Standard DE analysis by using edgeR and limma::voom pipeline
de_analysis(
dge,
group_col,
target_group,
normalize = TRUE,
group = FALSE,
filter = c(10, 10),
plot = FALSE,
lfc = 0,
p = 0.05,
markers = NULL,
gene_id = "SYMBOL",
slot = "counts",
batch = NULL,
summary = TRUE,
...
)DGEList object for DE analysis, including expr and samples info
character, column name of coldata to specify the DE comparisons
pattern, specify the group of interest, e.g. NK
logical, if the expr in data is raw counts needs to be normalized
logical, TRUE to separate samples into only 2 groups: `target_group`` and 'Others'; FALSE to set each level as a group
a vector of 2 numbers, filter condition to remove low expression genes, the 1st for min.counts (if normalize = TRUE) or CPM/TPM (if normalize = FALSE), the 2nd for samples size 'large.n'
logical, if to make plots to show QC before and after filtration
num, cutoff of logFC for DE analysis
num, cutoff of p value for DE analysis and permutation test if feature_selection = "rankproduct"
vector, a vector of gene names, listed the gene symbols to be kept anyway after filtration. Default 'NULL' means no special genes need to be kept.
character, specify the gene ID target_group of rownames of expression data when markers is not NULL, could be one of 'ENSEMBL', 'SYMBOL', 'ENTREZ'..., default 'SYMBOL'
character, specify which slot to use for DGEList, default 'counts'
vector of character, column name(s) of coldata to be treated as batch effect factor, default NULL
logical, if to show the summary of DE analysis
omitted
MArrayLM object generated by limma::treat()
data("im_data_6")
dge <- edgeR::DGEList(
counts = Biobase::exprs(im_data_6),
samples = Biobase::pData(im_data_6)
)
de_analysis(dge, group_col = "celltype.ch1", target_group = "NK")
#> NK-Neutrophils NK-Monocytes NK-B.cells NK-CD4 NK-CD8
#> Down 4009 3944 3146 2694 2153
#> NotSig 1476 2678 4405 4985 6183
#> Up 4926 3789 2860 2732 2075
#> An object of class "DGEList"
#> $counts
#> GSM1479438 GSM1479439 GSM1479440 GSM1479441 GSM1479442
#> ENSG00000000419 41 18 12 14 20
#> ENSG00000000457 32 9 24 19 16
#> ENSG00000000460 4 5 9 4 6
#> ENSG00000000938 2804 1711 105 1 56
#> ENSG00000001036 2 58 4 6 7
#> GSM1479443 GSM1479499 GSM1479500 GSM1479501 GSM1479502
#> ENSG00000000419 15 48 23 16 24
#> ENSG00000000457 14 34 8 20 24
#> ENSG00000000460 6 4 6 12 10
#> ENSG00000000938 560 2085 1722 156 1
#> ENSG00000001036 12 4 85 8 6
#> GSM1479503 GSM1479504 GSM1479506 GSM1479507 GSM1479508
#> ENSG00000000419 20 18 39 24 18
#> ENSG00000000457 17 16 40 9 18
#> ENSG00000000460 12 10 7 4 12
#> ENSG00000000938 43 657 2406 1672 150
#> ENSG00000001036 4 14 4 83 7
#> GSM1479509 GSM1479510 GSM1479511 GSM1479520 GSM1479521
#> ENSG00000000419 19 25 21 45 19
#> ENSG00000000457 18 12 15 33 7
#> ENSG00000000460 7 7 7 3 5
#> ENSG00000000938 22 176 573 2963 1529
#> ENSG00000001036 6 6 18 8 83
#> GSM1479522 GSM1479523 GSM1479524 GSM1479525
#> ENSG00000000419 20 20 30 21
#> ENSG00000000457 17 18 14 15
#> ENSG00000000460 9 7 7 6
#> ENSG00000000938 217 2 63 494
#> ENSG00000001036 8 7 5 13
#> 10406 more rows ...
#>
#> $samples
#> group lib.size norm.factors title geo_accession
#> GSM1479438 Neutrophils 1788397 0.4912341 lib226 GSM1479438
#> GSM1479439 Monocytes 1187419 0.8737218 lib227 GSM1479439
#> GSM1479440 B.cells 905677 1.1114484 lib228 GSM1479440
#> GSM1479441 CD4 804306 1.2167386 lib229 GSM1479441
#> GSM1479442 CD8 898835 1.1699504 lib230 GSM1479442
#> status submission_date last_update_date type
#> GSM1479438 Public on Jan 06 2015 Aug 14 2014 May 15 2019 SRA
#> GSM1479439 Public on Jan 06 2015 Aug 14 2014 May 15 2019 SRA
#> GSM1479440 Public on Jan 06 2015 Aug 14 2014 May 15 2019 SRA
#> GSM1479441 Public on Jan 06 2015 Aug 14 2014 May 15 2019 SRA
#> GSM1479442 Public on Jan 06 2015 Aug 14 2014 May 15 2019 SRA
#> channel_count source_name_ch1 organism_ch1 characteristics_ch1
#> GSM1479438 1 Whole Blood Homo sapiens age: 32
#> GSM1479439 1 Whole Blood Homo sapiens age: 32
#> GSM1479440 1 Whole Blood Homo sapiens age: 32
#> GSM1479441 1 Whole Blood Homo sapiens age: 32
#> GSM1479442 1 Whole Blood Homo sapiens age: 32
#> characteristics_ch1.1 characteristics_ch1.2
#> GSM1479438 cellcount: 14737500 celltype: Neutrophils
#> GSM1479439 cellcount: 2000000 celltype: Monocytes
#> GSM1479440 cellcount: 1012333 celltype: B-cells
#> GSM1479441 cellcount: 1071990 celltype: CD4
#> GSM1479442 cellcount: 1011154 celltype: CD8
#> characteristics_ch1.3 characteristics_ch1.4
#> GSM1479438 collectiondate: June 26 2012 diseasestatus: Healthy Control
#> GSM1479439 collectiondate: June 26 2012 diseasestatus: Healthy Control
#> GSM1479440 collectiondate: June 26 2012 diseasestatus: Healthy Control
#> GSM1479441 collectiondate: June 26 2012 diseasestatus: Healthy Control
#> GSM1479442 collectiondate: June 26 2012 diseasestatus: Healthy Control
#> characteristics_ch1.5 characteristics_ch1.6 characteristics_ch1.7
#> GSM1479438 donorid: 44 gender: F index: 5
#> GSM1479439 donorid: 44 gender: F index: 23
#> GSM1479440 donorid: 44 gender: F index: 6
#> GSM1479441 donorid: 44 gender: F index: 25
#> GSM1479442 donorid: 44 gender: F index: 12
#> characteristics_ch1.8 characteristics_ch1.9
#> GSM1479438 race: Hispanic samplename: 44_Neutrophils
#> GSM1479439 race: Hispanic samplename: 44_Monocytes
#> GSM1479440 race: Hispanic samplename: 44_Bcells
#> GSM1479441 race: Hispanic samplename: 44_CD4T
#> GSM1479442 race: Hispanic samplename: 44_CD8T
#> characteristics_ch1.10 characteristics_ch1.11
#> GSM1479438 smoker: -- time since last flare (months): --
#> GSM1479439 smoker: -- time since last flare (months): --
#> GSM1479440 smoker: -- time since last flare (months): --
#> GSM1479441 smoker: -- time since last flare (months): --
#> GSM1479442 smoker: -- time since last flare (months): --
#> characteristics_ch1.12 characteristics_ch1.13
#> GSM1479438 time since steroid dose: -- time since symptom onset (yrs): --
#> GSM1479439 time since steroid dose: -- time since symptom onset (yrs): --
#> GSM1479440 time since steroid dose: -- time since symptom onset (yrs): --
#> GSM1479441 time since steroid dose: -- time since symptom onset (yrs): --
#> GSM1479442 time since steroid dose: -- time since symptom onset (yrs): --
#> characteristics_ch1.14 molecule_ch1
#> GSM1479438 years since diagnosis: -- total RNA
#> GSM1479439 years since diagnosis: -- total RNA
#> GSM1479440 years since diagnosis: -- total RNA
#> GSM1479441 years since diagnosis: -- total RNA
#> GSM1479442 years since diagnosis: -- total RNA
#> extract_protocol_ch1
#> GSM1479438 Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
#> GSM1479439 Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
#> GSM1479440 Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
#> GSM1479441 Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
#> GSM1479442 Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
#> taxid_ch1
#> GSM1479438 9606
#> GSM1479439 9606
#> GSM1479440 9606
#> GSM1479441 9606
#> GSM1479442 9606
#> data_processing
#> GSM1479438 fastq files were created from .bcl files via Illumina's CASAVA 1.8.2
#> GSM1479439 fastq files were created from .bcl files via Illumina's CASAVA 1.8.2
#> GSM1479440 fastq files were created from .bcl files via Illumina's CASAVA 1.8.2
#> GSM1479441 fastq files were created from .bcl files via Illumina's CASAVA 1.8.2
#> GSM1479442 fastq files were created from .bcl files via Illumina's CASAVA 1.8.2
#> data_processing.1
#> GSM1479438 reads were aligned to Hg19 via Omicsoft sequence aligner (OSA) version 2.0.1
#> GSM1479439 reads were aligned to Hg19 via Omicsoft sequence aligner (OSA) version 2.0.1
#> GSM1479440 reads were aligned to Hg19 via Omicsoft sequence aligner (OSA) version 2.0.1
#> GSM1479441 reads were aligned to Hg19 via Omicsoft sequence aligner (OSA) version 2.0.1
#> GSM1479442 reads were aligned to Hg19 via Omicsoft sequence aligner (OSA) version 2.0.1
#> data_processing.2
#> GSM1479438 gene counts were generated by HTSeq version 0.5.4p3
#> GSM1479439 gene counts were generated by HTSeq version 0.5.4p3
#> GSM1479440 gene counts were generated by HTSeq version 0.5.4p3
#> GSM1479441 gene counts were generated by HTSeq version 0.5.4p3
#> GSM1479442 gene counts were generated by HTSeq version 0.5.4p3
#> data_processing.3
#> GSM1479438 TMMs were generated with Bioconductor package EdgeR
#> GSM1479439 TMMs were generated with Bioconductor package EdgeR
#> GSM1479440 TMMs were generated with Bioconductor package EdgeR
#> GSM1479441 TMMs were generated with Bioconductor package EdgeR
#> GSM1479442 TMMs were generated with Bioconductor package EdgeR
#> data_processing.4
#> GSM1479438 Genome_build: Hg19
#> GSM1479439 Genome_build: Hg19
#> GSM1479440 Genome_build: Hg19
#> GSM1479441 Genome_build: Hg19
#> GSM1479442 Genome_build: Hg19
#> data_processing.5
#> GSM1479438 Supplementary_files_format_and_content: tab delimited file contains TMM normalized counts
#> GSM1479439 Supplementary_files_format_and_content: tab delimited file contains TMM normalized counts
#> GSM1479440 Supplementary_files_format_and_content: tab delimited file contains TMM normalized counts
#> GSM1479441 Supplementary_files_format_and_content: tab delimited file contains TMM normalized counts
#> GSM1479442 Supplementary_files_format_and_content: tab delimited file contains TMM normalized counts
#> platform_id contact_name contact_email
#> GSM1479438 GPL15456 Scott,,Presnell SPresnell@benaroyaresearch.org
#> GSM1479439 GPL15456 Scott,,Presnell SPresnell@benaroyaresearch.org
#> GSM1479440 GPL15456 Scott,,Presnell SPresnell@benaroyaresearch.org
#> GSM1479441 GPL15456 Scott,,Presnell SPresnell@benaroyaresearch.org
#> GSM1479442 GPL15456 Scott,,Presnell SPresnell@benaroyaresearch.org
#> contact_department contact_institute contact_address
#> GSM1479438 Systems Immunology Benaroya Research Institute 1201 Ninth Ave.
#> GSM1479439 Systems Immunology Benaroya Research Institute 1201 Ninth Ave.
#> GSM1479440 Systems Immunology Benaroya Research Institute 1201 Ninth Ave.
#> GSM1479441 Systems Immunology Benaroya Research Institute 1201 Ninth Ave.
#> GSM1479442 Systems Immunology Benaroya Research Institute 1201 Ninth Ave.
#> contact_city contact_state contact_zip.postal_code contact_country
#> GSM1479438 Seattle WA 98101 USA
#> GSM1479439 Seattle WA 98101 USA
#> GSM1479440 Seattle WA 98101 USA
#> GSM1479441 Seattle WA 98101 USA
#> GSM1479442 Seattle WA 98101 USA
#> data_row_count instrument_model library_selection library_source
#> GSM1479438 0 Illumina HiScanSQ cDNA transcriptomic
#> GSM1479439 0 Illumina HiScanSQ cDNA transcriptomic
#> GSM1479440 0 Illumina HiScanSQ cDNA transcriptomic
#> GSM1479441 0 Illumina HiScanSQ cDNA transcriptomic
#> GSM1479442 0 Illumina HiScanSQ cDNA transcriptomic
#> library_strategy
#> GSM1479438 RNA-Seq
#> GSM1479439 RNA-Seq
#> GSM1479440 RNA-Seq
#> GSM1479441 RNA-Seq
#> GSM1479442 RNA-Seq
#> relation
#> GSM1479438 BioSample: https://www.ncbi.nlm.nih.gov/biosample/SAMN02990322
#> GSM1479439 BioSample: https://www.ncbi.nlm.nih.gov/biosample/SAMN02990323
#> GSM1479440 BioSample: https://www.ncbi.nlm.nih.gov/biosample/SAMN02990324
#> GSM1479441 BioSample: https://www.ncbi.nlm.nih.gov/biosample/SAMN02990325
#> GSM1479442 BioSample: https://www.ncbi.nlm.nih.gov/biosample/SAMN02990331
#> relation.1
#> GSM1479438 SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRX680546
#> GSM1479439 SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRX680547
#> GSM1479440 SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRX680548
#> GSM1479441 SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRX680549
#> GSM1479442 SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRX680550
#> supplementary_file_1 age.ch1 cellcount.ch1 celltype.ch1
#> GSM1479438 NONE 32 14737500 Neutrophils
#> GSM1479439 NONE 32 2000000 Monocytes
#> GSM1479440 NONE 32 1012333 B-cells
#> GSM1479441 NONE 32 1071990 CD4
#> GSM1479442 NONE 32 1011154 CD8
#> collectiondate.ch1 diseasestatus.ch1 donorid.ch1 gender.ch1
#> GSM1479438 June 26 2012 Healthy Control 44 F
#> GSM1479439 June 26 2012 Healthy Control 44 F
#> GSM1479440 June 26 2012 Healthy Control 44 F
#> GSM1479441 June 26 2012 Healthy Control 44 F
#> GSM1479442 June 26 2012 Healthy Control 44 F
#> index.ch1 race.ch1 samplename.ch1 smoker.ch1
#> GSM1479438 5 Hispanic 44_Neutrophils --
#> GSM1479439 23 Hispanic 44_Monocytes --
#> GSM1479440 6 Hispanic 44_Bcells --
#> GSM1479441 25 Hispanic 44_CD4T --
#> GSM1479442 12 Hispanic 44_CD8T --
#> time.since.last.flare..months..ch1 time.since.steroid.dose.ch1
#> GSM1479438 -- --
#> GSM1479439 -- --
#> GSM1479440 -- --
#> GSM1479441 -- --
#> GSM1479442 -- --
#> time.since.symptom.onset..yrs..ch1 years.since.diagnosis.ch1
#> GSM1479438 -- --
#> GSM1479439 -- --
#> GSM1479440 -- --
#> GSM1479441 -- --
#> GSM1479442 -- --
#> 19 more rows ...
#>
#> $original_counts
#> GSM1479438 GSM1479439 GSM1479440 GSM1479441 GSM1479442
#> ENSG00000000003 0 0 0 2 1
#> ENSG00000000005 0 0 0 0 0
#> ENSG00000000419 41 18 12 14 20
#> ENSG00000000457 32 9 24 19 16
#> ENSG00000000460 4 5 9 4 6
#> GSM1479443 GSM1479499 GSM1479500 GSM1479501 GSM1479502
#> ENSG00000000003 0 0 0 0 3
#> ENSG00000000005 0 0 0 0 0
#> ENSG00000000419 15 48 23 16 24
#> ENSG00000000457 14 34 8 20 24
#> ENSG00000000460 6 4 6 12 10
#> GSM1479503 GSM1479504 GSM1479506 GSM1479507 GSM1479508
#> ENSG00000000003 2 0 0 0 0
#> ENSG00000000005 0 0 0 0 0
#> ENSG00000000419 20 18 39 24 18
#> ENSG00000000457 17 16 40 9 18
#> ENSG00000000460 12 10 7 4 12
#> GSM1479509 GSM1479510 GSM1479511 GSM1479520 GSM1479521
#> ENSG00000000003 2 1 0 0 0
#> ENSG00000000005 0 0 0 0 0
#> ENSG00000000419 19 25 21 45 19
#> ENSG00000000457 18 12 15 33 7
#> ENSG00000000460 7 7 7 3 5
#> GSM1479522 GSM1479523 GSM1479524 GSM1479525
#> ENSG00000000003 0 2 1 0
#> ENSG00000000005 0 0 0 0
#> ENSG00000000419 20 20 30 21
#> ENSG00000000457 17 18 14 15
#> ENSG00000000460 9 7 7 6
#> 50040 more rows ...
#>
#> $vfit
#> $targets
#> group lib.size norm.factors title geo_accession
#> GSM1479438 Neutrophils 878521.6 0.4912341 lib226 GSM1479438
#> GSM1479439 Monocytes 1037473.8 0.8737218 lib227 GSM1479439
#> GSM1479440 B.cells 1006613.2 1.1114484 lib228 GSM1479440
#> GSM1479441 CD4 978630.2 1.2167386 lib229 GSM1479441
#> GSM1479442 CD8 1051592.3 1.1699504 lib230 GSM1479442
#> status submission_date last_update_date type
#> GSM1479438 Public on Jan 06 2015 Aug 14 2014 May 15 2019 SRA
#> GSM1479439 Public on Jan 06 2015 Aug 14 2014 May 15 2019 SRA
#> GSM1479440 Public on Jan 06 2015 Aug 14 2014 May 15 2019 SRA
#> GSM1479441 Public on Jan 06 2015 Aug 14 2014 May 15 2019 SRA
#> GSM1479442 Public on Jan 06 2015 Aug 14 2014 May 15 2019 SRA
#> channel_count source_name_ch1 organism_ch1 characteristics_ch1
#> GSM1479438 1 Whole Blood Homo sapiens age: 32
#> GSM1479439 1 Whole Blood Homo sapiens age: 32
#> GSM1479440 1 Whole Blood Homo sapiens age: 32
#> GSM1479441 1 Whole Blood Homo sapiens age: 32
#> GSM1479442 1 Whole Blood Homo sapiens age: 32
#> characteristics_ch1.1 characteristics_ch1.2
#> GSM1479438 cellcount: 14737500 celltype: Neutrophils
#> GSM1479439 cellcount: 2000000 celltype: Monocytes
#> GSM1479440 cellcount: 1012333 celltype: B-cells
#> GSM1479441 cellcount: 1071990 celltype: CD4
#> GSM1479442 cellcount: 1011154 celltype: CD8
#> characteristics_ch1.3 characteristics_ch1.4
#> GSM1479438 collectiondate: June 26 2012 diseasestatus: Healthy Control
#> GSM1479439 collectiondate: June 26 2012 diseasestatus: Healthy Control
#> GSM1479440 collectiondate: June 26 2012 diseasestatus: Healthy Control
#> GSM1479441 collectiondate: June 26 2012 diseasestatus: Healthy Control
#> GSM1479442 collectiondate: June 26 2012 diseasestatus: Healthy Control
#> characteristics_ch1.5 characteristics_ch1.6 characteristics_ch1.7
#> GSM1479438 donorid: 44 gender: F index: 5
#> GSM1479439 donorid: 44 gender: F index: 23
#> GSM1479440 donorid: 44 gender: F index: 6
#> GSM1479441 donorid: 44 gender: F index: 25
#> GSM1479442 donorid: 44 gender: F index: 12
#> characteristics_ch1.8 characteristics_ch1.9
#> GSM1479438 race: Hispanic samplename: 44_Neutrophils
#> GSM1479439 race: Hispanic samplename: 44_Monocytes
#> GSM1479440 race: Hispanic samplename: 44_Bcells
#> GSM1479441 race: Hispanic samplename: 44_CD4T
#> GSM1479442 race: Hispanic samplename: 44_CD8T
#> characteristics_ch1.10 characteristics_ch1.11
#> GSM1479438 smoker: -- time since last flare (months): --
#> GSM1479439 smoker: -- time since last flare (months): --
#> GSM1479440 smoker: -- time since last flare (months): --
#> GSM1479441 smoker: -- time since last flare (months): --
#> GSM1479442 smoker: -- time since last flare (months): --
#> characteristics_ch1.12 characteristics_ch1.13
#> GSM1479438 time since steroid dose: -- time since symptom onset (yrs): --
#> GSM1479439 time since steroid dose: -- time since symptom onset (yrs): --
#> GSM1479440 time since steroid dose: -- time since symptom onset (yrs): --
#> GSM1479441 time since steroid dose: -- time since symptom onset (yrs): --
#> GSM1479442 time since steroid dose: -- time since symptom onset (yrs): --
#> characteristics_ch1.14 molecule_ch1
#> GSM1479438 years since diagnosis: -- total RNA
#> GSM1479439 years since diagnosis: -- total RNA
#> GSM1479440 years since diagnosis: -- total RNA
#> GSM1479441 years since diagnosis: -- total RNA
#> GSM1479442 years since diagnosis: -- total RNA
#> extract_protocol_ch1
#> GSM1479438 Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
#> GSM1479439 Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
#> GSM1479440 Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
#> GSM1479441 Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
#> GSM1479442 Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
#> taxid_ch1
#> GSM1479438 9606
#> GSM1479439 9606
#> GSM1479440 9606
#> GSM1479441 9606
#> GSM1479442 9606
#> data_processing
#> GSM1479438 fastq files were created from .bcl files via Illumina's CASAVA 1.8.2
#> GSM1479439 fastq files were created from .bcl files via Illumina's CASAVA 1.8.2
#> GSM1479440 fastq files were created from .bcl files via Illumina's CASAVA 1.8.2
#> GSM1479441 fastq files were created from .bcl files via Illumina's CASAVA 1.8.2
#> GSM1479442 fastq files were created from .bcl files via Illumina's CASAVA 1.8.2
#> data_processing.1
#> GSM1479438 reads were aligned to Hg19 via Omicsoft sequence aligner (OSA) version 2.0.1
#> GSM1479439 reads were aligned to Hg19 via Omicsoft sequence aligner (OSA) version 2.0.1
#> GSM1479440 reads were aligned to Hg19 via Omicsoft sequence aligner (OSA) version 2.0.1
#> GSM1479441 reads were aligned to Hg19 via Omicsoft sequence aligner (OSA) version 2.0.1
#> GSM1479442 reads were aligned to Hg19 via Omicsoft sequence aligner (OSA) version 2.0.1
#> data_processing.2
#> GSM1479438 gene counts were generated by HTSeq version 0.5.4p3
#> GSM1479439 gene counts were generated by HTSeq version 0.5.4p3
#> GSM1479440 gene counts were generated by HTSeq version 0.5.4p3
#> GSM1479441 gene counts were generated by HTSeq version 0.5.4p3
#> GSM1479442 gene counts were generated by HTSeq version 0.5.4p3
#> data_processing.3
#> GSM1479438 TMMs were generated with Bioconductor package EdgeR
#> GSM1479439 TMMs were generated with Bioconductor package EdgeR
#> GSM1479440 TMMs were generated with Bioconductor package EdgeR
#> GSM1479441 TMMs were generated with Bioconductor package EdgeR
#> GSM1479442 TMMs were generated with Bioconductor package EdgeR
#> data_processing.4
#> GSM1479438 Genome_build: Hg19
#> GSM1479439 Genome_build: Hg19
#> GSM1479440 Genome_build: Hg19
#> GSM1479441 Genome_build: Hg19
#> GSM1479442 Genome_build: Hg19
#> data_processing.5
#> GSM1479438 Supplementary_files_format_and_content: tab delimited file contains TMM normalized counts
#> GSM1479439 Supplementary_files_format_and_content: tab delimited file contains TMM normalized counts
#> GSM1479440 Supplementary_files_format_and_content: tab delimited file contains TMM normalized counts
#> GSM1479441 Supplementary_files_format_and_content: tab delimited file contains TMM normalized counts
#> GSM1479442 Supplementary_files_format_and_content: tab delimited file contains TMM normalized counts
#> platform_id contact_name contact_email
#> GSM1479438 GPL15456 Scott,,Presnell SPresnell@benaroyaresearch.org
#> GSM1479439 GPL15456 Scott,,Presnell SPresnell@benaroyaresearch.org
#> GSM1479440 GPL15456 Scott,,Presnell SPresnell@benaroyaresearch.org
#> GSM1479441 GPL15456 Scott,,Presnell SPresnell@benaroyaresearch.org
#> GSM1479442 GPL15456 Scott,,Presnell SPresnell@benaroyaresearch.org
#> contact_department contact_institute contact_address
#> GSM1479438 Systems Immunology Benaroya Research Institute 1201 Ninth Ave.
#> GSM1479439 Systems Immunology Benaroya Research Institute 1201 Ninth Ave.
#> GSM1479440 Systems Immunology Benaroya Research Institute 1201 Ninth Ave.
#> GSM1479441 Systems Immunology Benaroya Research Institute 1201 Ninth Ave.
#> GSM1479442 Systems Immunology Benaroya Research Institute 1201 Ninth Ave.
#> contact_city contact_state contact_zip.postal_code contact_country
#> GSM1479438 Seattle WA 98101 USA
#> GSM1479439 Seattle WA 98101 USA
#> GSM1479440 Seattle WA 98101 USA
#> GSM1479441 Seattle WA 98101 USA
#> GSM1479442 Seattle WA 98101 USA
#> data_row_count instrument_model library_selection library_source
#> GSM1479438 0 Illumina HiScanSQ cDNA transcriptomic
#> GSM1479439 0 Illumina HiScanSQ cDNA transcriptomic
#> GSM1479440 0 Illumina HiScanSQ cDNA transcriptomic
#> GSM1479441 0 Illumina HiScanSQ cDNA transcriptomic
#> GSM1479442 0 Illumina HiScanSQ cDNA transcriptomic
#> library_strategy
#> GSM1479438 RNA-Seq
#> GSM1479439 RNA-Seq
#> GSM1479440 RNA-Seq
#> GSM1479441 RNA-Seq
#> GSM1479442 RNA-Seq
#> relation
#> GSM1479438 BioSample: https://www.ncbi.nlm.nih.gov/biosample/SAMN02990322
#> GSM1479439 BioSample: https://www.ncbi.nlm.nih.gov/biosample/SAMN02990323
#> GSM1479440 BioSample: https://www.ncbi.nlm.nih.gov/biosample/SAMN02990324
#> GSM1479441 BioSample: https://www.ncbi.nlm.nih.gov/biosample/SAMN02990325
#> GSM1479442 BioSample: https://www.ncbi.nlm.nih.gov/biosample/SAMN02990331
#> relation.1
#> GSM1479438 SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRX680546
#> GSM1479439 SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRX680547
#> GSM1479440 SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRX680548
#> GSM1479441 SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRX680549
#> GSM1479442 SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRX680550
#> supplementary_file_1 age.ch1 cellcount.ch1 celltype.ch1
#> GSM1479438 NONE 32 14737500 Neutrophils
#> GSM1479439 NONE 32 2000000 Monocytes
#> GSM1479440 NONE 32 1012333 B-cells
#> GSM1479441 NONE 32 1071990 CD4
#> GSM1479442 NONE 32 1011154 CD8
#> collectiondate.ch1 diseasestatus.ch1 donorid.ch1 gender.ch1
#> GSM1479438 June 26 2012 Healthy Control 44 F
#> GSM1479439 June 26 2012 Healthy Control 44 F
#> GSM1479440 June 26 2012 Healthy Control 44 F
#> GSM1479441 June 26 2012 Healthy Control 44 F
#> GSM1479442 June 26 2012 Healthy Control 44 F
#> index.ch1 race.ch1 samplename.ch1 smoker.ch1
#> GSM1479438 5 Hispanic 44_Neutrophils --
#> GSM1479439 23 Hispanic 44_Monocytes --
#> GSM1479440 6 Hispanic 44_Bcells --
#> GSM1479441 25 Hispanic 44_CD4T --
#> GSM1479442 12 Hispanic 44_CD8T --
#> time.since.last.flare..months..ch1 time.since.steroid.dose.ch1
#> GSM1479438 -- --
#> GSM1479439 -- --
#> GSM1479440 -- --
#> GSM1479441 -- --
#> GSM1479442 -- --
#> time.since.symptom.onset..yrs..ch1 years.since.diagnosis.ch1
#> GSM1479438 -- --
#> GSM1479439 -- --
#> GSM1479440 -- --
#> GSM1479441 -- --
#> GSM1479442 -- --
#> 19 more rows ...
#>
#> $E
#> GSM1479438 GSM1479439 GSM1479440 GSM1479441 GSM1479442
#> ENSG00000000419 5.561888 4.156377 3.634345 3.8891439 4.284975
#> ENSG00000000457 5.209216 3.194851 4.605199 4.3165651 3.971817
#> ENSG00000000460 2.356774 2.406355 3.238417 2.2010879 2.627863
#> ENSG00000000938 11.640376 10.687969 6.711588 0.6161254 5.747602
#> ENSG00000001036 1.508777 5.817288 2.160414 2.7316026 2.834314
#> GSM1479443 GSM1479499 GSM1479500 GSM1479501 GSM1479502
#> ENSG00000000419 4.045304 5.745972 4.540885 4.067716 4.5665245
#> ENSG00000000457 3.949089 5.254584 3.073759 4.380874 4.5665245
#> ENSG00000000460 2.791548 2.315984 2.686736 3.667178 3.3441321
#> ENSG00000000938 9.221678 11.172237 10.736584 7.313340 0.5367771
#> ENSG00000001036 3.734964 2.315984 6.404149 3.110784 2.6522544
#> GSM1479503 GSM1479504 GSM1479506 GSM1479507 GSM1479508
#> ENSG00000000419 4.426140 4.190749 5.374778 4.575686 4.137289
#> ENSG00000000457 4.197871 4.025690 5.410847 3.208904 4.137289
#> ENSG00000000460 3.712444 3.373613 2.977888 2.130901 3.571692
#> ENSG00000000938 5.511532 9.342143 11.303718 10.668767 7.161455
#> ENSG00000001036 2.238513 3.839277 2.240922 6.344680 2.834726
#> GSM1479509 GSM1479510 GSM1479511 GSM1479520 GSM1479521
#> ENSG00000000419 4.310208 4.697389 4.334526 5.623372 4.272855
#> ENSG00000000457 4.234259 3.668820 3.862458 5.181666 2.894343
#> ENSG00000000460 2.931697 2.931855 2.815152 1.922932 2.446884
#> ENSG00000000938 4.516659 7.488488 9.071911 11.648663 10.566297
#> ENSG00000001036 2.725246 2.725404 4.117715 3.203040 6.371157
#> GSM1479522 GSM1479523 GSM1479524 GSM1479525
#> ENSG00000000419 4.352512 4.398337 4.944876 4.405879
#> ENSG00000000457 4.124243 4.250238 3.872119 3.933810
#> ENSG00000000460 3.242887 2.947675 2.921029 2.680054
#> ENSG00000000938 7.759831 1.362713 6.002823 8.929441
#> ENSG00000001036 3.082422 2.947675 2.473570 3.734501
#> 10406 more rows ...
#>
#> $weights
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7]
#> [1,] 21.081591 15.225924 13.040102 14.184000 16.529104 13.57572 21.342178
#> [2,] 19.069471 8.147300 14.538571 14.476242 12.722322 11.90197 19.329896
#> [3,] 5.072784 5.643265 9.645769 6.772721 8.028387 6.76890 5.148148
#> [4,] 17.930722 19.113163 26.851705 4.384886 25.671321 23.13860 17.843145
#> [5,] 4.947266 25.764631 6.703949 6.439601 6.131992 11.42502 5.011334
#> [,8] [,9] [,10] [,11] [,12] [,13] [,14]
#> [1,] 14.995871 12.856636 14.643379 15.697280 14.200630 21.832334 15.143312
#> [2,] 7.962217 14.347984 14.937717 11.941789 12.509128 19.805415 8.080631
#> [3,] 5.542574 9.468695 7.084220 7.396865 7.204429 5.293314 5.606339
#> [4,] 19.202068 26.878913 4.489187 25.127831 22.852165 17.682074 19.144835
#> [5,] 25.625806 6.584327 6.725297 5.719272 12.029642 5.146002 25.720647
#> [,15] [,16] [,17] [,18] [,19] [,20] [,21]
#> [1,] 13.392960 14.220132 15.953070 14.623401 21.539551 14.989181 13.014929
#> [2,] 14.903115 14.513308 12.179474 12.911372 19.522159 7.956862 14.512435
#> [3,] 9.980621 6.797037 7.585686 7.513552 5.205385 5.539855 9.621417
#> [4,] 26.796226 4.393136 25.309223 22.663097 17.777537 19.204686 26.855408
#> [5,] 6.944336 6.461924 5.837830 12.434619 5.063746 25.621486 6.687502
#> [,22] [,23] [,24]
#> [1,] 14.129527 16.017353 14.210193
#> [2,] 14.420363 12.239372 12.518724
#> [3,] 6.736345 7.633475 7.211367
#> [4,] 4.372437 25.349095 22.847811
#> [5,] 6.405998 5.867726 12.038781
#> 10406 more rows ...
#>
#> $design
#> B.cells CD4 CD8 Monocytes NK Neutrophils
#> GSM1479438 0 0 0 0 0 1
#> GSM1479439 0 0 0 1 0 0
#> GSM1479440 1 0 0 0 0 0
#> GSM1479441 0 1 0 0 0 0
#> GSM1479442 0 0 1 0 0 0
#> 19 more rows ...
#>
#>
#> $tfit
#> $coefficients
#> Contrasts
#> NK-Neutrophils NK-Monocytes NK-B.cells NK-CD4
#> ENSG00000000419 -1.3284904 -0.1390368 0.1986597 -0.04616467
#> ENSG00000000457 -1.3229214 0.8480238 -0.3686330 -0.40165793
#> ENSG00000000460 0.5195102 0.4989879 -0.5144683 0.05419011
#> ENSG00000000938 -2.2999151 -1.5231729 1.9050683 7.38928195
#> ENSG00000001036 1.5387902 -2.3735193 1.0644773 1.09763610
#> Contrasts
#> NK-CD8
#> ENSG00000000419 -0.33961447
#> ENSG00000000457 0.01526575
#> ENSG00000000460 -0.12209992
#> ENSG00000000938 2.95452137
#> ENSG00000001036 1.28751737
#> 10406 more rows ...
#>
#> $stdev.unscaled
#> Contrasts
#> NK-Neutrophils NK-Monocytes NK-B.cells NK-CD4 NK-CD8
#> ENSG00000000419 0.1712318 0.1850232 0.1917903 0.1874947 0.1823235
#> ENSG00000000457 0.1814643 0.2262097 0.1929139 0.1928792 0.2010905
#> ENSG00000000460 0.2882859 0.2821774 0.2463212 0.2671228 0.2597647
#> ENSG00000000938 0.1580098 0.1548308 0.1422719 0.2600370 0.1441704
#> ENSG00000001036 0.2654190 0.1749246 0.2408559 0.2434700 0.2516250
#> 10406 more rows ...
#>
#> $sigma
#> [1] 0.9368969 0.5956268 0.9710709 2.6598431 1.0524317
#> 10406 more elements ...
#>
#> $df.residual
#> [1] 18 18 18 18 18
#> 10406 more elements ...
#>
#> $cov.coefficients
#> Contrasts
#> Contrasts NK-Neutrophils NK-Monocytes NK-B.cells NK-CD4 NK-CD8
#> NK-Neutrophils 0.50 0.25 0.25 0.25 0.25
#> NK-Monocytes 0.25 0.50 0.25 0.25 0.25
#> NK-B.cells 0.25 0.25 0.50 0.25 0.25
#> NK-CD4 0.25 0.25 0.25 0.50 0.25
#> NK-CD8 0.25 0.25 0.25 0.25 0.50
#>
#> $pivot
#> [1] 1 2 3 4 5 6
#>
#> $rank
#> [1] 6
#>
#> $Amean
#> ENSG00000000419 ENSG00000000457 ENSG00000000460 ENSG00000000938 ENSG00000001036
#> 4.522405 4.146876 2.843449 7.738280 3.422891
#> 10406 more elements ...
#>
#> $method
#> [1] "ls"
#>
#> $design
#> B.cells CD4 CD8 Monocytes NK Neutrophils
#> GSM1479438 0 0 0 0 0 1
#> GSM1479439 0 0 0 1 0 0
#> GSM1479440 1 0 0 0 0 0
#> GSM1479441 0 1 0 0 0 0
#> GSM1479442 0 0 1 0 0 0
#> 19 more rows ...
#>
#> $contrasts
#> Contrasts
#> Levels NK-Neutrophils NK-Monocytes NK-B.cells NK-CD4 NK-CD8
#> B.cells 0 0 -1 0 0
#> CD4 0 0 0 -1 0
#> CD8 0 0 0 0 -1
#> Monocytes 0 -1 0 0 0
#> NK 1 1 1 1 1
#> Neutrophils -1 0 0 0 0
#>
#> $df.prior
#> [1] 3.955315
#>
#> $s2.prior
#> [1] 0.7780205
#>
#> $s2.post
#> [1] 0.8598046 0.4310209 0.9132609 5.9403881 1.0482354
#> 10406 more elements ...
#>
#> $df.total
#> [1] 21.95532 21.95532 21.95532 21.95532 21.95532
#> 10406 more elements ...
#>
#> $t
#> Contrasts
#> NK-Neutrophils NK-Monocytes NK-B.cells NK-CD4 NK-CD8
#> ENSG00000000419 -8.367082 -0.8104083 1.117077 -0.2655344 -2.0088328
#> ENSG00000000457 -11.104367 5.7101526 -2.910594 -3.1719169 0.1156318
#> ENSG00000000460 1.885703 1.8504203 -2.185544 0.2122813 -0.4918558
#> ENSG00000000938 -5.972007 -4.0363102 5.493942 11.6589564 8.4082104
#> ENSG00000001036 5.662627 -13.2529470 4.316679 4.4033525 4.9976960
#> 10406 more rows ...
#>
#> $p.value
#> Contrasts
#> NK-Neutrophils NK-Monocytes NK-B.cells NK-CD4
#> ENSG00000000419 2.824919e-08 4.264031e-01 2.760372e-01 7.930752e-01
#> ENSG00000000457 1.779197e-10 9.695341e-06 8.116642e-03 4.421964e-03
#> ENSG00000000460 7.263599e-02 7.775660e-02 3.980415e-02 8.338460e-01
#> ENSG00000000938 5.245672e-06 5.538663e-04 1.618494e-05 7.081695e-11
#> ENSG00000001036 1.084705e-05 5.946509e-12 2.794616e-04 2.261660e-04
#> Contrasts
#> NK-CD8
#> ENSG00000000419 5.700893e-02
#> ENSG00000000457 9.089954e-01
#> ENSG00000000460 6.277031e-01
#> ENSG00000000938 2.599667e-08
#> ENSG00000001036 5.327634e-05
#> 10406 more rows ...
#>
#> $treat.lfc
#> [1] 0
#>
#>