar 06. PMID: 32151669.
Copy Download .nbib Format: NLM
snakePipes: facilitating flexible, scalable and integrative epigenomic analysis.

Bioinformatics (Oxford, England)

Bhardwaj V, Heyne S, Sikora K, Rabbani L, Rauer M, Kilpert F, Richter AS, Ryan DP, Manke T.
PMID: 31134269
Bioinformatics. 2019 Nov 01;35(22):4757-4759. doi: 10.1093/bioinformatics/btz436.

SUMMARY: Due to the rapidly increasing scale and diversity of epigenomic data, modular and scalable analysis workflows are of wide interest. Here we present snakePipes, a workflow package for processing and downstream analysis of data from common epigenomic assays:...

Cite
Bhardwaj V, Heyne S, Sikora K, et al. snakePipes: facilitating flexible, scalable and integrative epigenomic analysis. Bioinformatics. 2019;35(22):4757-4759doi: 10.1093/bioinformatics/btz436.
Bhardwaj, V., Heyne, S., Sikora, K., Rabbani, L., Rauer, M., Kilpert, F., Richter, A. S., Ryan, D. P., & Manke, T. (2019). snakePipes: facilitating flexible, scalable and integrative epigenomic analysis. Bioinformatics (Oxford, England), 35(22), 4757-4759. https://doi.org/10.1093/bioinformatics/btz436
Bhardwaj, Vivek, et al. "snakePipes: facilitating flexible, scalable and integrative epigenomic analysis." Bioinformatics (Oxford, England) vol. 35,22 (2019): 4757-4759. doi: https://doi.org/10.1093/bioinformatics/btz436
Bhardwaj V, Heyne S, Sikora K, Rabbani L, Rauer M, Kilpert F, Richter AS, Ryan DP, Manke T. snakePipes: facilitating flexible, scalable and integrative epigenomic analysis. Bioinformatics. 2019 Nov 01;35(22):4757-4759. doi: 10.1093/bioinformatics/btz436. PMID: 31134269; PMCID: PMC6853707.
Copy Download .nbib Format: NLM
Showing 1 to 12 of 25 entries