title: lib4764 [TN02_9075533_17]


title: lib4872 [START_003004_17]

status: Public on Feb 28 2019

type: SRA

city: Seattle,

first: Stephanie

last: Osmond

state: WA

address: 1201 9th Ave

country: USA

institute: Benaroya Research Institute

library_source: transcriptomic

data_processing:
Base-calling was performed automatically by Illumina real time analysis software and demultiplexing was performed on Illumina BaseSpace.
Hard trimming was performed in Galaxy; 1 3'-end base was removed from all reads using the FASTQ Trimmer tool (v1.0.0)
Quality-based trimming was performed in Galaxy; reads were trimmed from both ends using the FASTQ Quality Trimmer tool (v1.0.0) until minimum base quality for each read was >= 30.
Reads were aligned in Galaxy using bowtie and TopHat (Tophat for Illumina tool, v.1.5.0)
Read counts per Ensembl gene ID were estimated in Galaxy using htseq-count (htseq-count tool, v.0.4.1).
Sequencing, alignment, and quantitation metrics were obtained for FASTQ, BAM/SAM, and count files in Galaxy using FastQC, Picard, TopHat, Samtools, and htseq-count.
Genome_build: GRCh38
Supplementary_files_format_and_content: T1D_placebos_raw_counts.csv is a comma-delimited matrix. The first column ("ensgene") contains Ensembl gene IDs. The remaining columns include raw read counts assigned for each library. All samples that passed SNP-based identity checks are included, with 3 samples of uncertin provenance excluded. Data have not otherwise been filtered or normalized.

molecule: total RNA

organism: Homo sapiens

source_name: whole blood

extract_protocol:
RNA was isolated from whole blood samples preserved in Tempus blood RNA tubes (Applied Biosystems, CA) using the Total RNA Isolation chemistry on an ABI Prism 6100 (Applied Biosystems, CA) or a Thermo Scientific KingFisher (Thermo Fisher Scientific, MA).
Samples were globin-reduced with the GLOBINclear kit (Ambion, CA), and libraries were constructed from globin-reduced RNA using the Illumina TruSeq RNA Sample Preparation kit v2. Libraries were clustered on flow cells using the TruSeq Single Read Cluster Kit v3.

tag: subject

tag: rate of c-peptide change

tag: visit day

tag: age at enrollment

tag: Sex

value: male

tag: race

value: White

tag: ethnicity

value: Not Hispanic or Latino

tag: lymphocyte percent

tag: neutrophil percent


title: lib4771 [TN02_9024813_11]

value: female

tag: library batch


title: lib4882 [START_010005_14]

value: Hispanic or Latino


title: lib4762 [TN02_9065086_2]


title: lib4839 [START_002003_0]


title: lib4760 [TN02_9098713_2]


title: lib4761 [TN02_9076428_2]


title: lib4768 [TN02_9035402_11]


title: lib4763 [TN02_9039335_2]

value: Unknown or Not Reported


title: lib4765 [TN02_9025240_29]


title: lib4841 [START_002007_0]


title: lib4840 [START_002010_11]


title: lib4837 [TN02_9013178_23]


title: lib4836 [TN02_9081777_17]


title: lib4835 [TN02_9013178_17]


title: lib4773 [TN02_9057024_23]


title: lib4834 [TN02_9015755_17]


title: lib4833 [TN02_9098296_11]


title: lib4832 [TN02_9081451_17]


title: lib4826 [TN02_9064544_23]


title: lib4823 [TN02_9015338_17]


title: lib4825 [TN02_9081777_23]


title: lib4824 [TN02_9093772_23]


title: lib4828 [TN02_9098296_23]


title: lib4827 [TN02_9098296_17]


title: lib4739 [TN02_9053329_17]


title: lib4738 [TN02_9053329_11]


title: lib4734 [TN02_9041386_17]


title: lib4732 [TN02_9098713_17]


title: lib4733 [TN02_9043986_29]


title: lib4735 [TN02_9016861_23]


title: lib4731 [TN02_9001542_11]


title: lib4730 [TN02_9041386_2]


title: lib4729 [TN02_9065086_17]


title: lib4728 [TN02_9040657_2]

value: Other


title: lib4767 [TN02_9065329_29]

value: Asian


title: lib4766 [TN02_9053642_23]


title: lib4807 [TN02_9065086_11]


title: lib4831 [TN02_9013178_11]


title: lib4829 [TN02_9001825_23]


title: lib4740 [TN02_9065329_17]


title: lib4806 [TN02_9052681_2]


title: lib4736 [TN02_9053642_2]


title: lib4805 [TN02_9079286_2]


title: lib4678 [TN02_9076428_29]


title: lib4804 [TN02_9066885_11]


title: lib4677 [TN02_9025380_23]


title: lib4803 [TN02_9057024_11]


title: lib4679 [TN02_9058753_23]


title: lib4802 [TN02_9024813_2]


title: lib4674 [TN02_9028156_23]


title: lib4675 [TN02_9040657_17]


title: lib4670 [TN02_9076280_29]


title: lib4672 [TN02_9025380_17]


title: lib4838 [START_002003_11]


title: lib4668 [TN02_9065329_23]


title: lib4671 [TN02_9076428_23]


title: lib4669 [TN02_9019151_23]


title: lib4666 [TN02_9054059_11]


title: lib4673 [TN02_9043986_23]


title: lib4665 [TN02_9068868_2]


title: lib4667 [TN02_9068868_11]


title: lib4664 [TN02_9015755_2]


title: lib4676 [TN02_9035402_23]


title: lib4756 [TN02_9058753_17]


title: lib3308 [TN05_9010167_18]


title: lib3310 [TN05_9009405_27]


title: lib3306 [TN05_9072116_27]


title: lib4779 [TN02_9019151_29]


title: lib4663 [TN02_9054059_2]


title: lib3303 [TN05_9075694_27]


title: lib3300 [TN05_9023796_27]


title: lib3294 [TN05_9025834_27]


title: lib3282 [TN05_9026667_27]


title: lib3280 [TN05_9006024_18]


title: lib3286 [TN05_9032923_27]


title: lib3292 [TN05_9025834_18]


title: lib3277 [TN05_9072116_2]


title: lib3274 [TN05_9010167_2]


title: lib3256 [TN05_9006024_2]


title: lib3243 [TN05_9066662_16]


title: lib3254 [TN05_9045381_2]


title: lib3240 [TN05_9089953_16]


title: lib3266 [TN05_9066662_18]


title: lib3265 [TN05_9096837_27]


title: lib3242 [TN05_9009405_2]


title: lib3223 [TN05_9023796_16]


title: lib3279 [TN05_9089953_2]


title: lib3220 [TN05_9026667_16]


title: lib3413 [TN05_9031738_18]


title: lib3421 [TN05_9089953_29]


title: lib3411 [TN05_9072116_18]


title: lib3395 [TN05_9072116_29]


title: lib3405 [TN05_9044850_27]


title: lib3408 [TN05_9009405_18]


title: lib3247 [TN05_9023796_2]


title: lib3393 [TN05_9066662_29]


title: lib3385 [TN05_9045381_27]


title: lib3383 [TN05_9081664_29]


title: lib3417 [TN05_9023796_18]


title: lib3382 [TN05_9026667_2]


title: lib3218 [TN05_9072116_16]


title: lib3389 [TN05_9045381_29]


title: lib3379 [TN05_9066662_2]


title: lib3387 [TN05_9081664_18]


title: lib3369 [TN05_9081664_16]


title: lib3358 [TN05_9031738_16]


title: lib3373 [TN05_9006024_16]


title: lib3355 [TN05_9010167_16]


title: lib3352 [TN05_9006024_29]


title: lib3353 [TN05_9014572_2]


title: lib3354 [TN05_9081664_27]


title: lib4737 [TN02_9053642_11]


title: lib3348 [TN05_9026667_29]


title: lib3341 [TN05_9075694_16]


title: lib3351 [TN05_9032923_29]


title: lib3338 [TN05_9075694_29]


title: lib3330 [TN05_9026667_18]


title: lib3339 [TN05_9010167_29]


title: lib4830 [TN02_9015755_11]


title: lib3370 [TN05_9081664_2]


title: lib3360 [TN05_9006024_27]


title: lib3326 [TN05_9089953_18]


title: lib3322 [TN05_9075694_2]


title: lib3324 [TN05_9010167_27]


title: lib3321 [TN05_9031738_27]


title: lib3323 [TN05_9096837_29]


title: lib3595 [T1DAL_00110202_0]


title: lib3633 [T1DAL_00910199_28]


title: lib3592 [T1DAL_00410087_28]


title: lib3591 [T1DAL_00410087_0]


title: lib3630 [T1DAL_01010608_0]


title: lib3325 [TN05_9075694_18]


title: lib5167

data_processing:
Base-calling was performed automatically by Illumina real time analysis software and demultiplexing was performed on Illumina BaseSpace.
Hard trimming was performed in Galaxy; 1 3'-end base was removed from all reads using the FASTQ Trimmer tool (v1.0.0)
Quality-based trimming was performed in Galaxy; reads were trimmed from both ends using the FASTQ Quality Trimmer tool (v1.0.0) until minimum base quality for each read was >= 30.
Reads were aligned in Galaxy using bowtie and TopHat (Tophat for Illumina tool, v.1.5.0)
Read counts per Ensembl gene ID were estimated in Galaxy using htseq-count (htseq-count tool, v.0.4.1).
Sequencing, alignment, and quantitation metrics were obtained for FASTQ, BAM/SAM, and count files in Galaxy using FastQC, Picard, TopHat, Samtools, and htseq-count.
Genome_build: GRCh38
Supplementary_files_format_and_content: TN09_abatacept_raw_counts.csv is a comma-delimited matrix. The first column ("ensgene") contains Ensembl gene IDs. The remaining columns include raw read counts assigned for each library. All samples are included, and data have not been filtered or normalized.

extract_protocol:
RNA was isolated from whole blood samples using the Total RNA Isolation chemistry on an ABI Prism 6100 (Applied Biosystems, CA).
Samples were globin- reduced with the GLOBINclear kit (Ambion, CA), and libraries were constructed from globin-reduced RNA using the Illumina TruSeq RNA Sample Preparation kit v2. Libraries were clustered on flow cells using the TruSeq Single Read Cluster Kit v3.

tag: visit

value: day 728

tag: treatment

tag: age at draw

value: Black or African American


title: lib5170

value: day 84


title: lib5166

value: Placebo

value: White; Other


title: lib5165


title: lib5171


title: lib5164


title: lib5168

value: day 0


title: lib5160


title: lib5162


title: lib5159

value: Black or African American; White


title: lib5163


title: lib5169


title: lib5158


title: lib3357 [TN05_9009405_16]


title: lib5157


title: lib5155


title: lib5156


title: lib5154


title: lib5153


title: lib5152


title: lib5147


title: lib5151


title: lib5150


title: lib3401 [TN05_9089953_27]


title: lib3377 [TN05_9031738_2]


title: lib5146


title: lib5161


title: lib5145


title: lib5143


title: lib5138


title: lib5140


title: lib5137


title: lib5144


title: lib5139


title: lib5136


title: lib5131

value: 2 years, 6 months


title: lib5142


title: lib5133


title: lib5130


title: lib5132


title: lib5149


title: lib5148


title: lib5128

value: unscheduled


title: lib5135

value: male


title: lib5134

value: White


title: lib5129

value: Not Hispanic or Latino


title: lib5127


title: lib5123


title: lib5121


title: lib5126


title: lib5124


title: lib5120

value: female


title: lib5118


title: lib5117


title: lib5141


title: lib5116

value: Hispanic or Latino


title: lib5115


title: lib5111


title: lib5112


title: lib5125


title: lib5108


title: lib5103


title: lib5107


title: lib5104


title: lib5122


title: lib5106


title: lib5101


title: lib5110


title: lib5105


title: lib5102


title: lib5100


title: lib5119


title: lib5099


title: lib5096


title: lib5094


title: lib5098


title: lib5092


title: lib5091


title: lib5090


title: lib5093


title: lib5114


title: lib5113


title: lib5087


title: lib5088


title: lib5109


title: lib5089


title: lib5085


title: lib5086


title: lib5084


title: lib5095


title: lib5097


title: lib5082


title: lib5080


title: lib5078


title: lib5083


title: lib5077


title: lib5081


title: lib5079


title: lib5076


title: lib5075


title: lib5072


title: lib5074


title: lib5073


title: lib5071


title: lib5069


title: lib5070


title: lib5066


title: lib5068


title: lib5063


title: lib5065


title: lib5067


title: lib5064


title: lib5062


title: lib5061


title: lib5057


title: lib5059


title: lib5060


title: lib5058


title: lib5056


title: lib5054


title: lib5055


title: lib5052


title: lib5053


title: lib5049


title: lib5047


title: lib5048


title: lib5051


title: lib5050


title: lib5045


title: lib5041


title: lib5044


title: lib5042


title: lib5038


title: lib5040


title: lib5043


title: lib5036


title: lib5034


title: lib5035


title: lib5037


title: lib5033


title: lib5046


title: lib5032


title: lib5030


title: lib5039


title: lib5028


title: lib5027


title: lib5026


title: lib5025


title: lib5021


title: lib5019


title: lib5020


title: lib5017


title: lib5024


title: lib5016


title: lib5031


title: lib5018


title: lib5012


title: lib5008


title: lib5013


title: lib5015


title: lib5007


title: lib5010


title: lib5005


title: lib5011


title: lib5006


title: lib5029


title: lib5014


title: lib5009


title: lib5004


title: lib5003


title: lib5002


title: lib5001


title: lib5022


title: lib5000


title: lib4999


title: lib4997


title: lib4995


title: lib4996


title: lib4994


title: lib4992


title: lib4993


title: lib4991


title: lib4990


title: lib4989


title: lib4985


title: lib4988


title: lib4982


title: lib4987


title: lib4986


title: lib4980


title: lib4978


title: lib4983


title: lib4979


title: lib4981


title: lib4977


title: lib4971


title: lib4998


title: lib4974


title: lib4973


title: lib4975


title: lib4972


title: lib4976


title: lib4969


title: lib4970


title: lib4984


title: lib4966


title: lib4968


title: lib4964


title: lib4963


title: lib4962


title: lib4960


title: lib4965


title: lib4956


title: lib4959


title: lib4957


title: lib4958


title: lib5023


title: lib4955


title: lib4954


title: lib4952


title: lib4951


title: lib4950


title: lib4947


title: lib4967


title: lib4949


title: lib4948


title: lib4946


title: lib4943


title: lib4944


title: lib4941


title: lib4942


title: lib4938


title: lib4940


title: lib4939


title: lib4937


title: lib4936


title: lib4961


title: lib4935


title: lib4934


title: lib4933


title: lib4953


title: lib4932


title: lib4928


title: lib4929


title: lib4927


title: lib4930


title: lib4926


title: lib4931


title: lib4945


title: lib4924


title: lib4923


title: lib4925


title: lib4920


title: lib4919


title: lib4921


title: lib4918


title: lib4917


title: lib4916


title: lib4914


title: lib4915


title: lib4913


title: lib4912


title: lib4910


title: lib4911


title: lib4909


title: lib4922


title: lib4908


title: lib4907


title: lib4905


title: lib4903


title: lib4904


title: lib4901


title: lib4900


title: lib4899


title: lib4902


title: lib4897


title: lib6915 [T1DAL_01510142_30]


title: lib4896


title: lib6919 [T1DAL_01710726_30]


title: lib6912 [T1DAL_00410087_30]


title: lib4894


title: lib4906


title: lib4895


title: lib6909 [T1DAL_00110202_30]


title: lib4893


title: lib4898


title: lib4890


title: lib6903 [T1DAL_01010340_30]

value: White; American Indian or Alaska Native

value: Unknown


title: lib4891


title: lib6901 [T1DAL_01010608_30]


title: lib6890 [T1DAL_01110590_30]


title: lib4892


title: lib4888


title: lib6880 [T1DAL_01110590_15]


title: lib6905 [T1DAL_01410379_30]


title: lib6875 [T1DAL_01710433_15]


title: lib6918 [T1DAL_01710475_30]


title: lib4887


title: lib4886


title: lib6881 [T1DAL_00610411_15]


title: lib6873 [T1DAL_01710726_15]


title: lib6877 [T1DAL_01010608_15]


title: lib6871 [T1DAL_01710475_15]


title: lib6883 [T1DAL_00210551_15]


title: lib6864 [T1DAL_01410379_15]


title: lib6859 [T1DAL_01510142_15]


title: lib6868 [T1DAL_02010368_15]


title: lib6896 [T1DAL_00910199_30]


title: lib6849 [T1DAL_00910529_15]


title: lib4889


title: lib3611 [T1DAL_01710433_0]


title: lib6855 [T1DAL_00910199_15]


title: lib6899 [T1DAL_00210551_30]


title: lib3602 [T1DAL_01710726_0]


title: lib3603 [T1DAL_01710726_28]


title: lib3578 [T1DAL_01510142_28]


title: lib6876 [T1DAL_01010340_15]


title: lib3577 [T1DAL_01510142_0]


title: lib3558 [T1DAL_01410379_28]


title: lib3556 [T1DAL_02010368_28]


title: lib3557 [T1DAL_01410379_0]


title: lib3555 [T1DAL_02010368_0]


title: lib3553 [T1DAL_01710475_0]


title: lib3554 [T1DAL_01710475_28]


title: lib3609 [T1DAL_00610411_0]


title: lib3620 [T1DAL_01010340_0]


title: lib3632 [T1DAL_00910199_0]


title: lib3621 [T1DAL_01010340_28]


title: lib3580 [T1DAL_00210551_28]


title: lib3596 [T1DAL_00110202_28]


title: lib3563 [T1DAL_00910098_0]


title: lib3579 [T1DAL_00210551_0]


title: lib3605 [T1DAL_01110590_0]


title: lib1574 [ABATE_007005_42]


title: lib3599 [T1DAL_00910529_0]


title: lib3606 [T1DAL_01110590_28]


title: lib1570 [ABATE_006001_42]


title: lib1554 [ABATE_003006_42]


title: lib1577 [ABATE_007012_42]


title: lib1582 [ABATE_007019_42]


title: lib1573 [ABATE_007004_42]


title: lib1562 [ABATE_004005_42]


title: lib1569 [ABATE_005007_42]


title: lib1568 [ABATE_005006_42]


title: lib1550 [ABATE_002018_42]

value: White; Asian


title: lib1544 [ABATE_002008_42]


title: lib1546 [ABATE_002012_42]


title: lib6862 [T1DAL_00410087_15]


title: lib1532 [ABATE_001010_42]


title: lib1516 [ABATE_005006_19]


title: lib3631 [T1DAL_01010608_28]


title: lib1541 [ABATE_002004_42]


title: lib1513 [ABATE_004005_19]


title: lib1538 [ABATE_002001_42]


title: lib1519 [ABATE_006001_19]


title: lib1552 [ABATE_003003_42]


title: lib1521 [ABATE_007004_19]


title: lib1488 [ABATE_001010_19]


title: lib1565 [ABATE_005001_42]


title: lib1505 [ABATE_003006_19]


title: lib1517 [ABATE_005007_19]


title: lib1522 [ABATE_007005_19]


title: lib1504 [ABATE_003005_19]


title: lib1478 [ABATE_007005_0_2]


title: lib1500 [ABATE_002018_19]


title: lib1477 [ABATE_005007_0_1]


title: lib1476 [ABATE_004005_0_1]


title: lib1493 [ABATE_002004_19]


title: lib903 [ABATE_007005_0_1]


title: lib1473 [ABATE_003006_0_2]


title: lib902 [ABATE_007004_0]


title: lib1503 [ABATE_003003_19]


title: lib888 [ABATE_003012_0]


title: lib900 [ABATE_006001_0]


title: lib884 [ABATE_003005_0]


title: lib898 [ABATE_005007_0_2]


title: lib876 [ABATE_002004_0]


title: lib897 [ABATE_005006_0]


title: lib862 [ABATE_002018_21]


title: lib853 [ABATE_005006_21]


title: lib859 [ABATE_003006_21]


title: lib1490 [ABATE_002001_19]


title: lib885 [ABATE_003006_0_1]


title: lib871 [ABATE_001010_0]


title: lib878 [ABATE_002008_0]


title: lib1495 [ABATE_002008_19]


title: lib839 [ABATE_006001_21]


title: lib879 [ABATE_002012_0]


title: lib844 [ABATE_007012_21]


title: lib829 [ABATE_002012_21]


title: lib835 [ABATE_004005_21]


title: lib852 [ABATE_005007_21]


title: lib832 [ABATE_003005_21]


title: lib831 [ABATE_003003_21]


title: lib827 [ABATE_002004_21]


title: lib894 [ABATE_004005_0_2]


title: lib1497 [ABATE_002012_19]


title: lib873 [ABATE_002001_0]


title: HC182

status: Public on Nov 30 2018

data_processing:
Base-calling, demultiplexing, and filtering for reads containing base calls with phred scores <20 was performed using CASAVA v.1.8.1.
FASTQ reads were trimmed with the FASTQ Quality Trimmer tool v.1.0.0 in two steps: 1) hard-trimming to remove one 3'-end base; 2) quality trimming from both ends until minimum base quality for each read ≥ 30
Reads were aligned in Galaxy using Bowtie and TopHat v.1.4.0.
Read counts per Ensembl gene ID were estimated in Galaxy using htseq-count v.0.4.1
Genome_build: GRCh38
Supplementary_files_format_and_content: raw_counts_T1D_neutrophils.txt is a tab-delimited matrix. The first column contains Ensembl gene IDs. The remaining columns include raw read counts assigned for each library. Outlier samples have been removed but data have not been gene filtered or normalized.

source_name: purified neutrophils

extract_protocol:
Neutrophils were purified from whole blood using Ficoll-Hypaque gradient centrifugation. Cells were lysed in TRI Reagent (Sigma Aldrich), and RNA was extracted following the manufacturer’s protocol.
RNA quality was assessed using RNA electrophoresis (Agilent Bioanalyze 2100). All samples had RIN values >7. Sequencing libraries were constructed from total RNA using NEBNext Ultra RNA Library Prep Kit for Illumina (NEB Biolabs), followed by purification with AMPure XP Beads (Beckman Coulter)

tag: libraryid

tag: group

value: Healthy control

value: HC

tag: age


title: lib825 [ABATE_002001_21]


title: lib823 [ABATE_001010_21]


title: HC178


title: HC175


title: lib841 [ABATE_007005_21]


title: lib836 [ABATE_005001_21]


title: HC172


title: HC167


title: HC174


title: HC166


title: T1D317


title: T1D315


title: preT1D587


title: preT1D618


title: preT1D005


title: preT1D609


title: T1D291


title: T1D290


title: preT1D003


title: preT1D071


title: preT1D521


title: preT1D519


title: preT1D342


title: HC180


title: preT1D538


title: preT1D517


title: T1D240


title: HC110


title: preT1D526


title: HC104


title: HC115


title: preT1D515


title: HC113


title: preT1D082


title: preT1D024


title: HC099


title: preT1D054


title: HC101


title: preT1D019


title: preT1D010


title: preT1D006


title: preT1D022


title: HC100


title: preT1D014


title: F5_x8

status: Public on Oct 16 2018

city: New York

first: Varshini

last: Vasudevaraja

state: NY

address: 550 1st Avenue

department: Pathology

institute: NYU Langone Health

data_processing:
Base calling and demultiplexing was performed using Illumina bcl2fastq software.
The sequencing reads were aligned to the mouse genome (build mm10/GRCm38, respectively) using the splice-aware STAR aligner.
The featureCounts program was utilized to generate counts for each gene.
The raw counts were normalized using the DESeq2 R package.
Heatmaps and other statistics was performed using R3.2
Genome_build: mm10
Supplementary_files_format_and_content: CSV files contain raw and normalized counts for all genes and samples.

organism: Mus musculus

source_name: Nasal Lavage

growth_protocol: Infant mice were infected with S. pneumoniae at 4 days of life. S. pbeumoniae was grown to an OD of 1.

extract_protocol:
RNA was isolated from cells according to the RNeasy Qiagen Kit protocol
RNA libraries were prepared for sequencing using standard Illumina protocols

treatment_protocol: infant mice received intranasally 10^3 CFU of S. pneumoniae wild-type (WT) or pneumolysin mutant (PLY) strain in 3 uL PBS. Contral infant mice were inoculated with 3uL PBS respectively. Infant mice were euthanized at day 21 post-infection.

tag: tissue

value: Nasal Lavage

tag: strain

tag: infection

value: pneumolysin mutant

tag: time

value: Day 21 post-infection

tag: developmental stage

value: infant


title: F6_x8


title: F4_x8


title: F2_x8


title: E8_D9_X8

value: Mock


title: E4_x8

value: wild type


title: E5_x8


title: E3_x8


title: D4_x8


title: D5_x8


title: D1_x8


title: E2_x8


title: E1_x8


title: HC108


title: s_C48c_GeneCount

status: Public on Mar 08 2017

city: Rochester

first: Xuewei

last: Wang

address: 200 1st street

institute: Mayo Clinic

data_processing:
Base calling by CASAVA
Alignment by Tophat2 (v2.0.12)
Gene count by featureCounts (v1.4.4)
Normalization by edgeR(v2.6.2)
Genome_build: hg19
Supplementary_files_format_and_content: excel file for gene count

source_name: Cellular Dynamics iPSC-derived cardiomyocytes

growth_protocol: manufacturers protocol (Cellular Dynamics)

extract_protocol:
Qiagen RNAeasy minikit
Illumina TruSeq V2

treatment_protocol: 48 hours treatment with trastuzumab (100ug/ml) or lapatinib (2uM)

tag: cell type

value: iPSC-derived cardiomyocytes

value: untreated

tag: dose


title: CTRL_2

status: Public on Aug 30 2017

city: Brisbane

first: James

last: Hudson

state: QLD

address: 300 Herston Rd

country: Australia

institute: QIMR Berghofer Medical Research Institute

description:
EdgeR_Normalised_CPM
CountMatrix_Maturation_Ensembl_IDs

data_processing:
FASTQ files were quality trimmed with Trimmomatic
Reads were mapped to hg38 using RNA STAR
Count matrix was calculated with GENCODE v24 annotations using Htseq tools
EdgeR was used for all comparisons
Genome_build: GRCh38/hg38

molecule: polyA RNA

source_name: human cardiac organoids

growth_protocol: Briefly, HES3 were maintained as TypLE (ThermoFisher Scientific) passaged cultures using mTeSR-1 (Stem Cell Technologies)/Matrigel (Millipore). hPSCs were seeded at 2  104 cells/cm2 in Matrigel-coated flasks and cultured for 4 days using mTeSR-1. They were then differentiated into cardiac mesoderm using RPMI B27- medium (RPMI1640 GlutaMAX+ 2% B27 supplement without insulin, 200   M L-ascorbic acid 2 phosphate sesquimagnesium salt hydrate (Sigma) and 1% Penicillin/Streptomycin (all ThermoFisher Scientific) containing 5 ng/ml BMP-4 (RnD Systems), 9 ng/ml Activin A (RnD Systems), 5 ng/ml FGF-2 (RnD Systems) and 1   M CHIR99021 (Stem Cell Technologies) with daily medium exchange for 3 days. Subsequently, they were specified into a cardiomyocyte/stromal cell mixture using RPMI B27- containing 5   M IWP-4 (Stem Cell Technologies) followed by another 7 days of RPMI B27+ (RPMI1640 GlutaMAX + 2% B27 supplement with insulin, 200   M L-ascorbic acid 2 phosphate sesquimagnesium salt hydrate and 1% Penicillin/Streptomycin) with medium exchange every 2-3 days. The differentiated cells were then cultured in RPMI B27+ until digestion at 15 days using 0.2% collagenase type I (Sigma) in 20% fetal bovine serum (FBS) in PBS (with Ca2+ and Mg2+) for 60 min at 37  C, followed by 0.25% trypsin-EDTA for 10 min. The cells were filtered using a 100 mm mesh cell strainer (BD Biosciences), centrifuged at 300 x g for 3 min, and resuspended at the required density in CTRL medium:   -MEM GlutaMAX, 10% FBS, 200   M L-ascorbic acid 2 phosphate sesquimagnesium salt hydrate and 1% Penicillin/Streptomycin.

extract_protocol:
RNA was extracted using trizol and precipitated using glycogen according to manufacturers instructions. Clean-up and DNAse protocols was performed using Rneasy MinElute Cleanup Kit (QIAGEN)
RNA-seq libraries were created with TruSeq Stranded Total RNA kits (Illumina) and read with HiSeq SR Cluster v4 kit (Illumina) on a HiSeq 2500 sequencer. Barcode information:  <sample_name>_<flowcell_ID>_<index >_<lane>_<readNum>_fastq.gz

treatment_protocol: human cardiac organoids were cultured in either CTRL or MM media (DMEM without glucose, glutamine and phenol red (ThermoFisher Scientific) supplemented with 4% B27 (without insulin), 1% GlutaMAX, 200 μM L-ascorbic acid 2 phosphate sesquimagnesium salt hydrate and 1% Penicillin/Streptomycin, 1mM glucose and 100uM palmitatic acid) for 11 days and then harvested

value: ES-cell derived human cardiac organoids


title: CTRL_1


title: CTRL_4


title: CTRL_3


title: S31-B (ii)

status: Public on Sep 19 2016

data_processing:
Base-calling was performed automatically in Illumina BaseSpace after sequencing; FASTQ reads were trimmed in Galaxy in two steps: 1) hard-trimming to remove 1 3'-end base (FASTQ Trimmer tool, v.1.0.0); 2) quality trimming from both ends until minimum base quality for each read >= 30 (FASTQ Quality Trimmer tool, v.1.0.0).
Reads were aligned in Galaxy (Tophat for Illumina tool, v.1.5.0) using bowtie (v.0.12.7) and TopHat (v.1.4.0) .
Read counts per Ensembl gene ID were estimated in Galaxy (htseq-count tool, v.0.4.1) using htseq-count (v.0.5.4p3).
Genes expressed (trimmed mean of M-values >1) in less than 10% of all samples were removed. Data normalization (TMM) and differential expression analysis to compare stimulated vs. unstimulated cells were performed in R using the "edgeR" package.
Genome_build: GRCh38
Supplementary_files_format_and_content: IL6_CD4_T1D_rawCounts.csv: comma-separated matrix – first column contains Ensembl gene ID, remaining columns include raw read counts assigned for each library. Data represents all processing steps up to read counting, not including gene filtering, normalization, and analysis with edgeR.

source_name: CD4+CD25- T cells purified from PBMC using magnetic- activated cell sorting (MACS)

extract_protocol:
Cells were directly lysed in RLT lysis buffer (Qiagen) supplemented with 1% 2-mercaptoethanol and then extracted using the RNeasy mini kit with RNase–free DNase treatment (Qiagen).
Sequencing libraries were constructed from total RNA using the TruSeq RNA Sample Preparation V2 kit (Illumina)

treatment_protocol: CD4+CD25- T cells were purified from thawed PBMC using MACS (Miltenyi); 2-3 Mio cells/well of a 96-well round bottom tissue culture plate (Nunc) were  left untreated or were stimulated with 10ng/ml recombinant IL-6 (BD Pharmingen) in complete RPMI medium (10% FCS/PenStrep/L-Glut/SodPyr) for 24h at 37C

value: 10 ng/ml IL-6

value: 24 hours

tag: cells

value: MACS sorted CD4+CD25- T cells from PBMC


title: S18-A (ii)


title: S17-B (ii)


title: F3_x8


title: Human_adult_heart

source_name: Adult human hear tissue

extract_protocol:
RNA sourced from Clontech
RNA-seq libraries were created with TruSeq Stranded Total RNA kits (Illumina) and read with HiSeq SR Cluster v4 kit (Illumina) on a HiSeq 2500 sequencer. Barcode information:  <sample_name>_<flowcell_ID>_<index >_<lane>_<readNum>_fastq.gz

value: Human heart tissue isolated from 3 pooled samples


title: s_C48b_GeneCount


title: S10-A (ii)


title: S41-A (ii)


title: S16-A (ii)


title: S32-B (ii)


title: S18-A

value: unstimulated


title: S17-B


title: D3_x8


title: S10-A


title: S31-B


title: S16-A


title: S32-B


title: s_C48a_GeneCount


title: Small intestinal Spheroids Sample1

status: Public on May 11 2016

city: Brussels

first: Frederick

last: Libert

address: 808 route de Lennik

department: IRIBHM

country: Belgium

institute: ULB

description: E15.5 embryo

data_processing:
Approximately 25 million of paired-end reads per sample were mapped against the mouse reference genome (GRCm38.p4/mm10) using STAR software to generate read alignments for each sample.
Annotations Mus_musculus.GRCm38.79.gtf were obtained from ftp.Ensembl.org.
After transcripts assembling, gene level counts were obtained using HTSeq.
Genome_build: GRCm38.p4/mm10
Supplementary_files_format_and_content: tab-delimited text files include CPM (count per million) values for each Sample.

source_name: Small intestinal spheroids

growth_protocol: Ex vivo cultures: Embryonic stomach and intestine tissue were dissociated and epithelial samples were cultured according to the protocol reported by Sato et al (2010). Specifically, the culture medium used for growing gastric spheroids consisted in Advanced-DMEM/F12 medium supplemented with 2 mM L-Glutamine, N2 and B27 w/o vit.A (Invitrogen), gentamycin, penicillin-streptomycin cocktail, 10 mM HEPES, and 1 mM N acetyl cysteine. Growth factors were added at a final concentration of : 50 ng/ml EGF and 100 ng/ml Noggin (both from Peprotech), and 100 ng/ml CHO-derived R-spondin1 (R&D System). Culture medium was changed each other day and after 5-6 days in culture, spheroids were harvested, mechanically dissociated and replated in fresh Matrigel (BD).                                                                                Isolation of Trop2+ve and Lgr5-GFP+ve cells from fetal stomach and adult pyloric stomach from Lgr5-DTR, after Lgr5 cells ablation, was performed by FACS.   Proximal and distal areas of E14.5 embryos stomach (pool of 12, 18 and 19 embryos from given litter per experiment, n=3 independent experiments), were completely dissociated with the Stem Pro accutase cell dissociation reagent (Thermo electron) at 37°C and passed through a 40-μm nylon cell strainer (Greiner).   For adults Lgr5-DTR, antral glands were isolated as previously described by Barker et al. (Barker et al., 2010). Glands were after incubated in Stem Pro accutase cell dissociation reagent until total dissociation and passed through a 40-μm nylon cell strainer.  Cells from both types of isolation procedures were incubated with fluorochrome-conjugated anti-Trop2-APC antibody, or the relevant isotype control (R&D systems) in PBS-2% BSA-2mM EDTA for 45 min on ice and sorted by using the Facs Aria I (BD Biosciences). Lgr5-GFP+ve cells were directly sorted using the FITC channel. Sorted cells were directly collected for RNA analysis over Qiazol lysis reagent (Qiagen).

extract_protocol:
900 ng of total RNA extracted with the miRNA isolation kit (Ambion, Life Technologies), were checked for quality by Bioanalyzer (Agilent).
TruSeq® Stranded mRNA libraries were prepared for sequencing using standard Illumina protocols.
paired-end libraries 2x 100 bases or 2x 125 bases

treatment_protocol: Adult Lgr5-DTR heterozygous mice were injected with diphetheria toxin (a dose of 50 µg/kg of body weight) at day 1, 2 and 4. Stomach were harvested at day5 for FACS sorting.

tag: strain background

value: mixed

tag: developemental stage/age

value: E15.5 embryo

value: small intestine

value: ex vivo epithelial progenitors

tag: passages

value: Passage 2 day 6


title: Small intestinal Organoids Sample2

description: Adult (3 month-old) intestine

source_name: Small intestinal Organoids

value: Adult (3 month-old)

value: ex vivo  organoids

value: Passage 1 day 5


title: Small intestinal Spheroids Sample3

description: E15.5 embryo

value: Passage 3 day 3


title: Small intestinal Spheroids Sample2

description: E15.5 embryo


title: hfv rep 1

status: Public on May 12 2015

city: Seattle

first: Hannele

last: Ruohola-Baker

address: UW Medicine at South Lake Union, S580, 850 Republican Street

department: Department of Biochemistry

institute: University of Washington

description: results file: mrna-read-counts.tsv

data_processing:
Illumina Casava1.7 software used for basecalling.
Aligned to hg19 using rna-star 2.3.0
Reads counted for genes annotated in AceView Aug10
miRNA read counts generated with miRExpress 2.1.4
Genome_build: hg19
Supplementary_files_format_and_content: tab delimited mRNA/miRNA read counts

source_name: Ventricle

extract_protocol:
Total RNA samples were extracted using RNAeasy mini kit
RNA and Small RNA libraries were prepared independently using Truseq library preparation kits (Illumina) following the manufacturer's protocols.

value: Fetal ventricle

tag: time point

value: 90 days (approx)


title: adult rep 1

description: results file: mrna-read-counts.tsv

source_name: Heart

value: Adult heart

value: adult


title: adult rep 2

description: results file: mrna-read-counts.tsv


title: Small intestinal Organoids Sample1

description: E15.5 embryo

value: Passage 4 day 5


title: hfa rep 2

description: results file: mrna-read-counts.tsv

source_name: Atrium

value: Fetal atrium


title: hfv rep 2

description: results file: mrna-read-counts.tsv


title: FXRChIP_MVEH8

status: Public on Jan 27 2016

city: Innsbruck

first: Jose Miguel

last: Ramos Pittol

address: Innrain 80-82

department: Institute of Biochemistry

country: Austria

institute: University of Innsbruck

library_source: genomic

data_processing:
Sequencing reads were mapped against the reference genome (mm9 assembly, NCBI37) using BWA package ( mem –t 7 –c 100 –M –R ).
Peaks were called using MACS 1.4 package (p 4, nomodel, nolambda, shiftsize=150) with each respective input as background
Wig files were constructed with custom perl script counts on extended reads on 50bp intervals
Genome_build: mm9
Supplementary_files_format_and_content: .wig.gz WIG files, scores represent read counts over 50bp intervals
Supplementary_files_format_and_content: .bed.gz Peak and Summit Intervals

molecule: genomic DNA

source_name: Liver tissue

extract_protocol:
Lysates were clarified from sonicated nuclei foxated with Formaldehyde/DSG, and histone-DNA complexes were isolated with antibody.
Libraries were prepared according to the instructions accompanyindg the SOLiD ChIP-seq kit for library preparation. Libraries were sequenced on the SOLiD 5500 WG following the manufacturer's protocols.

treatment_protocol: Male mice were treated daily by oral gavage for 7 days with OCA/INT-747 (10mg/kg/day) or vehicle (1% methyl cellulose).

tag: chip antibody

value: FXR (SantaCruz, sc-13063)

tag: treatment

value: vehicle (1% methyl cellulose)

tag: gender

value: male


title: low fat diet

status: Public on May 11 2012

city: Shreveport

first: Tara

middle: M

last: Henagan

state: LA

address: 1501 Kings Hwy

department: Medical School

institute: Louisiana State University Health Sciences Center - Shreveport

data_processing:
Basecalls were performed using 5500 Series Genetic Analyzers Instrument Control Software v1.2.
Reads were trimmed for the adaptor sequence and aligned to the UCSC mm9 genome using Bowtie version 0.12.7 with the following parameters: - n 2 -l 28 - e 40.
Peaks were called using HOMER software using the following parameters: -fdr 0.05 -size 147 -minDist 162 -tagThreshold 4 -L 0 -C 0 -F 0 -o (read count ≥4; false discovery rate = 0.05; peak size = 147; minimum distance between peaks = 162; genome size = 2,000,000,000; number of tags used for normalization = 10,000,000; size of region used for local filtering = 10,000; Poisson p-value over local region = 1.00e-04).
Genome_build: mm9
Supplementary_files_format_and_content: fasta and qual files were generated using 5500 Series Genetic Analyzers Instrument Control Software v1.2 and are formatted as such:  (column 1), (column 2), (column 3). Text files were generated from HOMER and are formatted as follows: PeakID (column 1), chromosome (column 2), start index (column 3), end index (column 4), strand (column 5), peak score (column 6), focus ratio/region size (column 7), annotation (column 8), detailed annotation (column 9), distance to transcription start site (column 10), nearest promoter ID (column 11), Entrez ID (column 12), nearest Unigene (column 13), nearest Refseq (column 14), nearest Ensembl (column 15), gene name (column 16), gene alias (column 17), gene description (column 18), CpG% (column 19), GC% (column 20).

source_name: quadriceps muscle

growth_protocol: Mice were purchased from Jackson laboratories at 4 weeks of age and subsequently housed in Comparative Biology at the Pennington Biomedical Research Center in thermoneutral conditions (22-23°C) with ad libitum water and food.

extract_protocol: After 10 wks on their respective diets, mice were euthanized and quadriceps muscle was excised and snap frozen in liquid nitrogen. Due to the homogeneity of the tissue, quadriceps muscle was ground under liquid nitrogen with a motor and pestle to create a homogenous sample. 50mg of powdered tissue was then used to isolate nuclei via dounce homogenization in a 0.25M sucrose buffer (0.25M sucrose, in 10mM Tris-acetate, 1mM EDTA, 1mM DTT, 1mM sodium orthovanadate and a 1X protease inhibitor tablet) on ice. Isolated nuclei were resuspended in digestion buffer (0.25M sucrose buffer plus 4mM MgCl2 and 1mM CaC2) and incubated at 37°C with MNase for 15 min (90-95% partial digestion), as previously described. Native chromatin without cross-linking was released from nuclei by incubation a lysis buffer containing 50mM Tris, 10mM EDTA, 1% SDS and a protease inhibitor cocktail. Mononucleosomal DNA was collected and pooled from 5 mice per treatment group. Mononucleosomal and a control undigested genomic DNA were purified by EtOH precipitation after an overnight digestion with 0.1mg/mL of protease K at 37°C. For DNA sequencing, nucleosomal DNA was further modified following the SOLiD sequencing protocol and sequenced with a SOLiD 5500xl Genetic Analyzer (Applied Biosystems).

treatment_protocol: Mice were placed on respective diets at 5 weeks of age and maintained in thermoneutral conditions with ad libitum water and food for 10 weeks before euthanization and muscle extraction.

value: 15 weeks

value: quadriceps muscle

value: HF


title: S41-A

value: unstimulated

value: 24 hours

value: MACS sorted CD4+CD25- T cells from PBMC


title: high fat diet + NaB

value: HF+NaB


title: LMNA-KD NT

status: Public on Jul 11 2013

type: RNA

city: Roma

first: Ivan

last: Arisi

address: viale Regina Elena 295

department: Bioinformatics Facility

country: Italy

institute: European Brain Research Institute

description: LMNA-KD cells_untreated

hyb_protocol: One-color mixes of labelled cRNA pairs were hybridized to 4×44K whole human genome oligonucleotide microarray (Agilent G4112F, 41000 unique probes), at 65°C for 17 hours using Agilent’s Gene Expression Hybridization Kit. The hybridized microarrays were disassembled at room temperature in Agilent Gene Expression Wash Buffer 1. After the disassembly, the microarrays were washed in Gene Expression Buffer 1 for one minute at room temperature, followed by washing with Gene Expression Wash Buffer 2 for one minute at 37C. The microarrays were then treated with acetonitrile for one minute at room temperature.

scan_protocol: Post-hybridization image acquisition was accomplished using the Agilent Scanner G2564B. Data extraction from the 20 bits TIFF images was accomplished by Agilent Feature Extraction ver 10.1 software using the standard Agilent one-color gene expression extraction protocol (GE1_107_Sep09).

data_processing: The gProcessedSignal data column of the Feature Extraction *.txt output file was used, containing the median signals corrected by spatial and multiplicative detrend. Data quality filtering was performed using Agilent GeneSpring GX 11.0, discarding features with the Feature Extraction flag gIsWellAboveBG=0 in any sample, wich is a statistical method approximately equivalent to discarding features with a Signal/Noise ratio smaller than 2.0-3.0, where Signal = (median of the spot - median spot background level) and Noise is the Standard Deviation of the median spot background. Differential gene lists were obtained from filtered data using Microsoft Excel. A threshold of 350.0 in the absolute expression level was chosen to obtain a higher stringency and a smaller relative error of the signal. Differentially expressed genes were identified as those showing an average fold change ratio >1.5 or <1/1.5 in the linear scale.

source_name: LMNA-KD cells_untreated

label_protocol: The cyanine 3-CTP labeled cRNA was prepared using the Agilent Low Input Linear Amplification Kit, following the standard one-color Agilent protocol

growth_protocol: SHSY5Y cells were grown in a 1:1 mixture of Eagle's Minimum Essential Medium and F12 Medium (Gibco, Grand Island, NY, USA) supplemented with 10% fetal bovine serum (FBS, Hyclone), 2 mM L-glutamine, 0.5% non-essential amino acids, 0.5% sodium pyruvate and 1% penicillin and streptomycin in a fully-humidified incubator containing 5% CO2 at 37C.

extract_protocol: Cells were seeded in complete medium, harvested after the different treatments and total RNA was isolated from each sample using NucleoSpin RNA II silica columns (Macherey-Nagel).

treatment_protocol: For differentiation experiments cells were seeded at a density of 5×103 cells/cm2. The following day cells were induced to differentiate by 10 µM retinoic acid (RA) in a “differentiation medium” (DM) composed by 50% fresh and 50% conditioned culture medium. Cells were fed after 3 days with DM containing fresh RA. Untreated cells (NT) were harvested after 3 days of growth. RA-treated cells were harvested after 5 days of RA treatment (corresponding to 6 days after seeding).

tag: cell line

value: Human malignant neuroblastoma

tag: genotype/variation

value: infected with a silencing vector for LMNA (LMNA-KD)


title: Anti-H3K4Me2 ChIP Kdm1a KD

status: Public on Mar 29 2012

city: Manchester

first: Tim

middle: C

last: Somervaille

state: Lancashire

address: Wilmslow Road

country: United Kingdom

institute: Cancer Research UK Manchester Institute

data_processing:
Sequencing reads were aligned to the genome (Mus_musculus NCBIM37) using Bowtie (Langmead et al. 2009) with default parameters. Total reads per sample ranged from 2.6 to 6.6 x10^6. Reads that mapped to multiple loci were discarded and the alignments from three technical replicate sets (anti-H3K9Me2 Kdm1a KD) were pooled. Subsequent analysis was performed in R and Bioconductor (Gentleman et al. 2004). Data were then segmented according to annotated transcription start- and end-sites (TSS; TES), as defined by ENSEMBL version 64 and supplied by the annmap database (Yates et al. 2007). Each gene was split into 10 equally spaced bins between the TSS and TES and the average read depth calculated for each region (expressed in reads per kilobase). Similar data were computed for two additional regions 10kB-2.5kB and 2.5kB-0kB upstream of the TSS and the equivalent regions downstream of the TES. In total, 14 regions per gene were considered. In order to explore global changes in histone methylation across the genome of each sample, four sets of genes were considered: MLL-AF9 target genes (n=114), and the remaining protein coding genes (n=15806), stratified into three groups by expression level (0 – 30th percentile, 30th – 70th percentile, 70th – 100th percentile), and the average read depth per bin computed for each set.

BED file: The .BED file contains reads uniquely mapped by Bowtie to the mouse genome for one sample, indicated by the file name. Each line in the .BED file corresponds to one read, showing the mapped location in the mouse genome, i.e. the chromosome, the start coordinate (minus 1), the end coordinate, and the strand.

TXT file: File has 16 columns. On the left is the Ensembl gene ID for the 15920 protein-coding genes analyzed. The next column indicates which of the four analyzed gene sets each gene belongs to (MLL- MLL-AF9 bound; TOP - top 30% most highly expressed non-MLL-AF9 bound genes; MIDDLE - middle 40% expressed non-MLL-AF9 bound genes; BOTTOM - bottom 30% expressed non-MLL-AF9 bound genes). The 14 columns that follow indicate for each gene the ChIP-Seq signal in each of 14 bins, as described in the data processing section. ChIP-Seq signal is defined as mapped reads per kilobase per million reads.

Genome Build:
test_ShA4_K4_2_TS2_11.bed: NCBI Build 37
test_shA4_K4_Me2.txt: ENSEMBL version 64

source_name: Kdm1a KD AML cells, H3K4Me2 ChIP

growth_protocol: For experiments involving viral infection of cryopreserved AML cells, cells were thawed, spinoculated as above and cultured overnight with viral supernatant containing 5% X63 supernatant (Karasuyama and Melchers, 1988).

extract_protocol: Chromatin shearing was performed using a Covaris S2 system (Covaris, Woburn, MA) to 100-300 base pairs, according to manufacturer’s instructions. ChIP-grade antibodies were anti-H3K4Me2, anti-H3K4Me3, anti-H3K9Me2 and anti-H3K9Me3 (all from Cell Signaling). To prepare for next-generation sequencing, libraries were prepared from 2ng immunoprecipitated DNA fragments using the 5500 Series Fragment Library Core Kit and Barcode Adaptors (Applied Biosystems), according to the 5500 SOLiD ‘ALPHA’ ChIP Seq Library Preparation Protocol (Applied Biosystems), with 15 cycles of amplification. Library molarities were determined by Agilent Bioanalyser analysis and then libraries were pooled in equimolar ratios. Emulsion PCR was carried out using the EZBead System (Applied Biosystems) according to the manufacturer’s instructions. An E80 scale emulsion was prepared using 0.4pM of the pooled libraries and the resulting templated beads were modified for 4hrs at 37 C. Next-generation sequencing was carried out on a 5500XL Genetic Analyzer System (Applied Biosystems), according to the manufacturer’s instructions, to generate 50 base pair forward reads.

treatment_protocol: Kdm1a KD or control murine MLL-AF9 AML cells were FACS purified 42 hours following lentiviral infection, with GFP as the selectable marker, and subjected to ChIP-Seq.

tag: background/strain

value: Kdm1a KD

value: MLL-AF9 AML cells

tag: antibody vendor

value: Cell Signaling

tag: antibody catalog #

tag: antibody lot#


title: LMNA-KD RA

description: LMNA-KD cells_treated with retinoic acid (RA)


title: Anti-H3K9Me2 ChIP Kdm1a KD

data_processing:
Sequencing reads were aligned to the genome (Mus_musculus NCBIM37) using Bowtie (Langmead et al. 2009) with default parameters. Total reads per sample ranged from 2.6 to 6.6 x10^6. Reads that mapped to multiple loci were discarded and the alignments from three technical replicate sets (anti-H3K9Me2 Kdm1a KD) were pooled. Subsequent analysis was performed in R and Bioconductor (Gentleman et al. 2004). Data were then segmented according to annotated transcription start- and end-sites (TSS; TES), as defined by ENSEMBL version 64 and supplied by the annmap database (Yates et al. 2007). Each gene was split into 10 equally spaced bins between the TSS and TES and the average read depth calculated for each region (expressed in reads per kilobase). Similar data were computed for two additional regions 10kB-2.5kB and 2.5kB-0kB upstream of the TSS and the equivalent regions downstream of the TES. In total, 14 regions per gene were considered. In order to explore global changes in histone methylation across the genome of each sample, four sets of genes were considered: MLL-AF9 target genes (n=114), and the remaining protein coding genes (n=15806), stratified into three groups by expression level (0 – 30th percentile, 30th – 70th percentile, 70th – 100th percentile), and the average read depth per bin computed for each set.

BED file: The .BED file contains reads uniquely mapped by Bowtie to the mouse genome for one sample, indicated by the file name. Each line in the .BED file corresponds to one read, showing the mapped location in the mouse genome, i.e. the chromosome, the start coordinate (minus 1), the end coordinate, and the strand.

TXT file: File has 16 columns. On the left is the Ensembl gene ID for the 15920 protein-coding genes analyzed. The next column indicates which of the four analyzed gene sets each gene belongs to (MLL- MLL-AF9 bound; TOP - top 30% most highly expressed non-MLL-AF9 bound genes; MIDDLE - middle 40% expressed non-MLL-AF9 bound genes; BOTTOM - bottom 30% expressed non-MLL-AF9 bound genes). The 14 columns that follow indicate for each gene the ChIP-Seq signal in each of 14 bins, as described in the data processing section. ChIP-Seq signal is defined as mapped reads per kilobase per million reads.

Genome Build:
test_ShA4_K9_2_TS2_13_15_16.bed: NCBI Build 37
test_shA4_K9_Me2.txt: ENSEMBL version 64

source_name: Kdm1a KD AML cells, H3K9Me2 ChIP


title: Anti-H3K9Me3 ChIP Kdm1a KD

data_processing:
Sequencing reads were aligned to the genome (Mus_musculus NCBIM37) using Bowtie (Langmead et al. 2009) with default parameters. Total reads per sample ranged from 2.6 to 6.6 x10^6. Reads that mapped to multiple loci were discarded and the alignments from three technical replicate sets (anti-H3K9Me2 Kdm1a KD) were pooled. Subsequent analysis was performed in R and Bioconductor (Gentleman et al. 2004). Data were then segmented according to annotated transcription start- and end-sites (TSS; TES), as defined by ENSEMBL version 64 and supplied by the annmap database (Yates et al. 2007). Each gene was split into 10 equally spaced bins between the TSS and TES and the average read depth calculated for each region (expressed in reads per kilobase). Similar data were computed for two additional regions 10kB-2.5kB and 2.5kB-0kB upstream of the TSS and the equivalent regions downstream of the TES. In total, 14 regions per gene were considered. In order to explore global changes in histone methylation across the genome of each sample, four sets of genes were considered: MLL-AF9 target genes (n=114), and the remaining protein coding genes (n=15806), stratified into three groups by expression level (0 – 30th percentile, 30th – 70th percentile, 70th – 100th percentile), and the average read depth per bin computed for each set.

BED file: The .BED file contains reads uniquely mapped by Bowtie to the mouse genome for one sample, indicated by the file name. Each line in the .BED file corresponds to one read, showing the mapped location in the mouse genome, i.e. the chromosome, the start coordinate (minus 1), the end coordinate, and the strand.

TXT file: File has 16 columns. On the left is the Ensembl gene ID for the 15920 protein-coding genes analyzed. The next column indicates which of the four analyzed gene sets each gene belongs to (MLL- MLL-AF9 bound; TOP - top 30% most highly expressed non-MLL-AF9 bound genes; MIDDLE - middle 40% expressed non-MLL-AF9 bound genes; BOTTOM - bottom 30% expressed non-MLL-AF9 bound genes). The 14 columns that follow indicate for each gene the ChIP-Seq signal in each of 14 bins, as described in the data processing section. ChIP-Seq signal is defined as mapped reads per kilobase per million reads.

Genome Build:
test_ShA4_K9_3_TS2_14.bed: NCBI Build 37
test_shA4_K9_Me3.txt: ENSEMBL version 64

source_name: Kdm1a KD AML cells, H3K9Me3 ChIP


title: Anti-H3K9Me3 ChIP control

data_processing:
Sequencing reads were aligned to the genome (Mus_musculus NCBIM37) using Bowtie (Langmead et al. 2009) with default parameters. Total reads per sample ranged from 2.6 to 6.6 x10^6. Reads that mapped to multiple loci were discarded and the alignments from three technical replicate sets (anti-H3K9Me2 Kdm1a KD) were pooled. Subsequent analysis was performed in R and Bioconductor (Gentleman et al. 2004). Data were then segmented according to annotated transcription start- and end-sites (TSS; TES), as defined by ENSEMBL version 64 and supplied by the annmap database (Yates et al. 2007). Each gene was split into 10 equally spaced bins between the TSS and TES and the average read depth calculated for each region (expressed in reads per kilobase). Similar data were computed for two additional regions 10kB-2.5kB and 2.5kB-0kB upstream of the TSS and the equivalent regions downstream of the TES. In total, 14 regions per gene were considered. In order to explore global changes in histone methylation across the genome of each sample, four sets of genes were considered: MLL-AF9 target genes (n=114), and the remaining protein coding genes (n=15806), stratified into three groups by expression level (0 – 30th percentile, 30th – 70th percentile, 70th – 100th percentile), and the average read depth per bin computed for each set.

BED file: The .BED file contains reads uniquely mapped by Bowtie to the mouse genome for one sample, indicated by the file name. Each line in the .BED file corresponds to one read, showing the mapped location in the mouse genome, i.e. the chromosome, the start coordinate (minus 1), the end coordinate, and the strand.

TXT file: File has 16 columns. On the left is the Ensembl gene ID for the 15920 protein-coding genes analyzed. The next column indicates which of the four analyzed gene sets each gene belongs to (MLL- MLL-AF9 bound; TOP - top 30% most highly expressed non-MLL-AF9 bound genes; MIDDLE - middle 40% expressed non-MLL-AF9 bound genes; BOTTOM - bottom 30% expressed non-MLL-AF9 bound genes). The 14 columns that follow indicate for each gene the ChIP-Seq signal in each of 14 bins, as described in the data processing section. ChIP-Seq signal is defined as mapped reads per kilobase per million reads.

Genome Build:
control_ShX_K9_3_TS2_7.bed: NCBI Build 37
control_shX_K9_Me3.txt: ENSEMBL version 64

source_name: Control MLL-AF9 AML cells, H3K9Me3 ChIP

value: control


title: Input genomic DNA Kdm1a KD

data_processing:
Sequencing reads were aligned to the genome (Mus_musculus NCBIM37) using Bowtie (Langmead et al. 2009) with default parameters. Total reads per sample ranged from 2.6 to 6.6 x10^6. Reads that mapped to multiple loci were discarded and the alignments from three technical replicate sets (anti-H3K9Me2 Kdm1a KD) were pooled. Subsequent analysis was performed in R and Bioconductor (Gentleman et al. 2004). Data were then segmented according to annotated transcription start- and end-sites (TSS; TES), as defined by ENSEMBL version 64 and supplied by the annmap database (Yates et al. 2007). Each gene was split into 10 equally spaced bins between the TSS and TES and the average read depth calculated for each region (expressed in reads per kilobase). Similar data were computed for two additional regions 10kB-2.5kB and 2.5kB-0kB upstream of the TSS and the equivalent regions downstream of the TES. In total, 14 regions per gene were considered. In order to explore global changes in histone methylation across the genome of each sample, four sets of genes were considered: MLL-AF9 target genes (n=114), and the remaining protein coding genes (n=15806), stratified into three groups by expression level (0 – 30th percentile, 30th – 70th percentile, 70th – 100th percentile), and the average read depth per bin computed for each set.

BED file: The .BED file contains reads uniquely mapped by Bowtie to the mouse genome for one sample, indicated by the file name. Each line in the .BED file corresponds to one read, showing the mapped location in the mouse genome, i.e. the chromosome, the start coordinate (minus 1), the end coordinate, and the strand.

TXT file: File has 16 columns. On the left is the Ensembl gene ID for the 15920 protein-coding genes analyzed. The next column indicates which of the four analyzed gene sets each gene belongs to (MLL- MLL-AF9 bound; TOP - top 30% most highly expressed non-MLL-AF9 bound genes; MIDDLE - middle 40% expressed non-MLL-AF9 bound genes; BOTTOM - bottom 30% expressed non-MLL-AF9 bound genes). The 14 columns that follow indicate for each gene the ChIP-Seq signal in each of 14 bins, as described in the data processing section. ChIP-Seq signal is defined as mapped reads per kilobase per million reads.

Genome Build:
test_ShA4_input_TS2_8.bed: NCBI Build 37
Test_shA4_INPUT.txt: ENSEMBL version 64

source_name: Kdm1a KD AML cells, input


title: Anti-H3K4Me3 ChIP control

data_processing:
Sequencing reads were aligned to the genome (Mus_musculus NCBIM37) using Bowtie (Langmead et al. 2009) with default parameters. Total reads per sample ranged from 2.6 to 6.6 x10^6. Reads that mapped to multiple loci were discarded and the alignments from three technical replicate sets (anti-H3K9Me2 Kdm1a KD) were pooled. Subsequent analysis was performed in R and Bioconductor (Gentleman et al. 2004). Data were then segmented according to annotated transcription start- and end-sites (TSS; TES), as defined by ENSEMBL version 64 and supplied by the annmap database (Yates et al. 2007). Each gene was split into 10 equally spaced bins between the TSS and TES and the average read depth calculated for each region (expressed in reads per kilobase). Similar data were computed for two additional regions 10kB-2.5kB and 2.5kB-0kB upstream of the TSS and the equivalent regions downstream of the TES. In total, 14 regions per gene were considered. In order to explore global changes in histone methylation across the genome of each sample, four sets of genes were considered: MLL-AF9 target genes (n=114), and the remaining protein coding genes (n=15806), stratified into three groups by expression level (0 – 30th percentile, 30th – 70th percentile, 70th – 100th percentile), and the average read depth per bin computed for each set.

BED file: The .BED file contains reads uniquely mapped by Bowtie to the mouse genome for one sample, indicated by the file name. Each line in the .BED file corresponds to one read, showing the mapped location in the mouse genome, i.e. the chromosome, the start coordinate (minus 1), the end coordinate, and the strand.

TXT file: File has 16 columns. On the left is the Ensembl gene ID for the 15920 protein-coding genes analyzed. The next column indicates which of the four analyzed gene sets each gene belongs to (MLL- MLL-AF9 bound; TOP - top 30% most highly expressed non-MLL-AF9 bound genes; MIDDLE - middle 40% expressed non-MLL-AF9 bound genes; BOTTOM - bottom 30% expressed non-MLL-AF9 bound genes). The 14 columns that follow indicate for each gene the ChIP-Seq signal in each of 14 bins, as described in the data processing section. ChIP-Seq signal is defined as mapped reads per kilobase per million reads.

Genome Build:
control_ShX_K4_3_TS2_5.bed: NCBI Build 37
control_shX_K4_Me3.txt: ENSEMBL version 64

source_name: Control MLL-AF9 AML cells, H3K4Me3 ChIP


title: Anti-H3K4Me3 ChIP Kdm1a KD

data_processing:
Sequencing reads were aligned to the genome (Mus_musculus NCBIM37) using Bowtie (Langmead et al. 2009) with default parameters. Total reads per sample ranged from 2.6 to 6.6 x10^6. Reads that mapped to multiple loci were discarded and the alignments from three technical replicate sets (anti-H3K9Me2 Kdm1a KD) were pooled. Subsequent analysis was performed in R and Bioconductor (Gentleman et al. 2004). Data were then segmented according to annotated transcription start- and end-sites (TSS; TES), as defined by ENSEMBL version 64 and supplied by the annmap database (Yates et al. 2007). Each gene was split into 10 equally spaced bins between the TSS and TES and the average read depth calculated for each region (expressed in reads per kilobase). Similar data were computed for two additional regions 10kB-2.5kB and 2.5kB-0kB upstream of the TSS and the equivalent regions downstream of the TES. In total, 14 regions per gene were considered. In order to explore global changes in histone methylation across the genome of each sample, four sets of genes were considered: MLL-AF9 target genes (n=114), and the remaining protein coding genes (n=15806), stratified into three groups by expression level (0 – 30th percentile, 30th – 70th percentile, 70th – 100th percentile), and the average read depth per bin computed for each set.

BED file: The .BED file contains reads uniquely mapped by Bowtie to the mouse genome for one sample, indicated by the file name. Each line in the .BED file corresponds to one read, showing the mapped location in the mouse genome, i.e. the chromosome, the start coordinate (minus 1), the end coordinate, and the strand.

TXT file: File has 16 columns. On the left is the Ensembl gene ID for the 15920 protein-coding genes analyzed. The next column indicates which of the four analyzed gene sets each gene belongs to (MLL- MLL-AF9 bound; TOP - top 30% most highly expressed non-MLL-AF9 bound genes; MIDDLE - middle 40% expressed non-MLL-AF9 bound genes; BOTTOM - bottom 30% expressed non-MLL-AF9 bound genes). The 14 columns that follow indicate for each gene the ChIP-Seq signal in each of 14 bins, as described in the data processing section. ChIP-Seq signal is defined as mapped reads per kilobase per million reads.

Genome Build:
test_ShA4_K4_3_TS2_12.bed: NCBI Build 37
test_shA4_K4_Me3.txt: ENSEMBL version 64

source_name: Kdm1a KD AML cells, H3K4Me3 ChIP


title: Anti-H3K9Me2 ChIP control

data_processing:
Sequencing reads were aligned to the genome (Mus_musculus NCBIM37) using Bowtie (Langmead et al. 2009) with default parameters. Total reads per sample ranged from 2.6 to 6.6 x10^6. Reads that mapped to multiple loci were discarded and the alignments from three technical replicate sets (anti-H3K9Me2 Kdm1a KD) were pooled. Subsequent analysis was performed in R and Bioconductor (Gentleman et al. 2004). Data were then segmented according to annotated transcription start- and end-sites (TSS; TES), as defined by ENSEMBL version 64 and supplied by the annmap database (Yates et al. 2007). Each gene was split into 10 equally spaced bins between the TSS and TES and the average read depth calculated for each region (expressed in reads per kilobase). Similar data were computed for two additional regions 10kB-2.5kB and 2.5kB-0kB upstream of the TSS and the equivalent regions downstream of the TES. In total, 14 regions per gene were considered. In order to explore global changes in histone methylation across the genome of each sample, four sets of genes were considered: MLL-AF9 target genes (n=114), and the remaining protein coding genes (n=15806), stratified into three groups by expression level (0 – 30th percentile, 30th – 70th percentile, 70th – 100th percentile), and the average read depth per bin computed for each set.

BED file: The .BED file contains reads uniquely mapped by Bowtie to the mouse genome for one sample, indicated by the file name. Each line in the .BED file corresponds to one read, showing the mapped location in the mouse genome, i.e. the chromosome, the start coordinate (minus 1), the end coordinate, and the strand.

TXT file: File has 16 columns. On the left is the Ensembl gene ID for the 15920 protein-coding genes analyzed. The next column indicates which of the four analyzed gene sets each gene belongs to (MLL- MLL-AF9 bound; TOP - top 30% most highly expressed non-MLL-AF9 bound genes; MIDDLE - middle 40% expressed non-MLL-AF9 bound genes; BOTTOM - bottom 30% expressed non-MLL-AF9 bound genes). The 14 columns that follow indicate for each gene the ChIP-Seq signal in each of 14 bins, as described in the data processing section. ChIP-Seq signal is defined as mapped reads per kilobase per million reads.

Genome Build:
control_ShX_K9_2_TS2_6.bed: NCBI Build 37
control_shX_K9_Me2.txt: ENSEMBL version 64

source_name: Control MLL-AF9 AML cells, H3K9Me2 ChIP


title: Mock NT

description: Mock cells_untreated

source_name: Mock cells_untreated

value: infected with a mock vector (mock cells)


title: hfa rep 1

description: results file: mrna-read-counts.tsv

value: Fetal atrium

value: 90 days (approx)


title: Mock RA

description: Mock cells_treated with retinoic acid (RA)


title: high fat diet

tag: strain

tag: age

tag: tissue

value: LF


title: Anti-H3K4Me2 ChIP control

data_processing:
Sequencing reads were aligned to the genome (Mus_musculus NCBIM37) using Bowtie (Langmead et al. 2009) with default parameters. Total reads per sample ranged from 2.6 to 6.6 x10^6. Reads that mapped to multiple loci were discarded and the alignments from three technical replicate sets (anti-H3K9Me2 Kdm1a KD) were pooled. Subsequent analysis was performed in R and Bioconductor (Gentleman et al. 2004). Data were then segmented according to annotated transcription start- and end-sites (TSS; TES), as defined by ENSEMBL version 64 and supplied by the annmap database (Yates et al. 2007). Each gene was split into 10 equally spaced bins between the TSS and TES and the average read depth calculated for each region (expressed in reads per kilobase). Similar data were computed for two additional regions 10kB-2.5kB and 2.5kB-0kB upstream of the TSS and the equivalent regions downstream of the TES. In total, 14 regions per gene were considered. In order to explore global changes in histone methylation across the genome of each sample, four sets of genes were considered: MLL-AF9 target genes (n=114), and the remaining protein coding genes (n=15806), stratified into three groups by expression level (0 – 30th percentile, 30th – 70th percentile, 70th – 100th percentile), and the average read depth per bin computed for each set.

BED file: The .BED file contains reads uniquely mapped by Bowtie to the mouse genome for one sample, indicated by the file name. Each line in the .BED file corresponds to one read, showing the mapped location in the mouse genome, i.e. the chromosome, the start coordinate (minus 1), the end coordinate, and the strand.

TXT file: File has 16 columns. On the left is the Ensembl gene ID for the 15920 protein-coding genes analyzed. The next column indicates which of the four analyzed gene sets each gene belongs to (MLL- MLL-AF9 bound; TOP - top 30% most highly expressed non-MLL-AF9 bound genes; MIDDLE - middle 40% expressed non-MLL-AF9 bound genes; BOTTOM - bottom 30% expressed non-MLL-AF9 bound genes). The 14 columns that follow indicate for each gene the ChIP-Seq signal in each of 14 bins, as described in the data processing section. ChIP-Seq signal is defined as mapped reads per kilobase per million reads.

Genome Build:
control_ShX_K4_2_TS2_4.bed: NCBI Build 37
control_shX_K4_Me2.txt: ENSEMBL version 64

source_name: Control MLL-AF9 AML cells, H3K4Me2 ChIP

tag: cell type


title: lib840 [ABATE_007004_21]

data_processing:
Base-calling was performed automatically by Illumina real time analysis software and demultiplexing was performed on Illumina BaseSpace.
Hard trimming was performed in Galaxy; 1 3'-end base was removed from all reads using the FASTQ Trimmer tool (v1.0.0)
Quality-based trimming was performed in Galaxy; reads were trimmed from both ends using the FASTQ Quality Trimmer tool (v1.0.0) until minimum base quality for each read was >= 30.
Reads were aligned in Galaxy using bowtie and TopHat (Tophat for Illumina tool, v.1.5.0)
Read counts per Ensembl gene ID were estimated in Galaxy using htseq-count (htseq-count tool, v.0.4.1).
Sequencing, alignment, and quantitation metrics were obtained for FASTQ, BAM/SAM, and count files in Galaxy using FastQC, Picard, TopHat, Samtools, and htseq-count.
Genome_build: GRCh38
Supplementary_files_format_and_content: T1D_placebos_raw_counts.csv is a comma-delimited matrix. The first column ("ensgene") contains Ensembl gene IDs. The remaining columns include raw read counts assigned for each library. All samples that passed SNP-based identity checks are included, with 3 samples of uncertin provenance excluded. Data have not otherwise been filtered or normalized.

source_name: whole blood

tag: subject

tag: rate of c-peptide change

tag: visit day

tag: age at enrollment

tag: Sex

value: male

tag: race

value: White

tag: ethnicity

value: Not Hispanic or Latino

tag: library batch


title: lib882 [ABATE_002018_0]

value: female

value: White; Asian

tag: lymphocyte percent

tag: neutrophil percent