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Sample GSM1593875

Query DataSets for GSM1593875

Status

Public on Aug 01, 2015

Title

Ctrl.iPS1BC23_d14

Sample type

SRA

Source name

control_neuron derived from iPSC

Organism

Homo sapiens

Characteristics

subject group: Control
tissue/cell type: Day 14 neuron derived from iPSC
molecule subtype: small RNA

Extracted molecule

total RNA

Extraction protocol

total cellular RNA was isolated using the miRNeasy Kit (Qiagen) according to the manufacturer’s protocol
RNA libraries were prepared for sequencing using standard Illumina protocols. (1) Dilute Oligos and MgCl2 (2) Ligate the Small RNA 3' Adapter and 5' Adapter (3) Isolate Ligated Small RNA by Denaturing PAGE Gel (4) Recover the Isolated RNA (5) Reverse Transcribe and Amplify the Small RNA Ligated with Adapters (6) Purify the Amplified cDNA Construct

Library strategy

miRNA-Seq

Library source

transcriptomic

Library selection

size fractionation

Instrument model

Illumina HiSeq 2000

Data processing

First, 3’ adaptor sequences (TGGAATTCTCGGGTGCCAAGG) were removed from the raw miRNA-seq reads using a java script “AdRec.jar” from seqbuster. Out of the total, ~7% of reads were without adaptors. 92% of processed reads after adaptor trimming were 15-35bp in length. The trimmed reads were then mapped to known pre-miRNA sequences deposited in miRBase (hsa database from miRBASE20) (http://www.mirbase.org/), allowing for one mismatch at most using bowtie. For any read to be considered as from a known mature miRNA, its 5’ and 3’ ends needed to be within 1-3 bp from the 5’ and 3’ ends of the mature miRNAs annotated in miRBase, respectively. To avoid mis-mapping, all trimmed reads were also mapped to the human genome reference sequences (hg19). Any read with superior hits in non-microRNA genomic regions was discarded. We considered -5p and -3p derivatives of the same miRNA name as two separated miRNAs.
To determine differentially expressed (DE) miRNAs, we applied DESeq2 to analyze the read counts of all microRNAs. Specifically, DESeq2 models the variance in miRNA read counts across replicates using the negative binomial distribution and tests whether, for a given miRNA, the change in counts between the control and SZ/22q11.2 samples is significantly larger as compared to the variation within each replicate group. A nominally significant p-value of < 0.01 and fold change >1.5-fold were chosen as the cutoffs for identifying differentially expressed miRNAs between SZ and controls, but a multiple comparison correction was also applied to adjust the p-values for genome-wide significance.
Genome_build: miRBASE20
Supplementary_files_format_and_content: excel files for raw counts of all samples

Submission date

Jan 28, 2015

Last update date

May 15, 2019

Contact name

mingyan lin

E-mail(s)

mingyan.lin@phd.einstein.yu.edu

Organization name

aecom

Street address

1925 morris park ave